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Huzefa Rangwala
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- affiliation: George Mason University, Fairfax VA, USA
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2020 – today
- 2024
- [c133]Yuze Lou, Chuan Lei, Xiao Qin, Zichen Wang, Christos Faloutsos, Rishita Anubhai, Huzefa Rangwala:
DATALORE: Can a Large Language Model Find All Lost Scrolls in a Data Repository? ICDE 2024: 5170-5176 - [c132]Zifeng Wang, Zichen Wang, Balasubramaniam Srinivasan, Vassilis N. Ioannidis, Huzefa Rangwala, Rishita Anubhai:
BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs. ICLR 2024 - [c131]Kezhi Kong, Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Chuan Lei, Christos Faloutsos, Huzefa Rangwala, George Karypis:
OpenTab: Advancing Large Language Models as Open-domain Table Reasoners. ICLR 2024 - [c130]Hengrui Zhang, Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Xiao Qin, Christos Faloutsos, Huzefa Rangwala, George Karypis:
Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space. ICLR 2024 - [c129]Da Zheng, Xiang Song, Qi Zhu, Jian Zhang, Theodore Vasiloudis, Runjie Ma, Houyu Zhang, Zichen Wang, Soji Adeshina, Israt Nisa, Alejandro Mottini, Qingjun Cui, Huzefa Rangwala, Belinda Zeng, Christos Faloutsos, George Karypis:
GraphStorm: All-in-one Graph Machine Learning Framework for Industry Applications. KDD 2024: 6356-6367 - [i43]Kezhi Kong, Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Chuan Lei, Christos Faloutsos, Huzefa Rangwala, George Karypis:
OpenTab: Advancing Large Language Models as Open-domain Table Reasoners. CoRR abs/2402.14361 (2024) - [i42]Jonathan Vasquez, Carlotta Domeniconi, Huzefa Rangwala:
DispaRisk: Assessing and Interpreting Disparity Risks in Datasets. CoRR abs/2405.12372 (2024) - [i41]Da Zheng, Xiang Song, Qi Zhu, Jiani Zhang, Theodore Vasiloudis, Runjie Ma, Houyu Zhang, Zichen Wang, Soji Adeshina, Israt Nisa, Alejandro Mottini, Qingjun Cui, Huzefa Rangwala, Belinda Zeng, Christos Faloutsos, George Karypis:
GraphStorm: all-in-one graph machine learning framework for industry applications. CoRR abs/2406.06022 (2024) - [i40]Jiaming Liang, Chuan Lei, Xiao Qin, Jiani Zhang, Asterios Katsifodimos, Christos Faloutsos, Huzefa Rangwala:
FeatNavigator: Automatic Feature Augmentation on Tabular Data. CoRR abs/2406.09534 (2024) - 2023
- [j29]Panneer Selvam Santhalingam
, Parth Pathak
, Huzefa Rangwala
, Jana Kosecka
:
Synthetic Smartwatch IMU Data Generation from In-the-wild ASL Videos. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 7(2): 74:1-74:34 (2023) - [c128]Tasfia Mashiat, Xavier Gitiaux, Huzefa Rangwala, Sanmay Das:
Counterfactually Fair Dynamic Assignment: A Case Study on Policing. AAMAS 2023: 2526-2528 - [c127]Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Shen Wang, Huzefa Rangwala, George Karypis:
NameGuess: Column Name Expansion for Tabular Data. EMNLP 2023: 13276-13290 - [c126]Mia C. Mayer
, Muhammad Bilal Zafar
, Luca Franceschi
, Huzefa Rangwala
:
Hands-on Tutorial: "Explanations in AI: Methods, Stakeholders and Pitfalls". KDD 2023: 5783-5785 - [c125]Jonathan Vasquez, Xavier Gitiaux, Huzefa Rangwala:
Estimating the Risk of Individual Discrimination of Classifiers. PAKDD (1) 2023: 495-506 - [e3]M. Emre Celebi
, Md Sirajus Salekin, Hyunwoo J. Kim
, Shadi Albarqouni
, Catarina Barata, Allan Halpern
, Philipp Tschandl, Marc Combalia, Yuan Liu, Ghada Zamzmi
, Joshua Levy, Huzefa Rangwala, Annika Reinke, Diya Wynn, Bennett A. Landman, Won-Ki Jeong, Yiqing Shen, Zhongying Deng, Spyridon Bakas
, Xiaoxiao Li
, Chen Qin
, Nicola Rieke, Holger Roth
, Daguang Xu
:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops - ISIC 2023, Care-AI 2023, MedAGI 2023, DeCaF 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8-12, 2023, Proceedings. Lecture Notes in Computer Science 14393, Springer 2023, ISBN 978-3-031-47400-2 [contents] - [i39]Hengrui Zhang, Jiani Zhang, Balasubramaniam Srinivasan, Zhengyuan Shen, Xiao Qin, Christos Faloutsos, Huzefa Rangwala, George Karypis:
Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space. CoRR abs/2310.09656 (2023) - [i38]Jiani Zhang, Zhengyuan Shen, Balasubramaniam Srinivasan, Shen Wang, Huzefa Rangwala, George Karypis:
NameGuess: Column Name Expansion for Tabular Data. CoRR abs/2310.13196 (2023) - [i37]Costas Mavromatis, Balasubramaniam Srinivasan, Zhengyuan Shen, Jiani Zhang, Huzefa Rangwala, Christos Faloutsos, George Karypis:
Which Examples to Annotate for In-Context Learning? Towards Effective and Efficient Selection. CoRR abs/2310.20046 (2023) - 2022
- [c124]Angeela Acharya, Siddhartha Sikdar, Sanmay Das, Huzefa Rangwala:
GenSyn: A Multi-stage Framework for Generating Synthetic Microdata using Macro Data Sources. IEEE Big Data 2022: 685-692 - [c123]Jitin Krishnan, Antonios Anastasopoulos, Hemant Purohit
, Huzefa Rangwala:
Cross-Lingual Text Classification of Transliterated Hindi and Malayalam. IEEE Big Data 2022: 1850-1857 - [c122]Sneha Mehta, Huzefa Rangwala, Naren Ramakrishnan:
Improving Zero-Shot Event Extraction via Sentence Simplification. CASE@EMNLP 2022: 32-43 - [c121]Tasfia Mashiat
, Xavier Gitiaux, Huzefa Rangwala, Patrick J. Fowler, Sanmay Das:
Trade-offs between Group Fairness Metrics in Societal Resource Allocation. FAccT 2022: 1095-1105 - [c120]Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Causality Enhanced Societal Event Forecasting With Heterogeneous Graph Learning. ICDM 2022: 91-100 - [c119]Xavier Gitiaux, Huzefa Rangwala:
SoFaiR: Single Shot Fair Representation Learning. IJCAI 2022: 687-695 - [c118]Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Robust Event Forecasting with Spatiotemporal Confounder Learning. KDD 2022: 294-304 - [c117]Zichen Wang, Vassilis N. Ioannidis, Huzefa Rangwala, Tatsuya Arai, Ryan Brand, Mufei Li, Yohei Nakayama:
Graph Neural Networks in Life Sciences: Opportunities and Solutions. KDD 2022: 4834-4835 - [c116]Jonathan Vasquez Verdugo
, Xavier Gitiaux, Cesar Ortega, Huzefa Rangwala:
FairEd: A Systematic Fairness Analysis Approach Applied in a Higher Educational Context. LAK 2022: 271-281 - [e2]Aidong Zhang, Huzefa Rangwala:
KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14 - 18, 2022. ACM 2022, ISBN 978-1-4503-9385-0 [contents] - [i36]Tasfia Mashiat, Xavier Gitiaux, Huzefa Rangwala, Patrick J. Fowler, Sanmay Das:
Trade-offs between Group Fairness Metrics in Societal Resource Allocation. CoRR abs/2202.12334 (2022) - [i35]Sneha Mehta, Huzefa Rangwala, Naren Ramakrishnan:
Improving Zero-Shot Event Extraction via Sentence Simplification. CoRR abs/2204.02531 (2022) - [i34]Xavier Gitiaux, Huzefa Rangwala:
SoFaiR: Single Shot Fair Representation Learning. CoRR abs/2204.12556 (2022) - [i33]Jonathan Vasquez Verdugo, Xavier Gitiaux, Huzefa Rangwala:
Ex-Ante Assessment of Discrimination in Dataset. CoRR abs/2208.07918 (2022) - [i32]Gil Sadeh, Zichen Wang, Jasleen Grewal, Huzefa Rangwala, Layne Price:
Training self-supervised peptide sequence models on artificially chopped proteins. CoRR abs/2211.06428 (2022) - [i31]Angeela Acharya, Siddhartha Sikdar, Sanmay Das, Huzefa Rangwala:
GenSyn: A Multi-stage Framework for Generating Synthetic Microdata using Macro Data Sources. CoRR abs/2212.05975 (2022) - 2021
- [c115]Xavier Gitiaux, Huzefa Rangwala:
Fair Representations by Compression. AAAI 2021: 11506-11515 - [c114]Xavier Gitiaux, Huzefa Rangwala:
Learning Smooth and Fair Representations. AISTATS 2021: 253-261 - [c113]Hui Zheng, Pattiya Mahapasuthanon
, Yujing Chen, Huzefa Rangwala, Anya S. Evmenova, Vivian Genaro Motti
:
WLA4ND: a Wearable Dataset of Learning Activities for Young Adults with Neurodiversity to Provide Support in Education. ASSETS 2021: 29:1-29:15 - [c112]Al Amin Hosain, Huzefa Rangwala, Jana Kosecká:
Improving Sign Video Modeling Using Graph Neural Network. IEEE BigData 2021: 4506-4513 - [c111]Yujing Chen, Zheng Chai, Yue Cheng, Huzefa Rangwala:
Asynchronous Federated Learning for Sensor Data with Concept Drift. IEEE BigData 2021: 4822-4831 - [c110]Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Understanding Event Predictions via Contextualized Multilevel Feature Learning. CIKM 2021: 342-351 - [c109]Anlan Du, Alexandra Plukis, Huzefa Rangwala:
Using Course Evaluations and Student Data to Predict Computer Science Student Success. EDM (Workshops) 2021 - [c108]Dom Huh, Huzefa Rangwala:
Synthetic Embedding-based Data Generation Methods for Student Performance. EDM (Workshops) 2021 - [c107]Ashish Hingle, Huzefa Rangwala, Aditya Johri, Alex Monea:
Using Role-Plays to Improve Ethical Understanding of Algorithms Among Computing Students. FIE 2021: 1-7 - [c106]Zheng Chai, Yujing Chen, Ali Anwar
, Liang Zhao, Yue Cheng, Huzefa Rangwala:
FedAT: a high-performance and communication-efficient federated learning system with asynchronous tiers. SC 2021: 60 - [c105]Al Amin Hosain, Panneer Selvam Santhalingam, Parth H. Pathak, Huzefa Rangwala, Jana Kosecká:
Hand Pose Guided 3D Pooling for Word-level Sign Language Recognition. WACV 2021: 3428-3438 - [i30]Jitin Krishnan, Antonios Anastasopoulos, Hemant Purohit, Huzefa Rangwala:
Multilingual Code-Switching for Zero-Shot Cross-Lingual Intent Prediction and Slot Filling. CoRR abs/2103.07792 (2021) - [i29]Xavier Gitiaux, Huzefa Rangwala:
Fair Representations by Compression. CoRR abs/2105.14044 (2021) - [i28]Jitin Krishnan, Antonios Anastasopoulos, Hemant Purohit, Huzefa Rangwala:
Cross-Lingual Text Classification of Transliterated Hindi and Malayalam. CoRR abs/2108.13620 (2021) - [i27]Yujing Chen, Zheng Chai, Yue Cheng, Huzefa Rangwala:
Asynchronous Federated Learning for Sensor Data with Concept Drift. CoRR abs/2109.00151 (2021) - [i26]Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Causal Knowledge Guided Societal Event Forecasting. CoRR abs/2112.05695 (2021) - 2020
- [j28]Mohammad Arifur Rahman, Huzefa Rangwala:
IDMIL: an alignment-free Interpretable Deep Multiple Instance Learning (MIL) for predicting disease from whole-metagenomic data. Bioinform. 36(Supplement-1): i39-i47 (2020) - [j27]Panneer Selvam Santhalingam, Al Amin Hosain, Ding Zhang, Parth H. Pathak, Huzefa Rangwala, Raja S. Kushalnagar:
mmASL: Environment-Independent ASL Gesture Recognition Using 60 GHz Millimeter-wave Signals. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4(1): 26:1-26:30 (2020) - [j26]Mohammad Arifur Rahman
, Nathan LaPierre, Huzefa Rangwala
:
Phenotype Prediction from Metagenomic Data Using Clustering and Assembly with Multiple Instance Learning (CAMIL). IEEE ACM Trans. Comput. Biol. Bioinform. 17(3): 828-840 (2020) - [c104]Yuanqi Du, Nguyen Dang, Riley Wilkerson, Parth H. Pathak, Huzefa Rangwala, Jana Kosecka:
American Sign Language Recognition Using an FMCW Wireless Sensor (Student Abstract). AAAI 2020: 13781-13782 - [c103]Jitin Krishnan, Patrick Coronado, Hemant Purohit, Huzefa Rangwala:
Common-Knowledge Concept Recognition for SEVA. AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering (1) 2020 - [c102]Jitin Krishnan, Hemant Purohit
, Huzefa Rangwala:
Unsupervised and Interpretable Domain Adaptation to Rapidly Filter Tweets for Emergency Services. ASONAM 2020: 409-416 - [c101]Yujing Chen, Yue Ning, Martin Slawski, Huzefa Rangwala:
Asynchronous Online Federated Learning for Edge Devices with Non-IID Data. IEEE BigData 2020: 15-24 - [c100]Songgaojun Deng, Shusen Wang, Huzefa Rangwala, Lijing Wang
, Yue Ning
:
Cola-GNN: Cross-location Attention based Graph Neural Networks for Long-term ILI Prediction. CIKM 2020: 245-254 - [c99]Al Amin Hosain, Panneer Selvam Santhalingam, Parth H. Pathak, Jana Kosecká, Huzefa Rangwala:
Body Pose and Deep Hand-shape Feature Based American Sign Language Recognition. DSAA 2020: 207-215 - [c98]Qian Hu, Huzefa Rangwala:
Towards Fair Educational Data Mining: A Case Study on Detecting At-risk Students. EDM 2020 - [c97]Noah Hunt-Isaak, Peter Cherniavsky, Mark Snyder, Huzefa Rangwala:
Using online text books and in-class quizzes to predict in class performance. EDM 2020 - [c96]Al Amin Hosain, Panneer Selvam Santhalingam, Parth H. Pathak, Huzefa Rangwala, Jana Kosecká:
FineHand: Learning Hand Shapes for American Sign Language Recognition. FG 2020: 700-707 - [c95]Qian Hu, Huzefa Rangwala:
Metric-Free Individual Fairness with Cooperative Contextual Bandits. ICDM 2020: 182-191 - [c94]Yujing Chen, Yue Ning, Zheng Chai, Huzefa Rangwala:
Federated Multi-task Learning with Hierarchical Attention for Sensor Data Analytics. IJCNN 2020: 1-8 - [c93]Jitin Krishnan, Hemant Purohit, Huzefa Rangwala:
Attention Realignment and Pseudo-Labelling for Interpretable Cross-Lingual Classification of Crisis Tweets. KiML@KDD 2020: 43-50 - [c92]Songgaojun Deng, Huzefa Rangwala, Yue Ning:
Dynamic Knowledge Graph based Multi-Event Forecasting. KDD 2020: 1585-1595 - [c91]Jitin Krishnan, Hemant Purohit
, Huzefa Rangwala:
Diversity-Based Generalization for Unsupervised Text Classification Under Domain Shift. ECML/PKDD (2) 2020: 657-672 - [c90]Angeela Acharya, Jitin Krishnan, Desmond Arias, Huzefa Rangwala:
Homicidal Event Forecasting and Interpretable Analysis Using Hierarchical Attention Model. SBP-BRiMS 2020: 140-150 - [c89]Panneer Selvam Santhalingam, Yuanqi Du, Riley Wilkerson, Al Amin Hosain, Ding Zhang, Parth H. Pathak, Huzefa Rangwala, Raja S. Kushalnagar:
Expressive ASL Recognition using Millimeter-wave Wireless Signals. SECON 2020: 1-9 - [i25]Qian Hu, Huzefa Rangwala:
Academic Performance Estimation with Attention-based Graph Convolutional Networks. CoRR abs/2001.00632 (2020) - [i24]Jitin Krishnan, Hemant Purohit, Huzefa Rangwala:
Diversity-Based Generalization for Neural Unsupervised Text Classification under Domain Shift. CoRR abs/2002.10937 (2020) - [i23]Jitin Krishnan, Hemant Purohit, Huzefa Rangwala:
Unsupervised and Interpretable Domain Adaptation to Rapidly Filter Social Web Data for Emergency Services. CoRR abs/2003.04991 (2020) - [i22]Dom Huh, Sai Gurrapu, Frederick Olson, Huzefa Rangwala, Parth H. Pathak, Jana Kosecka:
Generative Multi-Stream Architecture For American Sign Language Recognition. CoRR abs/2003.08743 (2020) - [i21]Al Amin Hosain, Panneer Selvam Santhalingam, Parth H. Pathak, Huzefa Rangwala, Jana Kosecka:
FineHand: Learning Hand Shapes for American Sign Language Recognition. CoRR abs/2003.08753 (2020) - [i20]Jitin Krishnan, Patrick Coronado, Hemant Purohit, Huzefa Rangwala:
Common-Knowledge Concept Recognition for SEVA. CoRR abs/2003.11687 (2020) - [i19]Xavier Gitiaux, Huzefa Rangwala:
Learning Smooth and Fair Representations. CoRR abs/2006.08788 (2020) - [i18]Zheng Chai, Yujing Chen, Liang Zhao, Yue Cheng, Huzefa Rangwala:
FedAT: A Communication-Efficient Federated Learning Method with Asynchronous Tiers under Non-IID Data. CoRR abs/2010.05958 (2020) - [i17]Qian Hu, Huzefa Rangwala:
Metric-Free Individual Fairness with Cooperative Contextual Bandits. CoRR abs/2011.06738 (2020)
2010 – 2019
- 2019
- [j25]Carrie Klein
, Jaime Lester, Huzefa Rangwala, Aditya Johri:
Technological barriers and incentives to learning analytics adoption in higher education: insights from users. J. Comput. High. Educ. 31(3): 604-625 (2019) - [j24]Azad Naik
, Huzefa Rangwala:
Improving large-scale hierarchical classification by rewiring: a data-driven filter based approach. J. Intell. Inf. Syst. 52(1): 141-164 (2019) - [c88]Yujing Chen, Huzefa Rangwala:
Attention-based Multi-task Learning for Sensor Analytics. IEEE BigData 2019: 2187-2196 - [c87]Zhiyun Ren, Xia Ning, Andrew S. Lan, Huzefa Rangwala:
Grade Prediction with Neural Collaborative Filtering. DSAA 2019: 1-10 - [c86]Al Amin Hosain, Panneer Selvam Santhalingam, Parth H. Pathak, Jana Kosecká, Huzefa Rangwala:
Sign Language Recognition Analysis using Multimodal Data. DSAA 2019: 203-210 - [c85]Qian Hu, Huzefa Rangwala:
Academic Performance Estimation with Attention-based Graph Convolutional Networks. EDM 2019 - [c84]Zhiyun Ren, Xia Ning, Andrew S. Lan, Huzefa Rangwala:
Grade Prediction Based on Cumulative Knowledge and Co-taken Courses. EDM 2019 - [c83]Justin Alvin, Bob Kurtz, Paul Ammann, Huzefa Rangwala, René Just:
Guiding testing effort using mutant utility. ICSE (Companion Volume) 2019: 312-313 - [c82]Xavier Gitiaux, Huzefa Rangwala:
mdfa: Multi-Differential Fairness Auditor for Black Box Classifiers. IJCAI 2019: 5871-5879 - [c81]Songgaojun Deng, Huzefa Rangwala, Yue Ning
:
Learning Dynamic Context Graphs for Predicting Social Events. KDD 2019: 1007-1016 - [c80]Yue Ning, Liang Zhao, Feng Chen, Chang-Tien Lu
, Huzefa Rangwala:
Spatio-temporal Event Forecasting and Precursor Identification. KDD 2019: 3237-3238 - [c79]David C. Anastasiu
, Huzefa Rangwala, Andrea Tagarelli:
Tutorial: Are You My Neighbor?: Bringing Order to Neighbor Computing Problems. KDD 2019: 3241-3242 - [c78]Qian Hu, Huzefa Rangwala:
Reliable Deep Grade Prediction with Uncertainty Estimation. LAK 2019: 76-85 - [c77]Sneha Mehta, Mohammad Raihanul Islam, Huzefa Rangwala, Naren Ramakrishnan
:
Event Detection using Hierarchical Multi-Aspect Attention. WWW 2019: 3079-3085 - [i16]Qian Hu, Huzefa Rangwala:
Reliable Deep Grade Prediction with Uncertainty Estimation. CoRR abs/1902.10213 (2019) - [i15]Xavier Gitiaux, Huzefa Rangwala:
Multi-Differential Fairness Auditor for Black Box Classifiers. CoRR abs/1903.07609 (2019) - [i14]Yujing Chen, Yue Ning, Zheng Chai, Huzefa Rangwala:
Federated Multi-task Hierarchical Attention Model for Sensor Analytics. CoRR abs/1905.05142 (2019) - [i13]Al Amin Hosain, Panneer Selvam Santhalingam, Parth H. Pathak, Jana Kosecka, Huzefa Rangwala:
Sign Language Recognition Analysis using Multimodal Data. CoRR abs/1909.11232 (2019) - [i12]Yujing Chen, Yue Ning, Huzefa Rangwala:
Asynchronous Online Federated Learning for Edge Devices. CoRR abs/1911.02134 (2019) - [i11]Sneha Mehta, Huzefa Rangwala, Naren Ramakrishnan:
Low Rank Factorization for Compact Multi-Head Self-Attention. CoRR abs/1912.00835 (2019) - [i10]Songgaojun Deng, Shusen Wang, Huzefa Rangwala, Lijing Wang, Yue Ning:
Graph Message Passing with Cross-location Attentions for Long-term ILI Prediction. CoRR abs/1912.10202 (2019) - 2018
- [b1]Azad Naik, Huzefa Rangwala:
Large Scale Hierarchical Classification: State of the Art. Springer Briefs in Computer Science, Springer 2018, ISBN 978-3-030-01619-7, pp. 1-93 - [j23]Omaima Almatrafi
, Aditya Johri, Huzefa Rangwala:
Needle in a haystack: Identifying learner posts that require urgent response in MOOC discussion forums. Comput. Educ. 118: 1-9 (2018) - [c76]Li Zhang, Huzefa Rangwala:
Early Identification of At-Risk Students Using Iterative Logistic Regression. AIED (1) 2018: 613-626 - [c75]Yue Ning
, Sathappan Muthiah, Naren Ramakrishnan
, Huzefa Rangwala, David Mares:
When do Crowds Turn Violent? Uncovering Triggers from Media. ASONAM 2018: 77-82 - [c74]Mohammad Arifur Rahman, Huzefa Rangwala:
RegMIL: Phenotype Classification from Metagenomic Data. BCB 2018: 145-154 - [c73]Ananya S. Dhawan, Jana Kosecka, Huzefa Rangwala, Siddhartha Sikdar
:
An intuitive muscle-computer interface using ultrasound sensing and Markovian state transitions. ISBI 2018: 1191-1194 - [c72]Yujing Chen, Aditya Johri, Huzefa Rangwala:
Running out of STEM: a comparative study across STEM majors of college students at-risk of dropping out early. LAK 2018: 270-279 - [c71]Qian Hu, Huzefa Rangwala:
Course-Specific Markovian Models for Grade Prediction. PAKDD (2) 2018: 29-41 - [c70]Nasrin Akhter, Liang Zhao, Desmond Arias, Huzefa Rangwala, Naren Ramakrishnan
:
Forecasting Gang Homicides with Multi-level Multi-task Learning. SBP-BRiMS 2018: 28-37 - [c69]Sneha Nagpaul, Huzefa Rangwala:
From Language to Location Using Multiple Instance Neural Networks. SBP-BRiMS 2018: 46-53 - [c68]Yue Ning
, Rongrong Tao, Chandan K. Reddy
, Huzefa Rangwala, James C. Starz, Naren Ramakrishnan
:
STAPLE: Spatio-Temporal Precursor Learning for Event Forecasting. SDM 2018: 99-107 - [c67]Zhiyun Ren, Xia Ning, Huzefa Rangwala:
ALE: Additive Latent Effect Models for Grade Prediction. SDM 2018: 477-485 - [r1]Tanwistha Saha, Huzefa Rangwala, Carlotta Domeniconi:
Relational Network Classification and Its Applications in Recommender Systems. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - [i9]Zhiyun Ren, Xia Ning, Huzefa Rangwala:
ALE: Additive Latent Effect Models for Grade Prediction. CoRR abs/1801.05535 (2018) - 2017
- [j22]Azad Naik
, Huzefa Rangwala:
HierFlat: flattened hierarchies for improving top-down hierarchical classification. Int. J. Data Sci. Anal. 4(3): 191-208 (2017) - [j21]Mohammad Arifur Rahman, Nathan Lapierre, Huzefa Rangwala, Daniel Barbará:
Metagenome sequence clustering with hash-based canopies. J. Bioinform. Comput. Biol. 15(6): 1740006:1-1740006:18 (2017) - [c66]Qian Hu, Agoritsa Polyzou
, George Karypis
, Huzefa Rangwala:
Enriching Course-Specific Regression Models with Content Features for Grade Prediction. DSAA 2017: 504-513 - [c65]Zhiyun Ren, Xia Ning, Huzefa Rangwala:
Grade Prediction with Temporal Course-wise Influence. EDM 2017 - [c64]Qingzhe Li, Jessica Lin, Liang Zhao, Huzefa Rangwala:
A Uniform Representation for Trajectory Learning Tasks. SIGSPATIAL/GIS 2017: 80:1-80:4 - [c63]Yifeng Gao, Jessica Lin, Huzefa Rangwala:
IterativE Grammar-Based Framework for Discovering Variable-Length Time Series Motifs. ICDM 2017: 111-116 - [c62]Azad Naik, Huzefa Rangwala:
Integrated Framework for Improving Large-Scale Hierarchical Classification. ICMLA 2017: 281-288 - [c61]Jeff Offutt, Paul Ammann, Kinga Dobolyi, Chris Kauffmann, Jaime Lester, Upsorn Praphamontripong, Huzefa Rangwala, Sanjeev Setia, Pearl Y. Wang, Liz White:
A Novel Self-Paced Model for Teaching Programming. L@S 2017: 177-180 - [c60]Yifeng Gao, Qingzhe Li, Xiaosheng Li, Jessica Lin, Huzefa Rangwala:
TrajViz: A Tool for Visualizing Patterns and Anomalies in Trajectory. ECML/PKDD (3) 2017: 428-431 - [c59]Yue Ning
, Yue Shi, Liangjie Hong, Huzefa Rangwala, Naren Ramakrishnan
:
A Gradient-based Adaptive Learning Framework for Efficient Personal Recommendation. RecSys 2017: 23-31 - [i8]Azad Naik, Huzefa Rangwala:
Inconsistent Node Flattening for Improving Top-down Hierarchical Classification. CoRR abs/1706.01214 (2017) - [i7]Azad Naik, Huzefa Rangwala:
Embedding Feature Selection for Large-scale Hierarchical Classification. CoRR abs/1706.01581 (2017) - [i6]Azad Naik, Anveshi Charuvaka, Huzefa Rangwala:
Classifying Documents within Multiple Hierarchical Datasets using Multi-Task Learning. CoRR abs/1706.01583 (2017) - [i5]Zhiyun Ren, Xia Ning, Huzefa Rangwala:
Grade Prediction with Temporal Course-wise Influence. CoRR abs/1709.05433 (2017) - 2016
- [j20]Azad Naik, Huzefa Rangwala:
Large-scale hierarchical classification with rare categories and inconsistencies. AI Matters 2(3): 27-29 (2016) - [j19]Asmaa Elbadrawy, Agoritsa Polyzou
, Zhiyun Ren, Mackenzie Sweeney, George Karypis
, Huzefa Rangwala:
Predicting Student Performance Using Personalized Analytics. Computer 49(4): 61-69 (2016) - [j18]Nima Akhlaghi, Clayton A. Baker
, Mohamed Lahlou, Hozaifah Zafar, Karthik G. Murthy, Huzefa Rangwala, Jana Kosecka, Wilsaan M. Joiner, Joseph J. Pancrazio
, Siddhartha Sikdar
:
Real-Time Classification of Hand Motions Using Ultrasound Imaging of Forearm Muscles. IEEE Trans. Biomed. Eng. 63(8): 1687-1698 (2016) - [c58]Nathan LaPierre, Mohammad Arifur Rahman, Huzefa Rangwala:
CAMIL: Clustering and Assembly with Multiple Instance Learning for phenotype prediction. BIBM 2016: 33-40 - [c57]Azad Naik, Huzefa Rangwala:
Embedding feature selection for large-scale hierarchical classification. IEEE BigData 2016: 1212-1221 - [c56]Wei Wang, Yue Ning
, Huzefa Rangwala, Naren Ramakrishnan
:
A Multiple Instance Learning Framework for Identifying Key Sentences and Detecting Events. CIKM 2016: 509-518 - [c55]Azad Naik, Huzefa Rangwala:
Inconsistent Node Flattening for Improving Top-Down Hierarchical Classification. DSAA 2016: 379-388 - [c54]Mack Sweeney, Jaime Lester, Huzefa Rangwala, Aditya Johri:
Next-Term Student Performance Prediction: A Recommender Systems Approach. EDM 2016: 7 - [c53]Zhiyun Ren, Huzefa Rangwala, Aditya Johri:
Predicting Performance on MOOC Assessments using Multi-Regression Models. EDM 2016: 484-489 - [c52]Clayton A. Baker
, Nima Akhlaghi, Huzefa Rangwala, Jana Kosecká, Siddhartha Sikdar
:
Real-time, ultrasound-based control of a virtual hand by a trans-radial amputee. EMBC 2016: 3219-3222 - [c51]Yifeng Gao, Jessica Lin, Huzefa Rangwala:
Iterative Grammar-Based Framework for Discovering Variable-Length Time Series Motifs. ICMLA 2016: 7-12 - [c50]Yue Ning
, Sathappan Muthiah, Huzefa Rangwala, Naren Ramakrishnan
:
Modeling Precursors for Event Forecasting via Nested Multi-Instance Learning. KDD 2016: 1095-1104 - [c49]Omaima Almatrafi, Huzefa Rangwala, Aditya Johri, Jaime Lester:
Using Learning Analytics to Trace Academic Trajectories of CS and IT Students to Better Understanding Successful Pathways to Graduation (Abstract Only). SIGCSE 2016: 691 - [i4]Yue Ning, Sathappan Muthiah, Huzefa Rangwala, Naren Ramakrishnan:
Modeling Precursors for Event Forecasting via Nested Multi-Instance Learning. CoRR abs/1602.08033 (2016) - [i3]Azad Naik, Huzefa Rangwala:
Filter based Taxonomy Modification for Improving Hierarchical Classification. CoRR abs/1603.00772 (2016) - [i2]Mack Sweeney, Huzefa Rangwala, Jaime Lester, Aditya Johri:
Next-Term Student Performance Prediction: A Recommender Systems Approach. CoRR abs/1604.01840 (2016) - [i1]Zhiyun Ren, Huzefa Rangwala, Aditya Johri:
Predicting Performance on MOOC Assessments using Multi-Regression Models. CoRR abs/1605.02269 (2016) - 2015
- [j17]Nuttachat Wisittipanit, Huzefa Rangwala, Masoumeh Sikaroodi, Ali Keshavarzian, Ece A. Mutlu, Patrick Gillevet:
Classification methods for the analysis of LH-PCR data associated with inflammatory bowel disease patients. Int. J. Bioinform. Res. Appl. 11(2): 111-129 (2015) - [j16]Guo-Xian Yu, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zili Zhang:
Predicting Protein Function Using Multiple Kernels. IEEE ACM Trans. Comput. Biol. Bioinform. 12(1): 219-233 (2015) - [c48]Mack Sweeney, Jaime Lester, Huzefa Rangwala:
Next-term student grade prediction. IEEE BigData 2015: 970-975 - [c47]Azad Naik, Huzefa Rangwala:
A ranking-based approach for hierarchical classification. DSAA 2015: 1-10 - [c46]Nathan LaPierre, Huzefa Rangwala:
Predicting Clinical Phenotype Using OTU-Based Metagenome Representation. ICDM Workshops 2015: 156-163 - [c45]Jean Michel Rouly, Huzefa Rangwala, Aditya Johri:
What Are We Teaching?: Automated Evaluation of CS Curricula Content Using Topic Modeling. ICER 2015: 189-197 - [c44]Xing Wang, Yifeng Gao, Jessica Lin, Huzefa Rangwala, Ranjeev Mittu:
A Machine Learning Approach to False Alarm Detection for Critical Arrhythmia Alarms. ICMLA 2015: 202-207 - [c43]Anvardh Nanduri, Huzefa Rangwala:
Predicting New Friendships in Social Networks. ICMLA 2015: 521-526 - [c42]Nikhil Muralidhar, Huzefa Rangwala, Eui-Hong Sam Han:
Recommending Temporally Relevant News Content from Implicit Feedback Data. ICTAI 2015: 689-696 - [c41]Anveshi Charuvaka, Huzefa Rangwala:
HierCost: Improving Large Scale Hierarchical Classification with Cost Sensitive Learning. ECML/PKDD (1) 2015: 675-690 - [c40]Anveshi Charuvaka, Huzefa Rangwala:
Approximate block coordinate descent for large scale hierarchical classification. SAC 2015: 837-844 - [c39]Tanwistha Saha, Huzefa Rangwala, Carlotta Domeniconi:
Predicting Preference Tags to Improve Item Recommendation. SDM 2015: 864-872 - 2014
- [j15]Guo-Xian Yu, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zhiwen Yu:
Erratum to "Protein Function Prediction Using Multilabel Ensemble Classification". IEEE ACM Trans. Comput. Biol. Bioinform. 11(1): 265 (2014) - [j14]Guo-Xian Yu, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zhiwen Yu:
Protein Function Prediction withIncomplete Annotations. IEEE ACM Trans. Comput. Biol. Bioinform. 11(3): 579-591 (2014) - [j13]Gaurav Pandey, Huzefa Rangwala:
Guest Editorial for Special Section on BIOKDD2013. IEEE ACM Trans. Comput. Biol. Bioinform. 11(5): 773-774 (2014) - [j12]Anveshi Charuvaka
, Huzefa Rangwala:
Classifying Protein Sequences Using Regularized Multi-Task Learning. IEEE ACM Trans. Comput. Biol. Bioinform. 11(6): 1087-1098 (2014) - [c38]Anveshi Charuvaka, Huzefa Rangwala:
Convex multi-task relationship learning using hinge loss. CIDM 2014: 63-70 - [c37]Tanwistha Saha, Huzefa Rangwala, Carlotta Domeniconi:
FLIP: Active Learning for Relational Network Classification. ECML/PKDD (3) 2014: 1-18 - [c36]Huzefa Rangwala, Anveshi Charuvaka, Zeehasham Rasheed:
Machine Learning Approaches for Metagenomics. ECML/PKDD (3) 2014: 512-515 - 2013
- [j11]Zeehasham Rasheed, Huzefa Rangwala, Daniel Barbará:
16S rRNA metagenome clustering and diversity estimation using locality sensitive hashing. BMC Syst. Biol. 7(S-4): S11 (2013) - [j10]Sharath Hiremagalore, Chen Liang, Angelos Stavrou
, Huzefa Rangwala:
Improving network response times using social information. Soc. Netw. Anal. Min. 3(2): 209-220 (2013) - [j9]Guo-Xian Yu, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zhiwen Yu:
Protein Function Prediction Using Multilabel Ensemble Classification. IEEE ACM Trans. Comput. Biol. Bioinform. 10(4): 1045-1057 (2013) - [c35]Azad Naik, Anveshi Charuvaka, Huzefa Rangwala:
Classifying Documents within Multiple Hierarchical Datasets Using Multi-task Learning. ICTAI 2013: 390-397 - [c34]Guo-Xian Yu, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zili Zhang:
Protein Function Prediction by Integrating Multiple Kernels. IJCAI 2013: 1869-1875 - [c33]Zeehasham Rasheed, Huzefa Rangwala:
A Map-Reduce Framework for Clustering Metagenomes. IPDPS Workshops 2013: 549-558 - [c32]Sam Blasiak, Huzefa Rangwala, Kathryn B. Laskey:
Relevant Subsequence Detection with Sparse Dictionary Learning. ECML/PKDD (1) 2013: 401-416 - [c31]Guo-Xian Yu, Carlotta Domeniconi, Huzefa Rangwala, Guoji Zhang:
Protein Function Prediction Using Dependence Maximization. ECML/PKDD (1) 2013: 574-589 - [c30]Tanwistha Saha, Huzefa Rangwala, Carlotta Domeniconi:
Sparsification and Sampling of Networks for Collective Classification. SBP 2013: 293-302 - [c29]Samuel J. Blasiak, Huzefa Rangwala, Sithu Sudarsan:
Joint Segmentation and Clustering in Text Corpuses. SDM 2013: 485-493 - [c28]Huzefa Rangwala, Zeehasham Rasheed:
MC-MinH: Metagenome Clustering using Minwise based Hashing. SDM 2013: 677-685 - [e1]Gaurav Pandey, Huzefa Rangwala, George Karypis, Jake Yue Chen, Mohammed Javeed Zaki:
Proceedings of the 12th International Workshop on Data Mining in Bioinformatics, BioKDD 2013, Chicago, IL, USA, August 11, 2013. ACM 2013, ISBN 978-1-4503-2327-7 [contents] - 2012
- [j8]Zeehasham Rasheed, Huzefa Rangwala:
Metagenomic Taxonomic Classification Using Extreme Learning Machines. J. Bioinform. Comput. Biol. 10(5) (2012) - [c27]Guo-Xian Yu, Guoji Zhang, Huzefa Rangwala, Carlotta Domeniconi, Zhiwen Yu:
Protein function prediction using weak-label learning. BCB 2012: 202-209 - [c26]Zeehasham Rasheed, Huzefa Rangwala, Daniel Barbará:
LSH-Div: Species diversity estimation using locality sensitive hashing. BIBM 2012: 1-6 - [c25]Zeehasham Rasheed, Huzefa Rangwala, Patrick Gillevet:
Classification and clustering in metagenomics with unified data management and computational framework. BIBM Workshops 2012: 965-967 - [c24]Anveshi Charuvaka, Huzefa Rangwala:
Multi-task Learning for Classifying Proteins Using Dual Hierarchies. ICDM 2012: 834-839 - [c23]Tanwistha Saha, Huzefa Rangwala, Carlotta Domeniconi:
Multi-label Collective Classification Using Adaptive Neighborhoods. ICMLA (1) 2012: 427-432 - [c22]Guo-Xian Yu, Carlotta Domeniconi, Huzefa Rangwala, Guoji Zhang, Zhiwen Yu:
Transductive multi-label ensemble classification for protein function prediction. KDD 2012: 1077-1085 - [c21]Chaitanya Yavvari, Arnur G. Tokhtabayev, Huzefa Rangwala, Angelos Stavrou
:
Malware Characterization Using Behavioral Components. MMM-ACNS 2012: 226-239 - [c20]Pu Wang, Carlotta Domeniconi, Huzefa Rangwala, Kathryn B. Laskey:
Feature Enriched Nonparametric Bayesian Co-clustering. PAKDD (1) 2012: 517-529 - [c19]Sam Blasiak, Huzefa Rangwala, Kathryn B. Laskey:
A Family of Feed-Forward Models for Protein Sequence Classification. ECML/PKDD (2) 2012: 419-434 - [c18]Samuel J. Blasiak, Huzefa Rangwala, Kathryn B. Laskey:
Beam Methods for the Profile Hidden Markov Model. SDM 2012: 331-342 - [c17]Zeehasham Rasheed, Huzefa Rangwala, Daniel Barbará:
Efficient Clustering of Metagenomic Sequences using Locality Sensitive Hashing. SDM 2012: 1023-1034 - 2011
- [c16]Chen Liang, Sharath Hiremagalore, Angelos Stavrou
, Huzefa Rangwala:
Predicting Network Response Times Using Social Information. ASONAM 2011: 527-531 - [c15]Zeehasham Rasheed, Huzefa Rangwala:
TAC-ELM: Metagenomic Taxonomic Classification with Extreme Learning Machines. BICoB 2011: 92-97 - [c14]Sheng Li, Huzefa Rangwala:
An Information Theoretic Approach for the Analysis of RNA and DNA Binding Sites. BICoB 2011: 184-189 - [c13]Nuttachat Wisittipanit, Huzefa Rangwala, Masoumeh Sikaroodi, Ali Keshavarzian, Ece A. Mutlu, Patrick Gillevet:
Profiling Microbial Communities using SSU rRNA Sequence and LH-PCR Data. BICoB 2011: 190-195 - [c12]Syed Faraz Mahmood, Huzefa Rangwala:
GPU-Euler: Sequence Assembly Using GPGPU. HPCC 2011: 153-160 - [c11]Nuttachat Wisittipanit, Huzefa Rangwala, Patrick Gillevet:
Analysis of Microbiome Data across Inflammatory Bowel Disease Patients. ICMLA (2) 2011: 200-205 - [c10]Sam Blasiak, Huzefa Rangwala:
A Hidden Markov Model Variant for Sequence Classification. IJCAI 2011: 1192-1197 - [c9]Tanwistha Saha, Carlotta Domeniconi, Huzefa Rangwala:
Detection of Communities and Bridges in Weighted Networks. MLDM 2011: 584-598 - 2010
- [j7]Huzefa Rangwala, Salman Jamali:
Defining a Coparticipation Network Using Comments on Digg. IEEE Intell. Syst. 25(4): 36-45 (2010) - [j6]Rezwan Ahmed, Huzefa Rangwala, George Karypis
:
Toptmh: Topology Predictor for transmembrane alpha-helices. J. Bioinform. Comput. Biol. 8(1): 39-57 (2010) - [c8]Anveshi Charuvaka, Huzefa Rangwala:
Evaluation of short read metagenomic assembly. BIBM 2010: 171-178 - [c7]Huzefa Rangwala:
Multiple Kernel Learning for Fold Recognition. BICoB 2010: 7-12 - [c6]Huzefa Rangwala, Salman Jamali:
Co-Participation Networks Using Comment Information. ICWSM 2010
2000 – 2009
- 2009
- [j5]Huzefa Rangwala, Christopher Kauffman, George Karypis
:
svmPRAT: SVM-based Protein Residue Annotation Toolkit. BMC Bioinform. 10: 439 (2009) - [j4]Xia Ning, Huzefa Rangwala, George Karypis
:
Multi-Assay-Based Structure-Activity Relationship Models: Improving Structure-Activity Relationship Models by Incorporating Activity Information from Related Targets. J. Chem. Inf. Model. 49(11): 2444-2456 (2009) - [c5]Huzefa Rangwala, Christopher Kauffman, George Karypis:
A Kernel Framework for Protein Residue Annotation. PAKDD 2009: 439-451 - 2008
- [c4]Huzefa Rangwala, George Karypis:
fRMSDAlign: Protein Sequence Alignment Using Predicted Local Structure Information for Pairs with Low Sequence Identity. APBC 2008: 111-122 - [c3]Ruinan Zhang, Huzefa Rangwala, George Karypis
:
Genome Alignments Using MPI-LAGAN. BIBM 2008: 437-440 - [c2]Rezwan Ahmed, Huzefa Rangwala, George Karypis:
TOPTMH: Topology Predictor for Transmembrane alpha-Helices. ECML/PKDD (1) 2008: 23-38 - 2007
- [j3]Huzefa Rangwala, George Karypis
:
Incremental window-based protein sequence alignment algorithms. Bioinform. 23(2): 17-23 (2007) - 2006
- [j2]Huzefa Rangwala, George Karypis
:
Building multiclass classifiers for remote homology detection and fold recognition. BMC Bioinform. 7: 455 (2006) - 2005
- [j1]Huzefa Rangwala, George Karypis
:
Profile-based direct kernels for remote homology detection and fold recognition. Bioinform. 21(23): 4239-4247 (2005) - [c1]Benjamin W. Mayer, Huzefa Rangwala, Rohit Gupta, Jaideep Srivastava, George Karypis, Vipin Kumar, Piet C. de Groen:
Feature Mining for Prediction of Degree of Liver Fibrosis. AMIA 2005
Coauthor Index
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