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ORCID26th KDD 2020: Virtual Conference, USA
- Rajesh Gupta, Yan Liu, Jiliang Tang, B. Aditya Prakash:
KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Virtual Event, CA, USA, August 23-27, 2020. ACM 2020, ISBN 978-1-4503-7998-4
Keynote & Invited Talks
- Manuela Veloso:
AI for Intelligent Financial Services: Examples and Discussion. 1-2 - Emery N. Brown:
Keynote Speaker: Emery N. Brown. 3 - Yolanda Gil:
Keynote Speaker: Yolanda Gil. 4 - Alessandro Vespignani:
Keynote Speaker: Alessandro Vespignani. 5
Research Track Papers
- Ning Wu, Wayne Xin Zhao, Jingyuan Wang, Dayan Pan:
Learning Effective Road Network Representation with Hierarchical Graph Neural Networks. 6-14 - Jingyuan Wang, Yufan Wu, Mingxuan Li, Xin Lin, Junjie Wu, Chao Li:
Interpretability is a Kind of Safety: An Interpreter-based Ensemble for Adversary Defense. 15-24 - Aldo G. Carranza, Ryan A. Rossi, Anup Rao, Eunyee Koh:
Higher-order Clustering in Complex Heterogeneous Networks. 25-35 - Haoxing Lin, Rufan Bai, Weijia Jia, Xinyu Yang, Yongjian You:
Preserving Dynamic Attention for Long-Term Spatial-Temporal Prediction. 36-46 - Qifan Wang, Li Yang, Bhargav Kanagal, Sumit Sanghai, D. Sivakumar, Bin Shu, Zac Yu
, Jon Elsas:
Learning to Extract Attribute Value from Product via Question Answering: A Multi-task Approach. 47-55 - Liangyu Zhu, Wenbin Lu, Michael R. Kosorok, Rui Song:
Kernel Assisted Learning for Personalized Dose Finding. 56-65 - Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang:
Graph Structure Learning for Robust Graph Neural Networks. 66-74 - Jiarui Jin, Jiarui Qin, Yuchen Fang, Kounianhua Du, Weinan Zhang, Yong Yu, Zheng Zhang, Alexander J. Smola:
An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph. 75-84 - Nan Wang, Hongning Wang:
Directional Multivariate Ranking. 85-94 - Yue Wang, Ke Wang, Chunyan Miao:
Truth Discovery against Strategic Sybil Attack in Crowdsourcing. 95-104 - Gengyu Lyu, Songhe Feng, Yidong Li:
Partial Multi-Label Learning via Probabilistic Graph Matching Mechanism. 105-113 - Zhe Liu, Lina Yao, Lei Bai, Xianzhi Wang, Can Wang:
Spectrum-Guided Adversarial Disparity Learning. 114-124 - Yong He, Cheng Wang, Nan Li, Zhenyu Zeng:
Attention and Memory-Augmented Networks for Dual-View Sequential Learning. 125-134 - Lukas Pfahler, Katharina Morik:
Semantic Search in Millions of Equations. 135-143 - Kyuhan Lee, Hyeonsoo Jo, Jihoon Ko, Sungsu Lim, Kijung Shin:
SSumM: Sparse Summarization of Massive Graphs. 144-154 - Dawei Gao, Xiaoxi He, Zimu Zhou, Yongxin Tong, Ke Xu, Lothar Thiele:
Rethinking Pruning for Accelerating Deep Inference At the Edge. 155-164 - Hao-Jun Michael Shi, Dheevatsa Mudigere, Maxim Naumov, Jiyan Yang:
Compositional Embeddings Using Complementary Partitions for Memory-Efficient Recommendation Systems. 165-175 - Manh Tuan Do, Se-eun Yoon, Bryan Hooi, Kijung Shin:
Structural Patterns and Generative Models of Real-world Hypergraphs. 176-186 - Yasuhiro Fujiwara, Atsutoshi Kumagai, Sekitoshi Kanai, Yasutoshi Ida, Naonori Ueda:
Efficient Algorithm for the b-Matching Graph. 187-197 - Kai Ming Ting, Bi-Cun Xu, Takashi Washio, Zhi-Hua Zhou:
Isolation Distributional Kernel: A New Tool for Kernel based Anomaly Detection. 198-206 - Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, Juncheng Liu, Bryan Hooi:
NodeAug: Semi-Supervised Node Classification with Data Augmentation. 207-217 - Ruixiang Tang, Mengnan Du, Ninghao Liu, Fan Yang, Xia Hu:
An Embarrassingly Simple Approach for Trojan Attack in Deep Neural Networks. 218-228 - Hongyang Gao, Zhengyang Wang, Shuiwang Ji:
Kronecker Attention Networks. 229-237 - Thai Le, Suhang Wang, Dongwon Lee:
GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model's Prediction. 238-248 - Muhan Zhang, Christopher Ryan King, Michael Avidan, Yixin Chen:
Hierarchical Attention Propagation for Healthcare Representation Learning. 249-256 - Shengzhong Zhang, Zengfeng Huang, Haicang Zhou, Ziang Zhou:
SCE: Scalable Network Embedding from Sparsest Cut. 257-265 - Dongsheng Luo, Yuchen Bian, Yaowei Yan, Xiao Liu, Jun Huan, Xiang Zhang:
Local Community Detection in Multiple Networks. 266-274 - Ganzhao Yuan, Li Shen, Wei-Shi Zheng:
A Block Decomposition Algorithm for Sparse Optimization. 275-285 - Jian Liang, Bing Bai, Yuren Cao, Kun Bai, Fei Wang:
Adversarial Infidelity Learning for Model Interpretation. 286-296 - Zhihui Li, Xiaojun Chang, Lina Yao, Shirui Pan, Zongyuan Ge, Huaxiang Zhang:
Grounding Visual Concepts for Zero-Shot Event Detection and Event Captioning. 297-305 - Suman K. Bera, C. Seshadhri:
How to Count Triangles, without Seeing the Whole Graph. 306-316 - Jihoon Ko, Yunbum Kook, Kijung Shin:
Incremental Lossless Graph Summarization. 317-327 - Yufei Tao, Shangqi Lu:
From Online to Non-i.i.d. Batch Learning. 328-337 - Meng Liu, Hongyang Gao, Shuiwang Ji:
Towards Deeper Graph Neural Networks. 338-348 - Shenyang Huang, Yasmeen Hitti, Guillaume Rabusseau, Reihaneh Rabbany:
Laplacian Change Point Detection for Dynamic Graphs. 349-358 - Jianwen Yin, Chenghao Liu, Weiqing Wang, Jianling Sun, Steven C. H. Hoi:
Learning Transferrable Parameters for Long-tailed Sequential User Behavior Modeling. 359-367 - Kuo Zhong, Ying Wei, Chun Yuan, Haoli Bai, Junzhou Huang:
TranSlider: Transfer Ensemble Learning from Exploitation to Exploration. 368-378 - Jian Kang, Jingrui He, Ross Maciejewski, Hanghang Tong:
InFoRM: Individual Fairness on Graph Mining. 379-389 - Dongqi Fu, Dawei Zhou, Jingrui He:
Local Motif Clustering on Time-Evolving Graphs. 390-400 - Dawei Zhou, Lecheng Zheng, Jiawei Han, Jingrui He:
A Data-Driven Graph Generative Model for Temporal Interaction Networks. 401-411 - Xin Dai, Xiangnan Kong, Tian Guo, John Boaz Lee, Xinyue Liu, Constance M. Moore:
Recurrent Networks for Guided Multi-Attention Classification. 412-420 - Chao Li, Haoteng Tang, Cheng Deng, Liang Zhan, Wei Liu:
Vulnerability vs. Reliability: Disentangled Adversarial Examples for Cross-Modal Learning. 421-429 - Hao Yuan, Jiliang Tang, Xia Hu, Shuiwang Ji:
XGNN: Towards Model-Level Explanations of Graph Neural Networks. 430-438 - Xiang Li, Ben Kao, Caihua Shan, Dawei Yin, Martin Ester:
CAST: A Correlation-based Adaptive Spectral Clustering Algorithm on Multi-scale Data. 439-449 - Xianli Zhang, Buyue Qian, Shilei Cao, Yang Li, Hang Chen, Yefeng Zheng, Ian Davidson:
INPREM: An Interpretable and Trustworthy Predictive Model for Healthcare. 450-460 - Kwei-Herng Lai, Daochen Zha, Kaixiong Zhou, Xia Hu:
Policy-GNN: Aggregation Optimization for Graph Neural Networks. 461-471 - Mengdi Huai, Jianhui Sun, Renqin Cai, Liuyi Yao, Aidong Zhang:
Malicious Attacks against Deep Reinforcement Learning Interpretations. 472-482 - Jianxin Ma, Chang Zhou, Hongxia Yang, Peng Cui, Xin Wang, Wenwu Zhu:
Disentangled Self-Supervision in Sequential Recommenders. 483-491 - Limeng Cui, Haeseung Seo, Maryam Tabar, Fenglong Ma, Suhang Wang, Dongwon Lee:
DETERRENT: Knowledge Guided Graph Attention Network for Detecting Healthcare Misinformation. 492-502 - Namyong Park, Andrey Kan, Xin Luna Dong, Tong Zhao, Christos Faloutsos:
MultiImport: Inferring Node Importance in a Knowledge Graph from Multiple Input Signals. 503-512 - Meghana Madhyastha, Gongkai Li, Veronika Strnadová-Neeley, James Browne, Joshua T. Vogelstein, Randal C. Burns, Carey E. Priebe:
Geodesic Forests. 513-523 - Zed Lee, Tony Lindgren, Panagiotis Papapetrou:
Z-Miner: An Efficient Method for Mining Frequent Arrangements of Event Intervals. 524-534 - Shaoxu Song, Yu Sun:
Imputing Various Incomplete Attributes via Distance Likelihood Maximization. 535-545 - Syeda Nahida Akter, Muhammad Abdullah Adnan:
WeightGrad: Geo-Distributed Data Analysis Using Quantization for Faster Convergence and Better Accuracy. 546-556 - Jing-Han Wu, Xuan Wu, Qing-Guo Chen, Yao Hu, Min-Ling Zhang:
Feature-Induced Manifold Disambiguation for Multi-View Partial Multi-label Learning. 557-565 - Haoyu Zhang, Qin Zhang:
MinSearch: An Efficient Algorithm for Similarity Search under Edit Distance. 566-576 - Aritra Konar, Nicholas D. Sidiropoulos:
Mining Large Quasi-cliques with Quality Guarantees from Vertex Neighborhoods. 577-587 - Junteng Jia, Austin R. Benson:
Residual Correlation in Graph Neural Network Regression. 588-598 - Yanying Li, Haipei Sun, Wendy Hui Wang:
Towards Fair Truth Discovery from Biased Crowdsourced Answers. 599-607 - Jiancheng Lyu, Shuai Zhang, Yingyong Qi, Jack Xin:
AutoShuffleNet: Learning Permutation Matrices via an Exact Lipschitz Continuous Penalty in Deep Convolutional Neural Networks. 608-616 - Chengxi Zang, Fei Wang:
MoFlow: An Invertible Flow Model for Generating Molecular Graphs. 617-626 - Yipeng Zhang, Bo Du, Lefei Zhang, Jia Wu:
Parallel DNN Inference Framework Leveraging a Compact RISC-V ISA-based Multi-core System. 627-635 - Yuxuan Zhao, Madeleine Udell:
Missing Value Imputation for Mixed Data via Gaussian Copula. 636-646 - Junyu Luo, Muchao Ye, Cao Xiao, Fenglong Ma:
HiTANet: Hierarchical Time-Aware Attention Networks for Risk Prediction on Electronic Health Records. 647-656 - Hanzhi Wang, Zhewei Wei, Junhao Gan, Sibo Wang, Zengfeng Huang:
Personalized PageRank to a Target Node, Revisited. 657-667 - Kenta Niwa, Noboru Harada, Guoqiang Zhang, W. Bastiaan Kleijn:
Edge-consensus Learning: Deep Learning on P2P Networks with Nonhomogeneous Data. 668-678 - Yi Liu, Hao Yuan, Lei Cai, Shuiwang Ji:
Deep Learning of High-Order Interactions for Protein Interface Prediction. 679-687 - Manqing Dong, Feng Yuan, Lina Yao, Xiwei Xu, Liming Zhu:
MAMO: Memory-Augmented Meta-Optimization for Cold-start Recommendation. 688-697 - Lu Chen, Chengfei Liu, Rui Zhou, Jiajie Xu, Jeffrey Xu Yu, Jianxin Li:
Finding Effective Geo-social Group for Impromptu Activities with Diverse Demands. 698-708 - Yinan Mei, Shaoxu Song, Yunsu Lee, Jungho Park, Soo-Hyung Kim, Sungmin Yi:
Representing Temporal Attributes for Schema Matching. 709-719 - Kazuki Nakajima, Kazuyuki Shudo:
Estimating Properties of Social Networks via Random Walk considering Private Nodes. 720-730 - Zhongkai Hao, Chengqiang Lu, Zhenya Huang, Hao Wang, Zheyuan Hu, Qi Liu, Enhong Chen, Cheekong Lee:
ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction. 731-752 - Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Xiaojun Chang, Chengqi Zhang:
Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks. 753-763 - Corrado Monti, Gianmarco De Francisci Morales, Francesco Bonchi:
Learning Opinion Dynamics From Social Traces. 764-773 - Le Dai, Yu Yin, Chuan Qin, Tong Xu, Xiangnan He, Enhong Chen, Hui Xiong:
Enterprise Cooperation and Competition Analysis with a Sign-Oriented Preference Network. 774-782 - Otmane Sakhi, Stephen Bonner, David Rohde, Flavian Vasile:
BLOB: A Probabilistic Model for Recommendation that Combines Organic and Bandit Signals. 783-793 - Ting Li, Junbo Zhang, Kainan Bao, Yuxuan Liang, Yexin Li, Yu Zheng:
AutoST: Efficient Neural Architecture Search for Spatio-Temporal Prediction. 794-802 - Junyi Gao, Cao Xiao, Lucas M. Glass, Jimeng Sun:
COMPOSE: Cross-Modal Pseudo-Siamese Network for Patient Trial Matching. 803-812 - Jonas Fischer, Jilles Vreeken:
Discovering Succinct Pattern Sets Expressing Co-Occurrence and Mutual Exclusivity. 813-823 - Ang Li, Yixiao Duan, Huanrui Yang, Yiran Chen, Jianlei Yang:
TIPRDC: Task-Independent Privacy-Respecting Data Crowdsourcing Framework for Deep Learning with Anonymized Intermediate Representations. 824-832 - Wei Wen, Feng Yan, Yiran Chen, Hai Li:
AutoGrow: Automatic Layer Growing in Deep Convolutional Networks. 833-841 - Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, Jun Luo:
Curb-GAN: Conditional Urban Traffic Estimation through Spatio-Temporal Generative Adversarial Networks. 842-852 - Pengyang Wang, Kunpeng Liu, Lu Jiang, Xiaolin Li, Yanjie Fu:
Incremental Mobile User Profiling: Reinforcement Learning with Spatial Knowledge Graph for Modeling Event Streams. 853-861 - Changchang Yin, Ruoqi Liu, Dongdong Zhang, Ping Zhang:
Identifying Sepsis Subphenotypes via Time-Aware Multi-Modal Auto-Encoder. 862-872 - Elias Chaibub Neto:
A Causal Look at Statistical Definitions of Discrimination. 873-881 - Mohammad Mahdi Kamani, Sadegh Farhang, Mehrdad Mahdavi, James Z. Wang:
Targeted Data-driven Regularization for Out-of-Distribution Generalization. 882-891 - Chengxi Zang, Fei Wang:
Neural Dynamics on Complex Networks. 892-902 - Guangrun Wang, Guangcong Wang, Keze Wang, Xiaodan Liang, Liang Lin:
Grammatically Recognizing Images with Tree Convolution. 903-912 - Yikun Ban, Jingrui He:
Generic Outlier Detection in Multi-Armed Bandit. 913-923 - Yingtong Dou, Guixiang Ma, Philip S. Yu, Sihong Xie:
Robust Spammer Detection by Nash Reinforcement Learning. 924-933 - Caleb Belth, Xinyi Zheng, Danai Koutra:
Mining Persistent Activity in Continually Evolving Networks. 934-944 - Qingquan Song, Dehua Cheng, Hanning Zhou, Jiyan Yang, Yuandong Tian, Xia Hu:
Towards Automated Neural Interaction Discovery for Click-Through Rate Prediction. 945-955 - Nicholas Gao, Max Wilson, Thomas Vandal, Walter Vinci, Ramakrishna R. Nemani, Eleanor Gilbert Rieffel:
High-Dimensional Similarity Search with Quantum-Assisted Variational Autoencoder. 956-964 - Noveen Sachdeva, Yi Su, Thorsten Joachims:
Off-policy Bandits with Deficient Support. 965-975 - Ganqu Cui, Jie Zhou, Cheng Yang, Zhiyuan Liu:
Adaptive Graph Encoder for Attributed Graph Embedding. 976-985 - Si Zhang, Hanghang Tong, Yinglong Xia, Liang Xiong, Jiejun Xu:
NetTrans: Neural Cross-Network Transformation. 986-996 - Zhihao Jia, Sina Lin, Rex Ying, Jiaxuan You, Jure Leskovec, Alex Aiken:
Redundancy-Free Computation for Graph Neural Networks. 997-1005 - Kun Zhou, Wayne Xin Zhao, Shuqing Bian, Yuanhang Zhou, Ji-Rong Wen, Jingsong Yu:
Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion. 1006-1014 - Xiangyang Gou, Long He, Yinda Zhang, Ke Wang, Xilai Liu, Tong Yang, Yi Wang, Bin Cui:
Sliding Sketches: A Framework using Time Zones for Data Stream Processing in Sliding Windows. 1015-1025 - Yue Yu, Yinghao Li, Jiaming Shen, Hao Feng, Jimeng Sun, Chao Zhang:
STEAM: Self-Supervised Taxonomy Expansion with Mini-Paths. 1026-1035 - Chen Ma, Liheng Ma, Yingxue Zhang, Ruiming Tang, Xue Liu, Mark Coates:
Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation. 1036-1044 - Du Su, Hieu Tri Huynh, Ziao Chen, Yi Lu, Wenmiao Lu:
Re-identification Attack to Privacy-Preserving Data Analysis with Noisy Sample-Mean. 1045-1053 - Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, Tuo Zhao, Chao Zhang:
BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision. 1054-1064 - Qingqing Long, Yilun Jin, Guojie Song, Yi Li, Wei Lin:
Graph Structural-topic Neural Network. 1065-1073 - Guangxu Xun, Kishlay Jha, Jianhui Sun, Aidong Zhang:
Correlation Networks for Extreme Multi-label Text Classification. 1074-1082 - Le Yu, Leilei Sun, Bowen Du, Chuanren Liu, Hui Xiong, Weifeng Lv:
Predicting Temporal Sets with Deep Neural Networks. 1083-1091 - Bill Yuchen Lin, Ying Sheng, Nguyen Vo, Sandeep Tata:
FreeDOM: A Transferable Neural Architecture for Structured Information Extraction on Web Documents. 1092-1102 - Yao Zhang, Yun Xiong, Yun Ye, Tengfei Liu, Weiqiang Wang, Yangyong Zhu, Philip S. Yu:
SEAL: Learning Heuristics for Community Detection with Generative Adversarial Networks. 1103-1113 - Makoto Imamura, Takaaki Nakamura, Eamonn J. Keogh:
Matrix Profile XXI: A Geometric Approach to Time Series Chains Improves Robustness. 1114-1122 - Surgan Jandial, Ayush Chopra, Mausoom Sarkar, Piyush Gupta, Balaji Krishnamurthy, Vineeth Balasubramanian:
Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks. 1123-1131 - Pan Peng, Yuichi Yoshida:
Average Sensitivity of Spectral Clustering. 1132-1140 - Wanli Shi, Victor S. Sheng, Xiang Li, Bin Gu:
Semi-Supervised Multi-Label Learning from Crowds via Deep Sequential Generative Model. 1141-1149 - Jiezhong Qiu, Qibin Chen, Yuxiao Dong, Jing Zhang, Hongxia Yang, Ming Ding, Kuansan Wang, Jie Tang:
GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training. 1150-1160 - Zhihua Zhu, Xinxin Fan, Xiaokai Chu, Jingping Bi:
HGCN: A Heterogeneous Graph Convolutional Network-Based Deep Learning Model Toward Collective Classification. 1161-1171 - Tianwen Chen, Raymond Chi-Wing Wong:
Handling Information Loss of Graph Neural Networks for Session-based Recommendation. 1172-1180 - Susik Yoon, Jae-Gil Lee, Byung Suk Lee:
Ultrafast Local Outlier Detection from a Data Stream with Stationary Region Skipping. 1181-1191 - Yiheng Xu, Minghao Li, Lei Cui, Shaohan Huang, Furu Wei, Ming Zhou:
LayoutLM: Pre-training of Text and Layout for Document Image Understanding. 1192-1200 - Zilong Bai, Hoa Nguyen, Ian Davidson:
Block Model Guided Unsupervised Feature Selection. 1201-1211 - Claudia Plant, Sonja Biedermann, Christian Böhm:
Data Compression as a Comprehensive Framework for Graph Drawing and Representation Learning. 1212-1222 - Olivier Jeunen, David Rohde, Flavian Vasile, Martin Bompaire:
Joint Policy-Value Learning for Recommendation. 1223-1233 - Khalil Muhammad, Qinqin Wang, Diarmuid O'Reilly-Morgan, Elias Z. Tragos, Barry Smyth, Neil Hurley, James Geraci, Aonghus Lawlor:
FedFast: Going Beyond Average for Faster Training of Federated Recommender Systems. 1234-1242 - Xiao Wang, Meiqi Zhu, Deyu Bo, Peng Cui, Chuan Shi, Jian Pei:
AM-GCN: Adaptive Multi-channel Graph Convolutional Networks. 1243-1253 - Frédéric Pennerath, Panagiotis Mandros, Jilles Vreeken:
Discovering Approximate Functional Dependencies using Smoothed Mutual Information. 1254-1264 - Shuangli Li, Jingbo Zhou, Tong Xu, Hao Liu, Xinjiang Lu, Hui Xiong:
Competitive Analysis for Points of Interest. 1265-1274 - Pascal Welke, Florian Seiffarth, Michael Kamp, Stefan Wrobel:
HOPS: Probabilistic Subtree Mining for Small and Large Graphs. 1275-1284 - Anton Zhernov, Krishnamurthy (Dj) Dvijotham, Ivan Lobov, Dan A. Calian, Michelle X. Gong, Natarajan Chandrashekar, Timothy A. Mann:
The NodeHopper: Enabling Low Latency Ranking with Constraints via a Fast Dual Solver. 1285-1294 - Jiayi Chen, Aidong Zhang:
HGMF: Heterogeneous Graph-based Fusion for Multimodal Data with Incompleteness. 1295-1305 - Huimin Ren, Menghai Pan, Yanhua Li, Xun Zhou, Jun Luo:
ST-SiameseNet: Spatio-Temporal Siamese Networks for Human Mobility Signature Identification. 1306-1315 - Tianyu Kang, Ping Chen, John Quackenbush, Wei Ding:
A Novel Deep Learning Model by Stacking Conditional Restricted Boltzmann Machine and Deep Neural Network. 1316-1324 - Sudhanshu Chanpuriya, Cameron Musco:
InfiniteWalk: Deep Network Embeddings as Laplacian Embeddings with a Nonlinearity. 1325-1333 - Menghai Pan, Weixiao Huang, Yanhua Li, Xun Zhou, Jun Luo:
xGAIL: Explainable Generative Adversarial Imitation Learning for Explainable Human Decision Analysis. 1334-1343 - Olga Andreeva, Wei Li, Wei Ding, Marieke L. Kuijjer, John Quackenbush, Ping Chen:
Catalysis Clustering with GAN by Incorporating Domain Knowledge. 1344-1352 - Peng Zhang, Chuanren Liu, Kefeng Ning, Wenxiang Zhu, Yu Zhang:
Prediction and Profiling of Audience Competition for Online Television Series. 1353-1361 - Dongha Lee, Sehun Yu, Hwanjo Yu:
Multi-Class Data Description for Out-of-distribution Detection. 1362-1370 - Domenico Mandaglio, Andrea Tagarelli, Francesco Gullo:
In and Out: Optimizing Overall Interaction in Probabilistic Graphs under Clustering Constraints. 1371-1381 - Thomas Hartvigsen, Cansu Sen, Xiangnan Kong, Elke A. Rundensteiner:
Recurrent Halting Chain for Early Multi-label Classification. 1382-1392 - Weilin Cong, Rana Forsati, Mahmut T. Kandemir, Mehrdad Mahdavi:
Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks. 1393-1403 - Panagiotis Mandros, David Kaltenpoth, Mario Boley, Jilles Vreeken:
Discovering Functional Dependencies from Mixed-Type Data. 1404-1414 - Yutong Wang, Yufei Han, Hongyan Bao, Yun Shen, Fenglong Ma, Jin Li, Xiangliang Zhang:
Attackability Characterization of Adversarial Evasion Attack on Discrete Data. 1415-1425 - Shengmin Jin, Reza Zafarani:
The Spectral Zoo of Networks: Embedding and Visualizing Networks with Spectral Moments. 1426-1434 - Chanyoung Park, Carl Yang, Qi Zhu, Donghyun Kim, Hwanjo Yu, Jiawei Han:
Unsupervised Differentiable Multi-aspect Network Embedding. 1435-1445 - Chengrun Yang, Jicong Fan, Ziyang Wu, Madeleine Udell:
AutoML Pipeline Selection: Efficiently Navigating the Combinatorial Space. 1446-1456 - Rui Wang, Karthik Kashinath, Mustafa Mustafa, Adrian Albert, Rose Yu:
Towards Physics-informed Deep Learning for Turbulent Flow Prediction. 1457-1466 - Cyrus DiCiccio, Sriram Vasudevan, Kinjal Basu, Krishnaram Kenthapadi, Deepak Agarwal:
Evaluating Fairness Using Permutation Tests. 1467-1477 - Johannes Haug, Martin Pawelczyk, Klaus Broelemann, Gjergji Kasneci:
Leveraging Model Inherent Variable Importance for Stable Online Feature Selection. 1478-1502 - Hongxu Chen, Hongzhi Yin, Xiangguo Sun, Tong Chen, Bogdan Gabrys, Katarzyna Musial:
Multi-level Graph Convolutional Networks for Cross-platform Anchor Link Prediction. 1503-1511 - Shuo Zhang, Krisztian Balog:
Evaluating Conversational Recommender Systems via User Simulation. 1512-1520 - Xia Hu, Weiqing Liu, Jiang Bian, Jian Pei:
Measuring Model Complexity of Neural Networks with Curve Activation Functions. 1521-1531 - Guangyi Zhang, Aristides Gionis:
Diverse Rule Sets. 1532-1541 - Mohammad Hossein Namaki, Avrilia Floratou, Fotis Psallidas, Subru Krishnan, Ashvin Agrawal, Yinghui Wu, Yiwen Zhu, Markus Weimer:
Vamsa: Automated Provenance Tracking in Data Science Scripts. 1542-1551 - Yuan Xue, Denny Zhou, Nan Du, Andrew M. Dai, Zhen Xu, Kun Zhang, Claire Cui:
Deep State-Space Generative Model For Correlated Time-to-Event Predictions. 1552-1562 - Yuanfu Lu, Yuan Fang, Chuan Shi:
Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation. 1563-1573 - Jizhou Li, Zikun Li, Yifei Xu, Shiqi Jiang, Tong Yang, Bin Cui, Yafei Dai, Gong Zhang:
WavingSketch: An Unbiased and Generic Sketch for Finding Top-k Items in Data Streams. 1574-1584 - Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Dynamic Knowledge Graph based Multi-Event Forecasting. 1585-1595 - Brian J. Goode, Debanjan Datta:
A Geometric Approach to Predicting Bounds of Downstream Model Performance. 1596-1604 - Zhenxin Fu, Shaobo Cui, Mingyue Shang, Feng Ji, Dongyan Zhao, Haiqing Chen, Rui Yan:
Context-to-Session Matching: Utilizing Whole Session for Response Selection in Information-Seeking Dialogue Systems. 1605-1613 - Shenda Hong, Yanbo Xu, Alind Khare, Satria Priambada, Kevin O. Maher, Alaa Aljiffry, Jimeng Sun, Alexey Tumanov:
HOLMES: Health OnLine Model Ensemble Serving for Deep Learning Models in Intensive Care Units. 1614-1624 - Kejing Yin, Ardavan Afshar, Joyce C. Ho, William K. Cheung, Chao Zhang, Jimeng Sun:
LogPar: Logistic PARAFAC2 Factorization for Temporal Binary Data with Missing Values. 1625-1635 - Lan-Zhe Guo, Zhi Zhou, Yufeng Li:
RECORD: Resource Constrained Semi-Supervised Learning under Distribution Shift. 1636-1644 - Thien Q. Tran, Kazuto Fukuchi, Youhei Akimoto, Jun Sakuma:
Statistically Significant Pattern Mining with Ordinal Utility. 1645-1655 - Daniel Zügner, Stephan Günnemann:
Certifiable Robustness of Graph Convolutional Networks under Structure Perturbations. 1656-1665 - Zhen Yang, Ming Ding, Chang Zhou, Hongxia Yang, Jingren Zhou, Jie Tang:
Understanding Negative Sampling in Graph Representation Learning. 1666-1676 - Reid McIlroy-Young, Siddhartha Sen, Jon M. Kleinberg, Ashton Anderson:
Aligning Superhuman AI with Human Behavior: Chess as a Model System. 1677-1687 - Mehrdad Mansouri, Ali Arab, Zahra Zohrevand, Martin Ester:
Heidegger: Interpretable Temporal Causal Discovery. 1688-1696 - Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, Yanfang Ye:
Interpretable Deep Graph Generation with Node-edge Co-disentanglement. 1697-1707 - Nate Veldt, Austin R. Benson, Jon M. Kleinberg:
Minimizing Localized Ratio Cut Objectives in Hypergraphs. 1708-1718 - Diya Li, Mohammed J. Zaki:
RECIPTOR: An Effective Pretrained Model for Recipe Representation Learning. 1719-1727 - Puoya Tabaghi, Ivan Dokmanic:
Hyperbolic Distance Matrices. 1728-1738 - Jinghui Chen, Quanquan Gu:
RayS: A Ray Searching Method for Hard-label Adversarial Attack. 1739-1747 - Walid Krichene, Steffen Rendle:
On Sampled Metrics for Item Recommendation. 1748-1757 - Gordon Euhyun Moon, J. Austin Ellis, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan:
ALO-NMF: Accelerated Locality-Optimized Non-negative Matrix Factorization. 1758-1767 - Garrett Wilson, Janardhan Rao Doppa, Diane J. Cook:
Multi-Source Deep Domain Adaptation with Weak Supervision for Time-Series Sensor Data. 1768-1778 - James McInerney, Brian Brost, Praveen Chandar, Rishabh Mehrotra, Benjamin A. Carterette:
Counterfactual Evaluation of Slate Recommendations with Sequential Reward Interactions. 1779-1788 - Qiuling Suo, Jingyuan Chou, Weida Zhong, Aidong Zhang:
TAdaNet: Task-Adaptive Network for Graph-Enriched Meta-Learning. 1789-1799 - A. B. Siddique, Samet Oymak, Vagelis Hristidis:
Unsupervised Paraphrasing via Deep Reinforcement Learning. 1800-1809 - Tomas Martin, Guy Francoeur, Petko Valtchev:
CICLAD: A Fast and Memory-efficient Closed Itemset Miner for Streams. 1810-1818 - Lu Lin, Hongning Wang:
Graph Attention Networks over Edge Content-Based Channels. 1819-1827 - Qi Wang, Liang Zhan, Paul M. Thompson, Jiayu Zhou:
Multimodal Learning with Incomplete Modalities by Knowledge Distillation. 1828-1838 - Alane M. de Lima, Murilo V. G. da Silva, André Luís Vignatti:
Estimating the Percolation Centrality of Large Networks through Pseudo-dimension Theory. 1839-1847 - Bencheng Yan, Chaokun Wang, Gaoyang Guo, Yunkai Lou:
TinyGNN: Learning Efficient Graph Neural Networks. 1848-1856 - Ziniu Hu, Yuxiao Dong, Kuansan Wang, Kai-Wei Chang, Yizhou Sun:
GPT-GNN: Generative Pre-Training of Graph Neural Networks. 1857-1867 - Nate Veldt, Anthony Wirth, David F. Gleich:
Parameterized Correlation Clustering in Hypergraphs and Bipartite Graphs. 1868-1876 - Amel Awadelkarim, Johan Ugander:
Prioritized Restreaming Algorithms for Balanced Graph Partitioning. 1877-1887 - Yuantong Li, Qi Ma, Sujit K. Ghosh:
A Non-Iterative Quantile Change Detection Method in Mixture Model with Heavy-Tailed Components. 1888-1898 - Ren Pang, Xinyang Zhang, Shouling Ji, Xiapu Luo, Ting Wang:
AdvMind: Inferring Adversary Intent of Black-Box Attacks. 1899-1907 - Yu Meng, Yunyi Zhang, Jiaxin Huang, Yu Zhang, Chao Zhang, Jiawei Han:
Hierarchical Topic Mining via Joint Spherical Tree and Text Embedding. 1908-1917 - Hamid Dadkhahi, Karthikeyan Shanmugam, Jesus Rios, Payel Das, Samuel C. Hoffman, Troy David Loeffler, Subramanian Sankaranarayanan:
Combinatorial Black-Box Optimization with Expert Advice. 1918-1927 - Jiaxin Huang, Yiqing Xie, Yu Meng, Yunyi Zhang, Jiawei Han:
CoRel: Seed-Guided Topical Taxonomy Construction by Concept Learning and Relation Transferring. 1928-1936 - Soorajnath Boominathan, Michael Oberst, Helen Zhou, Sanjat Kanjilal, David A. Sontag:
Treatment Policy Learning in Multiobjective Settings with Fully Observed Outcomes. 1937-1947 - Jin Shang, Mingxuan Sun, Nina Siu-Ngan Lam:
List-wise Fairness Criterion for Point Processes. 1948-1958 - Xin Liu, Haojie Pan, Mutian He, Yangqiu Song, Xin Jiang, Lifeng Shang:
Neural Subgraph Isomorphism Counting. 1959-1969 - Yuuki Takai, Atsushi Miyauchi, Masahiro Ikeda, Yuichi Yoshida:
Hypergraph Clustering Based on PageRank. 1970-1978 - Yi Ren, Xu Tan, Tao Qin, Jian Luan, Zhou Zhao, Tie-Yan Liu:
DeepSinger: Singing Voice Synthesis with Data Mined From the Web. 1979-1989 - Jan Overgoor, George Pakapol Supaniratisai, Johan Ugander:
Scaling Choice Models of Relational Social Data. 1990-1998 - Subhabrata Dutta, Sarah Masud, Soumen Chakrabarti, Tanmoy Chakraborty:
Deep Exogenous and Endogenous Influence Combination for Social Chatter Intensity Prediction. 1999-2008 - Defu Lian, Yongji Wu, Yong Ge, Xing Xie, Enhong Chen:
Geography-Aware Sequential Location Recommendation. 2009-2019 - Shuyi Ji, Yifan Feng, Rongrong Ji, Xibin Zhao, Wanwan Tang, Yue Gao:
Dual Channel Hypergraph Collaborative Filtering. 2020-2029 - Jianing Sun, Wei Guo, Dengcheng Zhang, Yingxue Zhang, Florence Regol, Yaochen Hu, Huifeng Guo, Ruiming Tang, Han Yuan, Xiuqiang He, Mark Coates:
A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks. 2030-2039 - Hao Wu, Junhao Gan, Rui Zhang:
Learning Based Distributed Tracking. 2040-2050 - Alaa Maalouf, Adiel Statman, Dan Feldman:
Tight Sensitivity Bounds For Smaller Coresets. 2051-2061 - Zongyue Qin, Yunsheng Bai, Yizhou Sun:
GHashing: Semantic Graph Hashing for Approximate Similarity Search in Graph Databases. 2062-2072 - Wenqiang Lei, Gangyi Zhang, Xiangnan He, Yisong Miao, Xiang Wang, Liang Chen, Tat-Seng Chua:
Interactive Path Reasoning on Graph for Conversational Recommendation. 2073-2083 - Sebastian Buß, Hendrik Molter, Rolf Niedermeier, Maciej Rymar:
Algorithmic Aspects of Temporal Betweenness. 2084-2092 - Koki Kawabata, Yasuko Matsubara, Takato Honda, Yasushi Sakurai:
Non-Linear Mining of Social Activities in Tensor Streams. 2093-2102 - Yuval Heffetz, Roman Vainshtein, Gilad Katz, Lior Rokach:
DeepLine: AutoML Tool for Pipelines Generation using Deep Reinforcement Learning and Hierarchical Actions Filtering. 2103-2113 - Dong Li, Ruoming Jin, Jing Gao, Zhi Liu:
On Sampling Top-K Recommendation Evaluation. 2114-2124 - Renzhe Xu, Peng Cui, Kun Kuang, Bo Li, Linjun Zhou, Zheyan Shen, Wei Cui:
Algorithmic Decision Making with Conditional Fairness. 2125-2135 - Wenhui Yu, Xiao Lin, Junfeng Ge, Wenwu Ou, Zheng Qin:
Semi-supervised Collaborative Filtering by Text-enhanced Domain Adaptation. 2136-2144 - Yuichiro Ueno, Kazuki Osawa, Yohei Tsuji, Akira Naruse, Rio Yokota:
Rich Information is Affordable: A Systematic Performance Analysis of Second-order Optimization Using K-FAC. 2145-2153 - Vladislav Polianskii, Florian T. Pokorny:
Voronoi Graph Traversal in High Dimensions with Applications to Topological Data Analysis and Piecewise Linear Interpolation. 2154-2164 - Leonardo Pellegrina, Cyrus Cousins, Fabio Vandin, Matteo Riondato:
MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining. 2165-2174 - Shichao Pei, Lu Yu, Guoxian Yu, Xiangliang Zhang:
REA: Robust Cross-lingual Entity Alignment Between Knowledge Graphs. 2175-2184 - Zheyan Shen, Peng Cui, Jiashuo Liu, Tong Zhang, Bo Li, Zhitang Chen:
Stable Learning via Differentiated Variable Decorrelation. 2185-2193 - Yue He, Peng Cui, Jianxin Ma, Hao Zou, Xiaowei Wang, Hongxia Yang, Philip S. Yu:
Learning Stable Graphs from Multiple Environments with Selection Bias. 2194-2202 - Qingsong Wen, Zhe Zhang, Yan Li, Liang Sun:
Fast RobustSTL: Efficient and Robust Seasonal-Trend Decomposition for Time Series with Complex Patterns. 2203-2213 - Wenchong He, Zhe Jiang, Chengming Zhang, Arpan Man Sainju:
CurvaNet: Geometric Deep Learning based on Directional Curvature for 3D Shape Analysis. 2214-2224 - Fengli Xu, Yong Li, Shusheng Xu:
Attentional Multi-graph Convolutional Network for Regional Economy Prediction with Open Migration Data. 2225-2233
Applied Data Science Track Papers
- Yuning Mao, Tong Zhao, Andrey Kan, Chenwei Zhang, Xin Luna Dong, Christos Faloutsos, Jiawei Han:
Octet: Online Catalog Taxonomy Enrichment with Self-Supervision. 2247-2257 - Zhiping Xiao, Weiping Song, Haoyan Xu, Zhicheng Ren, Yizhou Sun:
TIMME: Twitter Ideology-detection via Multi-task Multi-relational Embedding. 2258-2268 - Xianfeng Tang, Yozen Liu, Neil Shah, Xiaolin Shi, Prasenjit Mitra, Suhang Wang:
Knowing your FATE: Friendship, Action and Temporal Explanations for User Engagement Prediction on Social Apps. 2269-2279 - Alexander Immer, Victor Kristof, Matthias Grossglauser, Patrick Thiran:
Sub-Matrix Factorization for Real-Time Vote Prediction. 2280-2290 - Yifei Ma, Balakrishnan (Murali) Narayanaswamy, Haibin Lin, Hao Ding:
Temporal-Contextual Recommendation in Real-Time. 2291-2299 - Linxia Gong, Xiaochuan Feng, Dezhi Ye, Hao Li, Runze Wu, Jianrong Tao, Changjie Fan, Peng Cui:
OptMatch: Optimized Matchmaking via Modeling the High-Order Interactions on the Arena. 2300-2310 - Aditya Pal, Chantat Eksombatchai, Yitong Zhou, Bo Zhao, Charles Rosenberg, Jure Leskovec:
PinnerSage: Multi-Modal User Embedding Framework for Recommendations at Pinterest. 2311-2320 - Hao Liu, Ying Li, Yanjie Fu, Huaibo Mei, Jingbo Zhou, Xu Ma, Hui Xiong:
Polestar: An Intelligent, Efficient and National-Wide Public Transportation Routing Engine. 2321-2329 - Aritra Ghosh, Neil T. Heffernan, Andrew S. Lan:
Context-Aware Attentive Knowledge Tracing. 2330-2339 - Eason Wang, Henggang Cui, Sai Yalamanchi, Mohana Moorthy, Nemanja Djuric:
Improving Movement Predictions of Traffic Actors in Bird's-Eye View Models using GANs and Differentiable Trajectory Rasterization. 2340-2348 - Menghan Wang, Yujie Lin, Guli Lin, Keping Yang, Xiao-Ming Wu:
M2GRL: A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender Systems. 2349-2358 - Zhen Qin, Suming J. Chen, Donald Metzler, Yongwoo Noh, Jingzheng Qin, Xuanhui Wang:
Attribute-based Propensity for Unbiased Learning in Recommender Systems: Algorithm and Case Studies. 2359-2367 - Teng Ye, Wei Ai, Lingyu Zhang, Ning Luo, Lulu Zhang, Jieping Ye, Qiaozhu Mei:
Predicting Individual Treatment Effects of Large-scale Team Competitions in a Ride-sharing Economy. 2368-2377 - Xin Zhang, Xiujun Shu, Bingwen Zhang, Jie Ren, Lizhou Zhou, Xin Chen:
Cellular Network Radio Propagation Modeling with Deep Convolutional Neural Networks. 2378-2386 - Manas R. Joglekar, Cong Li, Mei Chen, Taibai Xu, Xiaoming Wang, Jay K. Adams, Pranav Khaitan, Jiahui Liu, Quoc V. Le:
Neural Input Search for Large Scale Recommendation Models. 2387-2397 - David O. Nahmias, Kimberly L. Kontson:
Easy Perturbation EEG Algorithm for Spectral Importance (easyPEASI): A Simple Method to Identify Important Spectral Features of EEG in Deep Learning Models. 2398-2406 - Bojan Karlas, Matteo Interlandi, Cédric Renggli, Wentao Wu, Ce Zhang, Deepak Mukunthu Iyappan Babu, Jordan Edwards, Chris Lauren, Andy Xu, Markus Weimer:
Building Continuous Integration Services for Machine Learning. 2407-2415 - Weize Kong, Michael Bendersky, Marc Najork, Brandon Vargo, Mike Colagrosso:
Learning to Cluster Documents into Workspaces Using Large Scale Activity Logs. 2416-2424 - Chiqun Zhang, Dragomir Yankov, Chun-Ting Wu, Simon Shapiro, Jason Hong, Wei Wu:
What is that Building?: An End-to-end System for Building Recognition from Streetside Images. 2425-2433 - Carl Yang, Aditya Pal, Andrew Zhai, Nikil Pancha, Jiawei Han, Charles Rosenberg, Jure Leskovec:
MultiSage: Empowering GCN with Contextualized Multi-Embeddings on Web-Scale Multipartite Networks. 2434-2443 - Huiting Hong, Yucheng Lin, Xiaoqing Yang, Zang Li, Kun Fu, Zheng Wang, Xiaohu Qie, Jieping Ye:
HetETA: Heterogeneous Information Network Embedding for Estimating Time of Arrival. 2444-2454 - Chenyi Zhuang, Ziqi Liu, Zhiqiang Zhang, Yize Tan, Zhengwei Wu, Zhining Liu, Jianping Wei, Jinjie Gu, Guannan Zhang, Jun Zhou, Yuan Qi:
Hubble: An Industrial System for Audience Expansion in Mobile Marketing. 2455-2463 - Aleksandar Bojchevski, Johannes Klicpera, Bryan Perozzi, Amol Kapoor, Martin Blais, Benedek Rózemberczki, Michal Lukasik, Stephan Günnemann:
Scaling Graph Neural Networks with Approximate PageRank. 2464-2473 - Tan Yu, Yi Yang, Yi Li, Xiaodong Chen, Mingming Sun, Ping Li:
Combo-Attention Network for Baidu Video Advertising. 2474-2482 - Bin Gu, Zhiyuan Dang, Xiang Li, Heng Huang:
Federated Doubly Stochastic Kernel Learning for Vertically Partitioned Data. 2483-2493 - Ayat Fekry, Lucian Carata, Thomas F. J.-M. Pasquier, Andrew Rice, Andy Hopper:
To Tune or Not to Tune?: In Search of Optimal Configurations for Data Analytics. 2494-2504 - Jing Lei, Nasrin Akhter, Wanli Qiao, Amarda Shehu:
Reconstruction and Decomposition of High-Dimensional Landscapes via Unsupervised Learning. 2505-2513 - Rui Zhang, Conrad M. Albrecht, Wei Zhang, Xiaodong Cui, Ulrich Finkler, David S. Kung, Siyuan Lu:
Map Generation from Large Scale Incomplete and Inaccurate Data Labels. 2514-2522 - Jonathan Halcrow, Alexandru Mosoi, Sam Ruth, Bryan Perozzi:
Grale: Designing Networks for Graph Learning. 2523-2532 - Yaqing Wang, Yifan Ethan Xu, Xian Li, Xin Luna Dong, Jing Gao:
Automatic Validation of Textual Attribute Values in E-commerce Catalog by Learning with Limited Labeled Data. 2533-2541 - Viet-An Nguyen, Peibei Shi, Jagdish Ramakrishnan, Udi Weinsberg, Henry C. Lin, Steve Metz, Neil Chandra, Jane Jing, Dimitris Kalimeris:
CLARA: Confidence of Labels and Raters. 2542-2552 - Jui-Ting Huang, Ashish Sharma, Shuying Sun, Li Xia, David Zhang, Philip Pronin, Janani Padmanabhan, Giuseppe Ottaviano, Linjun Yang:
Embedding-based Retrieval in Facebook Search. 2553-2561 - Jamie Pool, Ebrahim Beyrami, Vishak Gopal, Ashkan Aazami, Jayant Gupchup, Jeff Rowland, Binlong Li, Pritesh Kanani, Ross Cutler, Johannes Gehrke:
Lumos: A Library for Diagnosing Metric Regressions in Web-Scale Applications. 2562-2570 - Lin Zhu, Wei Yu, Kairong Zhou, Xing Wang, Wenxing Feng, Pengyu Wang, Ning Chen, Pei Lee:
Order Fulfillment Cycle Time Estimation for On-Demand Food Delivery. 2571-2580 - Daheng Wang, Meng Jiang, Munira Syed, Oliver Conway, Vishal Juneja, Sriram Subramanian, Nitesh V. Chawla:
Calendar Graph Neural Networks for Modeling Time Structures in Spatiotemporal User Behaviors. 2581-2589 - Chen Xu, Quan Li, Junfeng Ge, Jinyang Gao, Xiaoyong Yang, Changhua Pei, Fei Sun, Jian Wu, Hanxiao Sun, Wenwu Ou:
Privileged Features Distillation at Taobao Recommendations. 2590-2598 - Hongwei Li, Qingping Yang, Yixuan Cao, Jiaquan Yao, Ping Luo:
Cracking Tabular Presentation Diversity for Automatic Cross-Checking over Numerical Facts. 2599-2607 - Sean Bell, Yiqun Liu, Sami Alsheikh, Yina Tang, Edward Pizzi, M. Henning, Karun Singh, Omkar Parkhi, Fedor Borisyuk:
GrokNet: Unified Computer Vision Model Trunk and Embeddings For Commerce. 2608-2616 - Ata Akbari Asanjan, Kamalika Das, Alan S. Li, Ved Chirayath, Juan Torres-Perez, Soroosh Sorooshian:
Learning Instrument Invariant Characteristics for Generating High-resolution Global Coral Reef Maps. 2617-2624 - Zenan Wang, Xuan Yin, Tianbo Li, Liangjie Hong:
Causal Meta-Mediation Analysis: Inferring Dose-Response Function From Summary Statistics of Many Randomized Experiments. 2625-2635 - Bin Liu, Chenxu Zhu, Guilin Li, Weinan Zhang, Jincai Lai, Ruiming Tang, Xiuqiang He, Zhenguo Li, Yong Yu:
AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction. 2636-2645 - Yu Wei, Minjia Mao, Xi Zhao, Jianhua Zou, Ping An:
City Metro Network Expansion with Reinforcement Learning. 2646-2656 - Sharanya Eswaran, Mridul Sachdeva, Vikram Vimal, Deepanshi Seth, Suhaas Kalpam, Sanjay Agarwal, Tridib Mukherjee, Samrat Dattagupta:
Game Action Modeling for Fine Grained Analyses of Player Behavior in Multi-player Card Games (Rummy as Case Study). 2657-2665 - Francesco Ducci, Mathias Kraus, Stefan Feuerriegel:
Cascade-LSTM: A Tree-Structured Neural Classifier for Detecting Misinformation Cascades. 2666-2676 - Jizhou Huang, Haifeng Wang, Miao Fan, An Zhuo, Ying Li:
Personalized Prefix Embedding for POI Auto-Completion in the Search Engine of Baidu Maps. 2677-2685 - Hu Liu, Jing Lu, Hao Yang, Xiwei Zhao, Sulong Xu, Hao Peng, Zehua Zhang, Wenjie Niu, Xiaokun Zhu, Yongjun Bao, Weipeng Yan:
Category-Specific CNN for Visual-aware CTR Prediction at JD.com. 2686-2696 - Xiaomin Fang, Jizhou Huang, Fan Wang, Lingke Zeng, Haijin Liang, Haifeng Wang:
ConSTGAT: Contextual Spatial-Temporal Graph Attention Network for Travel Time Estimation at Baidu Maps. 2697-2705 - Junyi Li, Heng Huang:
Faster Secure Data Mining via Distributed Homomorphic Encryption. 2706-2714 - Dawei Cheng, Zhibin Niu, Yiyi Zhang:
Contagious Chain Risk Rating for Networked-guarantee Loans. 2715-2723 - Xin Luna Dong, Xiang He, Andrey Kan, Xian Li, Yan Liang, Jun Ma, Yifan Ethan Xu, Chenwei Zhang, Tong Zhao, Gabriel Blanco Saldana, Saurabh Deshpande, Alexandre Michetti Manduca, Jay Ren, Surender Pal Singh, Fan Xiao, Haw-Shiuan Chang, Giannis Karamanolakis, Yuning Mao, Yaqing Wang, Christos Faloutsos, Andrew McCallum, Jiawei Han:
AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types. 2724-2734 - Xiaowei Jia, Handong Zhao, Zhe Lin, Ajinkya Kale, Vipin Kumar:
Personalized Image Retrieval with Sparse Graph Representation Learning. 2735-2743 - Shengyu Zhang, Ziqi Tan, Zhou Zhao, Jin Yu, Kun Kuang, Tan Jiang, Jingren Zhou, Hongxia Yang, Fei Wu:
Comprehensive Information Integration Modeling Framework for Video Titling. 2744-2754 - Ying Li, Abraham Miller, Arthur Liu, Kyle Coburn, Luis J. Salazar:
Acoustic Measures for Real-Time Voice Coaching. 2755-2763 - Kaichen Zhang, Jingbo Zhou, Donglai Tao, Panagiotis Karras, Qing Li, Hui Xiong:
Geodemographic Influence Maximization. 2764-2774 - Monidipa Das, Mahardhika Pratama, Tegoeh Tjahjowidodo:
A Self-Evolving Mutually-Operative Recurrent Network-based Model for Online Tool Condition Monitoring in Delay Scenario. 2775-2783 - Yifei Zhao, Yu-Hang Zhou, Mingdong Ou, Huan Xu, Nan Li:
Maximizing Cumulative User Engagement in Sequential Recommendation: An Online Optimization Perspective. 2784-2792 - Ying Li, Vitalii Zakhozhyi, Daniel Zhu, Luis J. Salazar:
Domain Specific Knowledge Graphs as a Service to the Public: Powering Social-Impact Funding in the US. 2793-2801 - Jin Xu, Xu Tan, Yi Ren, Tao Qin, Jian Li, Sheng Zhao, Tie-Yan Liu:
LRSpeech: Extremely Low-Resource Speech Synthesis and Recognition. 2802-2812 - Sijie Ruan, Zi Xiong, Cheng Long, Yiheng Chen, Jie Bao, Tianfu He, Ruiyuan Li, Shengnan Wu, Zhongyuan Jiang, Yu Zheng:
Doing in One Go: Delivery Time Inference Based on Couriers' Trajectories. 2813-2821 - Malay Haldar, Prashant Ramanathan, Tyler Sax, Mustafa Abdool, Lanbo Zhang, Aamir Mansawala, Shulin Yang, Bradley C. Turnbull, Junshuo Liao:
Improving Deep Learning for Airbnb Search. 2822-2830 - Junqi Zhang, Bing Bai, Ye Lin, Jian Liang, Kun Bai, Fei Wang:
General-Purpose User Embeddings based on Mobile App Usage. 2831-2840 - Takahiro Yabe, Kota Tsubouchi, Toru Shimizu, Yoshihide Sekimoto, Satish V. Ukkusuri:
Unsupervised Translation via Hierarchical Anchoring: Functional Mapping of Places across Cities. 2841-2851 - Ruocheng Guo, Xiaoting Zhao, Adam Henderson, Liangjie Hong, Huan Liu:
Debiasing Grid-based Product Search in E-commerce. 2852-2860 - Fan Zhou, Liang Li, Kunpeng Zhang, Goce Trajcevski, Fuming Yao, Ying Huang, Ting Zhong, Jiahao Wang, Qiao Liu:
Forecasting the Evolution of Hydropower Generation. 2861-2870 - Baoxu Shi, Jaewon Yang, Feng Guo, Qi He:
Salience and Market-aware Skill Extraction for Job Targeting. 2871-2879 - Sundong Kim, Yu-Che Tsai, Karandeep Singh, Yeonsoo Choi, Etim Ibok, Cheng-Te Li, Meeyoung Cha:
DATE: Dual Attentive Tree-aware Embedding for Customs Fraud Detection. 2880-2890 - Ercan Yildiz, Joshua Safyan, Marc Harper:
User Sentiment as a Success Metric: Persistent Biases Under Full Randomization. 2891-2899 - Suming J. Chen, Zhen Qin, Zac Wilson, Brian Calaci, Michael Rose, Ryan Evans, Sean Abraham, Donald Metzler, Sandeep Tata, Mike Colagrosso:
Improving Recommendation Quality in Google Drive. 2900-2908 - Liuyihan Song, Pan Pan, Kang Zhao, Hao Yang, Yiming Chen, Yingya Zhang, Yinghui Xu, Rong Jin:
Large-Scale Training System for 100-Million Classification at Alibaba. 2909-2930 - Linjun Shou, Shining Bo, Feixiang Cheng, Ming Gong, Jian Pei, Daxin Jiang:
Mining Implicit Relevance Feedback from User Behavior for Web Question Answering. 2931-2941 - Yukuo Cen, Jianwei Zhang, Xu Zou, Chang Zhou, Hongxia Yang, Jie Tang:
Controllable Multi-Interest Framework for Recommendation. 2942-2951 - Mustafa Abdool, Malay Haldar, Prashant Ramanathan, Tyler Sax, Lanbo Zhang, Aamir Manaswala, Lynn Yang, Bradley C. Turnbull, Qing Zhang, Thomas Legrand:
Managing Diversity in Airbnb Search. 2952-2960 - Seiji Takeda, Toshiyuki Hama, Hsiang-Han Hsu, Victoria A. Piunova, Dmitry Zubarev, Daniel P. Sanders, Jed W. Pitera, Makoto Kogoh, Takumi Hongo, Yenwei Cheng, Wolf Bocanett, Hideaki Nakashika, Akihiro Fujita, Yuta Tsuchiya, Katsuhiko Hino, Kentaro Yano, Shuichi Hirose, Hiroki Toda, Yasumitsu Orii, Daiju Nakano:
Molecular Inverse-Design Platform for Material Industries. 2961-2969 - Sungwon Han, Donghyun Ahn, Sungwon Park, Jeasurk Yang, Susang Lee, Jihee Kim, Hyunjoo Yang, Sangyoon Park, Meeyoung Cha:
Learning to Score Economic Development from Satellite Imagery. 2970-2979 - Hong Zhang, Lan Zhang, Lan Xu, Xiaoyang Ma, Zhengtao Wu, Cong Tang, Wei Xu, Yiguo Yang:
A Request-level Guaranteed Delivery Advertising Planning: Forecasting and Allocation. 2980-2988 - Yinghua Zhang, Yangqiu Song, Jian Liang, Kun Bai, Qiang Yang:
Two Sides of the Same Coin: White-box and Black-box Attacks for Transfer Learning. 2989-2997 - Di Yin, Jiwei Tan, Zhe Zhang, Hongbo Deng, Shujian Huang, Jiajun Chen:
Learning to Generate Personalized Query Auto-Completions via a Multi-View Multi-Task Attentive Approach. 2998-3007 - Kevin P. Yancey, Burr Settles:
A Sleeping, Recovering Bandit Algorithm for Optimizing Recurring Notifications. 3008-3016 - Hang Lei, Yin Zhao, Longjun Cai:
Multi-objective Optimization for Guaranteed Delivery in Video Service Platform. 3017-3025 - Xuetao Ding, Runfeng Zhang, Zhen Mao, Ke Xing, Fangxiao Du, Xingyu Liu, Guoxing Wei, Feifan Yin, Renqing He, Zhizhao Sun:
Delivery Scope: A New Way of Restaurant Retrieval for On-demand Food Delivery Service. 3026-3034 - Can Liu, Qiwei Zhong, Xiang Ao, Li Sun, Wangli Lin, Jinghua Feng, Qing He, Jiayu Tang:
Fraud Transactions Detection via Behavior Tree with Local Intention Calibration. 3035-3043 - Lu Duan, Haoyuan Hu, Zili Wu, Guozheng Li, Xinhang Zhang, Yu Gong, Yinghui Xu:
Balanced Order Batching with Task-Oriented Graph Clustering. 3044-3053 - Lu Duan, Yang Zhan, Haoyuan Hu, Yu Gong, Jiangwen Wei, Xiaodong Zhang, Yinghui Xu:
Efficiently Solving the Practical Vehicle Routing Problem: A Novel Joint Learning Approach. 3054-3063 - Fred X. Han, Di Niu, Haolan Chen, Weidong Guo, Shengli Yan, Bowei Long:
Meta-Learning for Query Conceptualization at Web Scale. 3064-3073 - Rui Dai, Shenkun Xu, Qian Gu, Chenguang Ji, Kaikui Liu:
Hybrid Spatio-Temporal Graph Convolutional Network: Improving Traffic Prediction with Navigation Data. 3074-3082 - Zhen Qin, Yicheng Cheng, Zhe Zhao, Zhe Chen, Donald Metzler, Jingzheng Qin:
Multitask Mixture of Sequential Experts for User Activity Streams. 3083-3091 - Maryam Tabar, Heesoo Park, Stephanie Winkler, Dongwon Lee, Anamika Barman-Adhikari, Amulya Yadav:
Identifying Homeless Youth At-Risk of Substance Use Disorder: Data-Driven Insights for Policymakers. 3092-3100 - Bernardo Branco, Pedro Abreu, Ana Sofia Gomes, Mariana S. C. Almeida, João Tiago Ascensão, Pedro Bizarro:
Interleaved Sequence RNNs for Fraud Detection. 3101-3109 - Vijay Ekambaram, Kushagra Manglik, Sumanta Mukherjee, Surya Shravan Kumar Sajja, Satyam Dwivedi, Vikas Raykar:
Attention based Multi-Modal New Product Sales Time-series Forecasting. 3110-3118 - Aman Dalmia, Jerome White, Ankit Chaurasia, Vishal Agarwal, Rajesh Jain, Dhruvin Vora, Balasaheb Dhame, Raghu Dharmaraju, Rahul Panicker:
Pest Management In Cotton Farms: An AI-System Case Study from the Global South. 3119-3127 - Nima Noorshams, Saurabh Verma, Aude Hofleitner:
TIES: Temporal Interaction Embeddings for Enhancing Social Media Integrity at Facebook. 3128-3135 - Prakhar Mehrotra, Linsey Pang, Karthick Gopalswamy, Avinash Thangali, Timothy Winters, Ketki Gupte, Dnyanesh Kulkarni, Sunil Potnuru, Supreeth Shastry, Harshada Vuyyuri:
Price Investment using Prescriptive Analytics and Optimization in Retail. 3136-3144 - Yumin Liu, Auroop R. Ganguly, Jennifer G. Dy:
Climate Downscaling Using YNet: A Deep Convolutional Network with Skip Connections and Fusion. 3145-3153 - Xiangyu Sun, Jack Davis, Oliver Schulte, Guiliang Liu:
Cracking the Black Box: Distilling Deep Sports Analytics. 3154-3162 - Wei-Cheng Chang, Hsiang-Fu Yu, Kai Zhong, Yiming Yang, Inderjit S. Dhillon:
Taming Pretrained Transformers for Extreme Multi-label Text Classification. 3163-3171 - Anna Lioznova, Alexey Drutsa, Vladimir Kukushkin, Anastasia A. Bezzubtseva:
Prediction of Hourly Earnings and Completion Time on a Crowdsourcing Platform. 3172-3182 - Venu Satuluri, Yao Wu, Xun Zheng, Yilei Qian, Brian Wichers, Qieyun Dai, Gui Ming Tang, Jerry Jiang, Jimmy Lin:
SimClusters: Community-Based Representations for Heterogeneous Recommendations at Twitter. 3183-3193 - Martin Pavlovski, Jelena Gligorijevic, Ivan Stojkovic, Shubham Agrawal, Shabhareesh Komirishetty, Djordje Gligorijevic, Narayan Bhamidipati, Zoran Obradovic:
Time-Aware User Embeddings as a Service. 3194-3202 - Raymond Shiau, Hao-Yu Wu, Eric Kim, Yue Li Du, Anqi Guo, Zhiyuan Zhang, Eileen Li, Kunlong Gu, Charles Rosenberg, Andrew Zhai:
Shop The Look: Building a Large Scale Visual Shopping System at Pinterest. 3203-3212 - Wenjuan Luo, Han Zhang, Xiaodi Yang, Lin Bo, Xiaoqing Yang, Zang Li, Xiaohu Qie, Jieping Ye:
Dynamic Heterogeneous Graph Neural Network for Real-time Event Prediction. 3213-3223 - Rishabh Mehrotra, Niannan Xue, Mounia Lalmas:
Bandit based Optimization of Multiple Objectives on a Music Streaming Platform. 3224-3233 - Krishna Karthik Gadiraju, Bharathkumar Ramachandra, Zexi Chen, Ranga Raju Vatsavai:
Multimodal Deep Learning Based Crop Classification Using Multispectral and Multitemporal Satellite Imagery. 3234-3242 - Richard Barnes, Senaka Buthpitiya, James Cook, Alex Fabrikant, Andrew Tomkins, Fangzhou Xu:
BusTr: Predicting Bus Travel Times from Real-Time Traffic. 3243-3251 - Shuai Zhao, Wen-Ling Hsu, George Ma, Tan Xu, Guy Jacobson, Raif M. Rustamov:
Characterizing and Learning Representation on Customer Contact Journeys in Cellular Services. 3252-3260 - Xin Huang, Jangsoo Lee, Young-Woo Kwon, Chul-Ho Lee:
CrowdQuake: A Networked System of Low-Cost Sensors for Earthquake Detection via Deep Learning. 3261-3271 - Megha Srivastava, Besmira Nushi, Ece Kamar, Shital Shah, Eric Horvitz:
An Empirical Analysis of Backward Compatibility in Machine Learning Systems. 3272-3280 - Phuong Pham, Vivek Jain, Lukas Dauterman, Justin Ormont, Navendu Jain:
DeepTriage: Automated Transfer Assistance for Incidents in Cloud Services. 3281-3289 - Zekun Li, Yao-Yi Chiang, Sasan Tavakkol, Basel Shbita, Johannes H. Uhl, Stefan Leyk, Craig A. Knoblock:
An Automatic Approach for Generating Rich, Linked Geo-Metadata from Historical Map Images. 3290-3298 - Eileen Li, Eric Kim, Andrew Zhai, Josh Beal, Kunlong Gu:
Bootstrapping Complete The Look at Pinterest. 3299-3307 - Tommaso Lanciano, Francesco Bonchi, Aristides Gionis:
Explainable Classification of Brain Networks via Contrast Subgraphs. 3308-3318 - Xiangyu Zhao, Xudong Zheng, Xiwang Yang, Xiaobing Liu, Jiliang Tang:
Jointly Learning to Recommend and Advertise. 3319-3327 - Alireza Abdoli, Sara Alaee, Shima Imani, Amy C. Murillo, Alec C. Gerry, Leslie Hickle, Eamonn J. Keogh:
Fitbit for Chickens?: Time Series Data Mining Can Increase the Productivity of Poultry Farms. 3328-3336 - Kun Fu, Fanlin Meng, Jieping Ye, Zheng Wang:
CompactETA: A Fast Inference System for Travel Time Prediction. 3337-3345 - Jingbo Zhou, Zhenwei Tang, Min Zhao, Xiang Ge, Fuzhen Zhuang, Meng Zhou, Liming Zou, Chenglei Yang, Hui Xiong:
Intelligent Exploration for User Interface Modules of Mobile App with Collective Learning. 3346-3355 - Jixing Xu, Zhenlong Zhu, Jianxin Zhao, Xuanye Liu, Minghui Shan, Jiecheng Guo:
Gemini: A Novel and Universal Heterogeneous Graph Information Fusing Framework for Online Recommendations. 3356-3365 - Jaehyuk Yi, Jinkyoo Park:
Hypergraph Convolutional Recurrent Neural Network. 3366-3376 - Che Liu, Junfeng Jiang, Chao Xiong, Yi Yang, Jieping Ye:
Towards Building an Intelligent Chatbot for Customer Service: Learning to Respond at the Appropriate Time. 3377-3385 - Jinyun Yan, Zhiyuan Xu, Birjodh Tiwana, Shaunak Chatterjee:
Ads Allocation in Feed via Constrained Optimization. 3386-3394 - Julien Audibert, Pietro Michiardi, Frédéric Guyard, Sébastien Marti, Maria A. Zuluaga:
USAD: UnSupervised Anomaly Detection on Multivariate Time Series. 3395-3404 - Xichuan Niu, Bofang Li, Chenliang Li, Rong Xiao, Haochuan Sun, Hongbo Deng, Zhenzhong Chen:
A Dual Heterogeneous Graph Attention Network to Improve Long-Tail Performance for Shop Search in E-Commerce. 3405-3415 - Rishabh Mehrotra, Ashish Gupta:
Learning with Limited Labels via Momentum Damped & Differentially Weighted Optimization. 3416-3425
Health Day Papers
- Jie Feng, Zeyu Yang, Fengli Xu, Haisu Yu, Mudan Wang, Yong Li:
Learning to Simulate Human Mobility. 3426-3433 - Salah Ghamizi, Renaud Rwemalika, Maxime Cordy, Lisa Veiber, Tegawendé F. Bissyandé, Mike Papadakis, Jacques Klein, Yves Le Traon:
Data-driven Simulation and Optimization for Covid-19 Exit Strategies. 3434-3442 - Jizhou Huang, Haifeng Wang, Miao Fan, An Zhuo, Yibo Sun, Ying Li:
Understanding the Impact of the COVID-19 Pandemic on Transportation-related Behaviors with Human Mobility Data. 3443-3450 - Shaon Bhatta Shuvo, Bonaventure C. Molokwu, Ziad Kobti:
Simulating the Impact of Hospital Capacity and Social Isolation to Minimize the Propagation of Infectious Diseases. 3451-3457 - Clara H. McCreery, Namit Katariya, Anitha Kannan, Manish Chablani, Xavier Amatriain:
Effective Transfer Learning for Identifying Similar Questions: Matching User Questions to COVID-19 FAQs. 3458-3465 - Minseok Kim, Junhyeok Kang, Doyoung Kim, Hwanjun Song, Hyangsuk Min, Youngeun Nam, Dongmin Park, Jae-Gil Lee:
Hi-COVIDNet: Deep Learning Approach to Predict Inbound COVID-19 Patients and Case Study in South Korea. 3466-3473 - Chloë Brown, Jagmohan Chauhan, Andreas Grammenos, Jing Han, Apinan Hasthanasombat, Dimitris Spathis, Tong Xia, Pietro Cicuta, Cecilia Mascolo:
Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data. 3474-3484 - Qianyue Hao, Lin Chen, Fengli Xu, Yong Li:
Understanding the Urban Pandemic Spreading of COVID-19 with Real World Mobility Data. 3485-3492
Panel
- Tina Eliassi-Rad, Nitesh V. Chawla, Vittoria Colizza, Lauren Gardner, Marcel Salathé, Samuel V. Scarpino, Joseph T. Wu:
Fighting a Pandemic: Convergence of Expertise, Data Science and Policy. 3493-3494
Tutorial Abstracts
- Aniththa Umamahesan, Deepak Mukunthu Iyappan Babu:
From Zero to AI Hero with Automated Machine Learning. 3495 - Wenming Ye, Rachel Hu, Miro Enev:
Put Deep Learning to Work: Accelerate Deep Learning through Amazon SageMaker and ML Services. 3496 - Chenhui Hu, Vanja Paunic:
Building Forecasting Solutions Using Open-Source and Azure Machine Learning. 3497-3498 - Natalia Culakova, Dan Murphy, Joao Gante, Carlos Ledezma, Vahan Hovhannisyan, Alan Mosca:
How to Calibrate your Neural Network Classifier: Getting True Probabilities from a Classification Model. 3499-3500 - Arjun Gopalan, Da-Cheng Juan, Cesar Ilharco Magalhaes, Chun-Sung Ferng, Allan Heydon, Chun-Ta Lu, Philip Pham, George Yu:
Neural Structured Learning: Training Neural Networks with Structured Signals. 3501-3502 - Bartley Richardson, Bradley Rees, Tom Drabas, Even Oldridge, David A. Bader, Rachel Allen:
Accelerating and Expanding End-to-End Data Science Workflows with DL/ML Interoperability Using RAPIDS. 3503-3504 - Jeff Rasley, Samyam Rajbhandari, Olatunji Ruwase, Yuxiong He:
DeepSpeed: System Optimizations Enable Training Deep Learning Models with Over 100 Billion Parameters. 3505-3506 - Raghavendra Chalapathy, Nguyen Lu Dang Khoa, Sanjay Chawla:
Robust Deep Learning Methods for Anomaly Detection. 3507-3508 - Jonas Mueller, Xingjian Shi, Alexander J. Smola:
Faster, Simpler, More Accurate: Practical Automated Machine Learning with Tabular, Text, and Image Data. 3509-3510 - Rich Caruana, Scott M. Lundberg, Marco Túlio Ribeiro, Harsha Nori, Samuel Jenkins:
Intelligible and Explainable Machine Learning: Best Practices and Practical Challenges. 3511-3512 - Pedro Saleiro, Kit T. Rodolfa, Rayid Ghani:
Dealing with Bias and Fairness in Data Science Systems: A Practical Hands-on Tutorial. 3513-3514 - Zhoutong Fu, Huiji Gao, Weiwei Guo, Sandeep Kumar Jha, Jun Jia, Xiaowei Liu, Bo Long, Jun Shi, Sida Wang, Mingzhou Zhou:
Deep Learning for Search and Recommender Systems in Practice. 3515-3516 - Yuanbo Wang, Osama Sakhi, Ala Eddine Ayadi, Matthew S. Hagen, Estelle Afshar:
Computer Vision: Deep Dive into Object Segmentation Approaches. 3517-3518 - Iris Shen, Le Zhang, Jianxun Lian, Chieh-Han Wu, Miguel González-Fierro, Andreas Argyriou, Tao Wu:
In Search for a Cure: Recommendation With Knowledge Graph on CORD-19. 3519-3520 - Da Zheng, Minjie Wang, Quan Gan, Zheng Zhang, George Karypis:
Scalable Graph Neural Networks with Deep Graph Library. 3521-3522 - James G. Shanahan, Liang Dai:
Introduction to Computer Vision and Real Time Deep Learning-based Object Detection. 3523-3524 - Dheevatsa Mudigere, Maxim Naumov, Joe Spisak, Geeta Chauhan, Narine Kokhlikyan, Amanpreet Singh, Vedanuj Goswami:
Building Recommender Systems with PyTorch. 3525-3526 - Peng Cui, Zheyan Shen, Sheng Li, Liuyi Yao, Yaliang Li, Zhixuan Chu, Jing Gao:
Causal Inference Meets Machine Learning. 3527-3528 - Muhammad Aurangzeb Ahmad, Arpit Patel, Carly Eckert, Vikas Kumar, Ankur Teredesai:
Fairness in Machine Learning for Healthcare. 3529-3530 - Zhiting Hu, Eric P. Xing:
Learning from All Types of Experiences: A Unifying Machine Learning Perspective. 3531-3532 - Rishabh Mehrotra, Ben Carterette, Yong Li, Quanming Yao, Chen Gao, James T. Kwok, Qiang Yang, Isabelle Guyon:
Advances in Recommender Systems: From Multi-stakeholder Marketplaces to Automated RecSys. 3533-3534 - Muhammad Aurangzeb Ahmad, Sener Özönder:
Physics Inspired Models in Artificial Intelligence. 3535-3536 - Meng Jiang, Jingbo Shang:
Scientific Text Mining and Knowledge Graphs. 3537-3538 - Huaxiu Yao, Xiaowei Jia, Vipin Kumar, Zhenhui Li:
Learning with Small Data. 3539-3540 - Han Xu, Yaxin Li, Wei Jin, Jiliang Tang:
Adversarial Attacks and Defenses: Frontiers, Advances and Practice. 3541-3542 - Xin Luna Dong, Hannaneh Hajishirzi, Colin Lockard, Prashant Shiralkar:
Multi-modal Information Extraction from Text, Semi-structured, and Tabular Data on the Web. 3543-3544 - Fei Wang, Peng Cui, Jian Pei, Yangqiu Song, Chengxi Zang:
Recent Advances on Graph Analytics and Its Applications in Healthcare. 3545-3546 - Prithwish Chakraborty, Bum Chul Kwon, Sanjoy Dey, Amit Dhurandhar, Daniel M. Gruen, Kenney Ng, Daby Sow, Kush R. Varshney:
Tutorial on Human-Centered Explainability for Healthcare. 3547-3548 - Zitao Liu, Songfan Yang, Jiliang Tang, Neil T. Heffernan, Rose Luckin:
Recent Advances in Multimodal Educational Data Mining in K-12 Education. 3549-3550 - Liangjie Hong, Mounia Lalmas:
Tutorial on Online User Engagement: Metrics and Optimization. 3551-3552 - Jian Pei:
Data Pricing - From Economics to Data Science. 3553-3554 - Yu Rong, Tingyang Xu, Junzhou Huang, Wenbing Huang, Hong Cheng, Yao Ma, Yiqi Wang, Tyler Derr, Lingfei Wu, Tengfei Ma:
Deep Graph Learning: Foundations, Advances and Applications. 3555-3556 - Chuxu Zhang, Meng Jiang, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla:
Multi-modal Network Representation Learning. 3557-3558 - Ron Bekkerman, Vanja Josifovski, Foster J. Provost:
Data Science for the Real Estate Industry. 3559-3560 - Abhinav Jain, Hima Patel, Lokesh Nagalapatti, Nitin Gupta, Sameep Mehta, Shanmukha C. Guttula, Shashank Mujumdar, Shazia Afzal, Ruhi Sharma Mittal, Vitobha Munigala:
Overview and Importance of Data Quality for Machine Learning Tasks. 3561-3562 - Jaesik Choi:
Interpreting and Explaining Deep Neural Networks: A Perspective on Time Series Data. 3563-3564 - Radu Marculescu, Diana Marculescu, Ümit Y. Ogras:
Edge AI: Systems Design and ML for IoT Data Analytics. 3565-3566 - Daniel Ting, Jonathan Malkin, Lee Rhodes:
Data Sketching for Real Time Analytics: Theory and Practice. 3567-3568 - Ruoying Wang, Kexin Nie, Yen-Jung Chang, Xinwei Gong, Tie Wang, Yang Yang, Bo Long:
Deep Learning for Anomaly Detection. 3569-3570 - Chetan Gupta, Ahmed K. Farahat:
Deep Learning for Industrial AI: Challenges, New Methods and Best Practices. 3571-3572 - Yu Meng, Jiaxin Huang, Jiawei Han:
Embedding-Driven Multi-Dimensional Topic Mining and Text Analysis. 3573-3574 - Qingyun Wu, Huazheng Wang, Hongning Wang:
Learning by Exploration: New Challenges in Real-World Environments. 3575-3576 - Aman Gupta, Sirjan Kafle, Di Wen, Dylan Wang, Sumit Srivastava, Suhit Sinha, Nikita Gupta, Bharat Jain, Ananth Sankar, Liang Zhang:
Image and Video Understanding for Recommendation and Spam Detection Systems. 3577-3578 - Estevam R. Hruschka Jr.:
Data-Driven Never-Ending Learning Question Answering Systems. 3579-3580
Diversity and Inclusion Abstracts
- Manuel A. Pérez-Quiñones:
How Can Computer Science Education Address Inequities. 3581 - Eliana Valenzuela Andrade:
Diversity and Inclusion, a Perspective from a Four Years MSI Faculty Member. 3582 - Wilson E. Lozano-Rolon:
CoRE Lab - An Effort to Engage College Hispanic Students in STEM. 3583 - Daniel A. Jiménez:
Support for Diverse Students. 3584 - Brianna B. Posadas:
Broadening Participation in Technology Policy. 3585 - Mariya I. Vasileva:
The Dark Side of Machine Learning Algorithms: How and Why They Can Leverage Bias, and What Can Be Done to Pursue Algorithmic Fairness. 3586-3587 - Brianna Blaser:
Accessible Online Meetings and Presentations. 3588 - Hasan Jackson:
Perspectives on Broadening Participation in STEM Careers across Academia, Government, and Industry. 3589-3590 - Keolu Fox:
The Illusion of Inclusion: Large Scale Genomic Data Sovereignty and Indigenous Populations. 3591 - Krystal S. Tsosie:
Models of Data Governance and Advancing Indigenous Genomic Data Sovereignty. 3592 - Caitlin Kuhlman, Latifa Jackson, Rumi Chunara:
No Computation without Representation: Avoiding Data and Algorithm Biases through Diversity. 3593 - Patricia Ordóñez Franco:
Mutually Beneficial Collaborations to Broaden Participation of Hispanics in Data Science. 3594-3595 - Heriberto Acosta Maestre:
Bringing Inclusive Diversity to Data Science: Opportunities and Challenges. 3596 - Latifa Jackson, Heriberto Acosta Maestre:
The Data Science Mentoring Fire Next Time: Innovative Strategies for Mentoring in Data Science. 3597-3600
Applied Data Science Invited Talks Abstracts
- Alon Y. Halevy:
Preserving Integrity in Online Social Media. 3601 - Daniel Marcu:
Straddling the Boundary between Contribution and Solution Driven Science. 3602 - Dorin Comaniciu:
Artificial Intelligence for Healthcare. 3603 - Jan Schellenberger:
Using Machine Learning to Detect Cancer Early. 3604 - Michael Li, Catalin Tiseanu, Burkay Gur:
Build the State-of-the-Art Machine Learning Technology for the Crypto Economy. 3605 - Nhung Ho:
How AI Can Help Build Resiliency for Small Businesses in a Global Economic Crisis. 3606 - Saleema Amershi:
Toward Responsible AI by Planning to Fail. 3607 - Shalini Ghosh:
Multimodal Machine Learning for Video and Image Analysis. 3608 - Timnit Gebru:
Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning. 3609 - Wang-Chiew Tan:
Unleashing the Power of Subjective Data: Managing Experiences as First-Class Citizens. 3610 - Ashwin Ram:
Innovating with Language AI. 3611 - Mona T. Diab:
Data Paucity and Low Resource Scenarios: Challenges and Opportunities. 3612
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