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ORCID12th ACML 2020: Bangkok, Thailand
- Sinno Jialin Pan, Masashi Sugiyama:
Proceedings of The 12th Asian Conference on Machine Learning, ACML 2020, 18-20 November 2020, Bangkok, Thailand. Proceedings of Machine Learning Research 129, PMLR 2020 - Haofei Chen, Ya Liu, Japnit Kaur Ahuja, Daren Ler:
A Distance-Weighted Class-Homogeneous Neighbourhood Ratio for Algorithm Selection. 1-16 - Xuena Ren, Dongming Zhang, Xiuguo Bao:
Semantic-Guided Shared Feature Alignment for Occluded Person Re-IDentification. 17-32 - Dung Nguyen, Svetha Venkatesh, Phuoc Nguyen, Truyen Tran:
Theory of Mind with Guilt Aversion Facilitates Cooperative Reinforcement Learning. 33-48 - Clemens Damke
, Vitalik Melnikov, Eyke Hüllermeier:
A Novel Higher-order Weisfeiler-Lehman Graph Convolution. 49-64 - Tianyi Zhang, Ikko Yamane, Nan Lu, Masashi Sugiyama:
A One-step Approach to Covariate Shift Adaptation. 65-80 - Reza Refaei Afshar, Yingqian Zhang, Murat Firat, Uzay Kaymak:
A State Aggregation Approach for Solving Knapsack Problem with Deep Reinforcement Learning. 81-96 - Zhonghong Li, Yang Yi, Ying She, Jialun Song, Yukun Wu:
AARM: Action Attention Recalibration Module for Action Recognition. 97-112 - Yuan Liang, Weinan Song, Jiawei Yang, Liang Qiu, Kun Wang, Lei He:
Atlas-aware ConvNet for Accurate yet Robust Anatomical Segmentation. 113-128 - Xingchen Deng, Lei Zhang, Yixing Fan, Long Bai, Jiafeng Guo, Pengfei Wang:
Bidirectional Dependency-Guided Attention for Relation Extraction. 129-144 - Yao-Xiang Ding, Zhi-Hua Zhou:
Boosting-Based Reliable Model Reuse. 145-160 - Yasuhiro Katsura, Masato Uchida:
Bridging Ordinary-Label Learning and Complementary-Label Learning. 161-176 - Jia He, Feiyang Pan, Fuzhen Zhuang, Qing He:
CCA-Flow: Deep Multi-view Subspace Learning with Inverse Autoregressive Flow. 177-192 - Hiba Dakdouk, Raphaël Féraud, Nadège Varsier, Patrick Maillé:
Collaborative Exploration in Stochastic Multi-Player Bandits. 193-208 - Haoxian Chen, Henry Lam, Fengpei Li, Amirhossein Meisami:
Constrained Reinforcement Learning via Policy Splitting. 209-224 - Anas Barakat, Pascal Bianchi:
Convergence Rates of a Momentum Algorithm with Bounded Adaptive Step Size for Nonconvex Optimization. 225-240 - Mitsuki Maekawa, Atsuyoshi Nakamura, Mineichi Kudo:
Data-Dependent Conversion to a Compact Integer-Weighted Representation of a Weighted Voting Classifier. 241-256 - Haixin Wang, Xingzhang Ren, Jinan Sun, Wei Ye, Long Chen, Muzhi Yu, Shikun Zhang:
Deep Dynamic Boosted Forest. 257-272 - Sourya Dey, Saikrishna C. Kanala, Keith M. Chugg, Peter A. Beerel:
Deep-n-Cheap: An Automated Search Framework for Low Complexity Deep Learning. 273-288 - Bowen Li, Kai Huang, Siang Chen, Dongliang Xiong, Haitian Jiang, Luc Claesen:
DFQF: Data Free Quantization-aware Fine-tuning. 289-304 - Masanori Yamada, Heecheol Kim, Kosuke Miyoshi, Tomoharu Iwata, Hiroshi Yamakawa:
Disentangled Representations for Sequence Data using Information Bottleneck Principle. 305-320 - Zhibing Zhao, Yingce Xia, Tao Qin, Lirong Xia, Tie-Yan Liu:
Dual Learning: Theoretical Study and an Algorithmic Extension. 321-336 - Hengfeng Zha, Rui Liu, Dongsheng Zhou, Xin Yang, Qiang Zhang, Xiaopeng Wei:
Efficient Attention Calibration Network for Real-Time Semantic Segmentation. 337-352 - Yang Hong, Xinhuai Tang, Tiancheng Tang, Yunlong Hu, Jintai Tian:
Enhancing Topic Models by Incorporating Explicit and Implicit External Knowledge. 353-368 - Maanik Arora, Naresh Manwani:
Exact Passive-Aggressive Algorithms for Multiclass Classification Using Bandit Feedbacks. 369-384 - Yuchu Fang, Wenzhong Li, Yao Zeng, Sanglu Lu:
FIREPruning: Learning-based Filter Pruning for Convolutional Neural Network Compression. 385-400 - Alexis Jacq, Julien Pérolat, Matthieu Geist, Olivier Pietquin:
Foolproof Cooperative Learning. 401-416 - Florian Yger, Sylvain Chevallier, Quentin Barthélemy, Suvrit Sra:
Geodesically-convex optimization for averaging partially observed covariance matrices. 417-432 - Jianxun Wang, David L. Roberts, Andinet Enquobahrie:
Inferring Continuous Treatment Doses from Historical Data via Model-Based Entropy-Regularized Reinforcement Learning. 433-448 - Yaser Alwatter, Yuhong Guo:
Inverse Visual Question Answering with Multi-Level Attentions. 449-464 - Paulo R. de O. da Costa, Jason Rhuggenaath, Yingqian Zhang, Alp Akcay:
Learning 2-opt Heuristics for the Traveling Salesman Problem via Deep Reinforcement Learning. 465-480 - Jia-Wei Mi, Shu-Ting Shi, Ming Li:
Learning Code Changes by Exploiting Bidirectional Converting Deviation. 481-496 - Chuanchang Chen, Yubo Tao, Hai Lin:
Learning Dynamic Context Graph Embedding. 497-512 - Kuen-Han Tsai, Hsuan-Tien Lin:
Learning from Label Proportions with Consistency Regularization. 513-528 - Khaled Belahcène, Nataliya Sokolovska, Yann Chevaleyre, Jean-Daniel Zucker:
Learning Interpretable Models using Soft Integrity Constraints. 529-544 - Arun Verma, Manjesh Kumar Hanawal, Nandyala Hemachandra:
Thompson Sampling for Unsupervised Sequential Selection. 545-560 - Kaushalya Madhawa, Tsuyoshi Murata:
{M. 561-576 - Edouard Leurent, Odalric-Ambrym Maillard:
Monte-Carlo Graph Search: the Value of Merging Similar States. 577-592 - Yulei Yang, Dongsheng Li:
NENN: Incorporate Node and Edge Features in Graph Neural Networks. 593-608 - Meng Liu, Ziwei Quan, Yong Liu:
Network Representation Learning Algorithm Based on Neighborhood Influence Sequence. 609-624 - Aadirupa Saha:
Polytime Decomposition of Generalized Submodular Base Polytopes with Efficient Sampling. 625-640 - Weipéng Huáng, Guangyuan Piao, Raúl Moreno, Neil Hurley:
Partially Observable Markov Decision Process Modelling for Assessing Hierarchies. 641-656 - Bin Xiao, Chien-Liang Liu, Wen-Hoar Hsaio:
Proxy Network for Few Shot Learning. 657-672 - Nishma Laitonjam, Weipéng Huáng, Neil J. Hurley:
Scalable Inference on the Soft Affiliation Graph Model for Overlapping Community Detection. 673-688 - Rameshwar Pratap, Karthik Revanuru, Anirudh Ravi, Raghav Kulkarni:
Randomness Efficient Feature Hashing for Sparse Binary Data. 689-704 - Rameshwar Pratap, Anup Anand Deshmukh, Pratheeksha Nair, Anirudh Ravi:
Scaling up Simhash. 705-720 - Zihao Wang, Datong Zhou, Ming Yang, Yong Zhang, Chenglong Rao, Hao Wu:
Robust Document Distance with Wasserstein-Fisher-Rao metric. 721-736 - Alexander Tornede, Marcel Wever, Stefan Werner, Felix Mohr, Eyke Hüllermeier:
Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis. 737-752 - Wenye Li:
Scalable Calibration of Affinity Matrices from Incomplete Observations. 753-768 - Shiwen Ni, Hung-Yu Kao:
PSForest: Improving Deep Forest via Feature Pooling and Error Screening. 769-781 - Bhanu Garg, Naresh Manwani:
Robust Deep Ordinal Regression under Label Noise. 782-796 - Detong Chen:
A foreground detection algorithm for Time-of-Flight cameras adapted dynamic integration time adjustment and multipath distortions. 797-810 - Qidong Liu, Feng Tian, Weihua Ji, Qinghua Zheng:
A New Representation Learning Method for Individual Treatment Effect Estimation: Split Covariate Representation Network. 811-822 - Linfeng Liu, Liping Liu:
Localizing and Amortizing: Efficient Inference for Gaussian Processes. 823-836 - Lei Wu, Zhanxing Zhu:
Towards Understanding and Improving the Transferability of Adversarial Examples in Deep Neural Networks. 837-850
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