2025
Optimal large-scale stochastic optimization of NDCG surrogates for deep learning.
Mach. Learn., January, 2025
2024
Guest Editorial: AutoML for Nonstationary Data.
IEEE Trans. Artif. Intell., June, 2024
Transfer and share: semi-supervised learning from long-tailed data.
Mach. Learn., April, 2024
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization.
J. Mach. Learn. Res., 2024
A Survey on Self-play Methods in Reinforcement Learning.
CoRR, 2024
MQE: Unleashing the Power of Interaction with Multi-agent Quadruped Environment.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024
Efficient Stochastic Approximation of Minimax Excess Risk Optimization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
LLMArena: Assessing Capabilities of Large Language Models in Dynamic Multi-Agent Environments.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
Safe Abductive Learning in the Presence of Inaccurate Rules.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
DGPO: Discovering Multiple Strategies with Diversity-Guided Policy Optimization.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
Robust sliding mode control for a class of nonlinear systems through dual-layer sliding mode scheme.
J. Frankl. Inst., September, 2023
Improved robust reduced-order sliding mode fault-tolerant control for T-S fuzzy systems with disturbances.
Fuzzy Sets Syst., July, 2023
OpenRL: A Unified Reinforcement Learning Framework.
CoRR, 2023
Robustness and Generalizability of Deepfake Detection: A Study with Diffusion Models.
CoRR, 2023
Diverse Policies Converge in Reward-free Markov Decision Processe.
CoRR, 2023
Efficient Stochastic Approximation of Minimax Excess Risk Optimization.
CoRR, 2023
Automated 3D Pre-Training for Molecular Property Prediction.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization.
Proceedings of the International Conference on Machine Learning, 2023
Learning Graph-Enhanced Commander-Executor for Multi-Agent Navigation.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023
TiZero: Mastering Multi-Agent Football with Curriculum Learning and Self-Play.
Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, 2023
2022
Codabench: Flexible, easy-to-use, and reproducible meta-benchmark platform.
Patterns, 2022
Online strongly convex optimization with unknown delays.
Mach. Learn., 2022
Projection-free Distributed Online Learning with Sublinear Communication Complexity.
J. Mach. Learn. Res., 2022
Bridging the Gap of AutoGraph Between Academia and Industry: Analyzing AutoGraph Challenge at KDD Cup 2020.
Frontiers Artif. Intell., 2022
Online Frank-Wolfe with Unknown Delays.
CoRR, 2022
Bridging the Gap of AutoGraph between Academia and Industry: Analysing AutoGraph Challenge at KDD Cup 2020.
CoRR, 2022
Graph Neural Networks for Double-Strand DNA Breaks Prediction.
CoRR, 2022
Robust model selection for positive and unlabeled learning with constraints.
Sci. China Inf. Sci., 2022
Strongly adaptive online learning over partial intervals.
Sci. China Inf. Sci., 2022
LTU Attacker for Membership Inference.
Algorithms, 2022
Translation-Based Implicit Annotation Projection for Zero-Shot Cross-Lingual Event Argument Extraction.
Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022
Diverse Policies Converge in Reward-Free Markov Decision Processes.
Proceedings of the PRICAI 2023: Trends in Artificial Intelligence, 2022
Online Frank-Wolfe with Arbitrary Delays.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
VSM: A Versatile Semi-supervised Model for Multi-modal Cell Instance Segmentation.
Proceedings of The Cell Segmentation Challenge in Multi-modality High-Resolution Microscopy Images, 2022
Multiple Temporal Fusion based Weakly-supervised Pre-training Techniques for Video Categorization.
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022
2021
Guest Editorial: Automated Machine Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2021
Optimal ϵ -stealthy attack in cyber-physical systems.
J. Frankl. Inst., 2021
Codabench: Flexible, Easy-to-Use and Reproducible Benchmarking for Everyone.
CoRR, 2021
Robust Long-Tailed Learning under Label Noise.
CoRR, 2021
TabGNN: Multiplex Graph Neural Network for Tabular Data Prediction.
CoRR, 2021
AutoML Meets Time Series Regression Design and Analysis of the AutoSeries Challenge.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track, 2021
Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
OmniPrint: A Configurable Printed Character Synthesizer.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021
Towards Robust Prediction on Tail Labels.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
Task-wise Split Gradient Boosting Trees for Multi-center Diabetes Prediction.
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Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021
Auto-KWS 2021 Challenge: Task, Datasets, and Baselines.
Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021
Search to aggregate neighborhood for graph neural network.
Proceedings of the 37th IEEE International Conference on Data Engineering, 2021
Understanding Social Behavior in Dyadic and Small Group Interactions: Preface.
Proceedings of the ChaLearn LAP Challenge on Understanding Social Behavior in Dyadic and Small Group Interactions, 2021
ChaLearn LAP Challenges on Self-Reported Personality Recognition and Non-Verbal Behavior Forecasting During Social Dyadic Interactions: Dataset, Design, and Results.
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Proceedings of the ChaLearn LAP Challenge on Understanding Social Behavior in Dyadic and Small Group Interactions, 2021
Comparison of Spatio-Temporal Models for Human Motion and Pose Forecasting in Face-to-Face Interaction Scenarios.
Proceedings of the ChaLearn LAP Challenge on Understanding Social Behavior in Dyadic and Small Group Interactions, 2021
Didn't see that coming: a survey on non-verbal social human behavior forecasting.
Proceedings of the ChaLearn LAP Challenge on Understanding Social Behavior in Dyadic and Small Group Interactions, 2021
Explanation Consistency Training: Facilitating Consistency-Based Semi-Supervised Learning with Interpretability.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction.
Proceedings of the Federated Learning - Privacy and Incentive, 2020
Towards automated computer vision: analysis of the AutoCV challenges 2019.
Pattern Recognit. Lett., 2020
MixPUL: Consistency-based Augmentation for Positive and Unlabeled Learning.
CoRR, 2020
Network On Network for Tabular Data Classification in Real-world Applications.
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020
AutoSpeech 2020: The Second Automated Machine Learning Challenge for Speech Classification.
Proceedings of the 21st Annual Conference of the International Speech Communication Association, 2020
Projection-free Distributed Online Convex Optimization with $O(\sqrt{T})$ Communication Complexity.
Proceedings of the 37th International Conference on Machine Learning, 2020
SAdam: A Variant of Adam for Strongly Convex Functions.
Proceedings of the 8th International Conference on Learning Representations, 2020
Efficient Neural Architecture Search via Proximal Iterations.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
Towards AutoML in the presence of Drift: first results.
CoRR, 2019
Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions.
CoRR, 2019
Differentiable Neural Architecture Search via Proximal Iterations.
CoRR, 2019
SAdam: A Variant of Adam for Strongly Convex Functions.
CoRR, 2019
AutoML @ NeurIPS 2018 challenge: Design and Results.
CoRR, 2019
Towards Automated Deep Learning: Analysis of the AutoDL challenge series 2019.
Proceedings of the NeurIPS 2019 Competition and Demonstration Track, 2019
AutoCross: Automatic Feature Crossing for Tabular Data in Real-World Applications.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019
Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Learning for Tail Label Data: A Label-Specific Feature Approach.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
Towards Automated Semi-Supervised Learning.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
Multi-Fidelity Automatic Hyper-Parameter Tuning via Transfer Series Expansion.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019
Analysis of the AutoML Challenge Series 2015-2018.
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Proceedings of the Automated Machine Learning - Methods, Systems, Challenges, 2019
2018
Privacy-preserving Transfer Learning for Knowledge Sharing.
CoRR, 2018
Taking Human out of Learning Applications: A Survey on Automated Machine Learning.
CoRR, 2018