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2020 – today
- 2024
[j15]Sijia Chen, Yu-Jie Zhang, Wei-Wei Tu, Peng Zhao, Lijun Zhang:
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization. J. Mach. Learn. Res. 25: 178:1-178:62 (2024)- [j14]Tong Wei, Qian-Yu Liu, Jiang-Xin Shi, Wei-Wei Tu, Lan-Zhe Guo:
Transfer and share: semi-supervised learning from long-tailed data. Mach. Learn. 113(4): 1725-1742 (2024) - [j13]Ran Cheng
, Hugo Jair Escalante, Wei-Wei Tu, Jan N. van Rijn, Shuo Wang, Yun Yang:
Guest Editorial: AutoML for Nonstationary Data. IEEE Trans. Artif. Intell. 5(6): 2456-2457 (2024) - [c36]Wentse Chen, Shiyu Huang, Yuan Chiang, Tim Pearce, Wei-Wei Tu, Ting Chen, Jun Zhu:
DGPO: Discovering Multiple Strategies with Diversity-Guided Policy Optimization. AAAI 2024: 11390-11398 - [c35]Xiaowen Yang, Jie-Jing Shao, Wei-Wei Tu, Yufeng Li, Wang-Zhou Dai, Zhi-Hua Zhou:
Safe Abductive Learning in the Presence of Inaccurate Rules. AAAI 2024: 16361-16369 - [c34]Junzhe Chen, Xuming Hu, Shuodi Liu, Shiyu Huang, Wei-Wei Tu, Zhaofeng He, Lijie Wen:
LLMArena: Assessing Capabilities of Large Language Models in Dynamic Multi-Agent Environments. ACL (1) 2024: 13055-13077 - [c33]Lijun Zhang, Haomin Bai, Wei-Wei Tu, Ping Yang, Yao Hu:
Efficient Stochastic Approximation of Minimax Excess Risk Optimization. ICML 2024 - [i38]Junzhe Chen, Xuming Hu, Shuodi Liu, Shiyu Huang, Wei-Wei Tu, Zhaofeng He, Lijie Wen:
LLMArena: Assessing Capabilities of Large Language Models in Dynamic Multi-Agent Environments. CoRR abs/2402.16499 (2024) - [i37]Ziyan Xiong, Bo Chen, Shiyu Huang, Wei-Wei Tu, Zhaofeng He, Yang Gao:
MQE: Unleashing the Power of Interaction with Multi-agent Quadruped Environment. CoRR abs/2403.16015 (2024) - [i36]Ruize Zhang, Zelai Xu, Chengdong Ma, Chao Yu, Wei-Wei Tu, Shiyu Huang, Deheng Ye, Wenbo Ding, Yaodong Yang, Yu Wang:
A Survey on Self-play Methods in Reinforcement Learning. CoRR abs/2408.01072 (2024) - 2023
- [j12]Weiwei Tu, Jiuxiang Dong:
Improved robust reduced-order sliding mode fault-tolerant control for T-S fuzzy systems with disturbances. Fuzzy Sets Syst. 464: 108481 (2023) - [j11]Weiwei Tu, Jiuxiang Dong:
Robust sliding mode control for a class of nonlinear systems through dual-layer sliding mode scheme. J. Frankl. Inst. 360(13): 10227-10250 (2023) - [c32]Fanqi Lin, Shiyu Huang, Tim Pearce, Wenze Chen, Wei-Wei Tu:
TiZero: Mastering Multi-Agent Football with Curriculum Learning and Self-Play. AAMAS 2023: 67-76 - [c31]Xinyi Yang, Shiyu Huang, Yiwen Sun, Yuxiang Yang, Chao Yu, Wei-Wei Tu, Huazhong Yang, Yu Wang:
Learning Graph-Enhanced Commander-Executor for Multi-Agent Navigation. AAMAS 2023: 1652-1660 - [c30]Sijia Chen, Wei-Wei Tu, Peng Zhao, Lijun Zhang:
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization. ICML 2023: 5002-5035 - [c29]Xu Wang, Huan Zhao, Wei-Wei Tu, Quanming Yao:
Automated 3D Pre-Training for Molecular Property Prediction. KDD 2023: 2419-2430 - [i35]Xinyi Yang, Shiyu Huang, Yiwen Sun, Yuxiang Yang, Chao Yu, Wei-Wei Tu, Huazhong Yang, Yu Wang:
Learning Graph-Enhanced Commander-Executor for Multi-Agent Navigation. CoRR abs/2302.04094 (2023) - [i34]Sijia Chen, Wei-Wei Tu, Peng Zhao, Lijun Zhang:
Optimistic Online Mirror Descent for Bridging Stochastic and Adversarial Online Convex Optimization. CoRR abs/2302.04552 (2023) - [i33]Fanqi Lin, Shiyu Huang, Tim Pearce, Wenze Chen, Wei-Wei Tu:
TiZero: Mastering Multi-Agent Football with Curriculum Learning and Self-Play. CoRR abs/2302.07515 (2023) - [i32]Lijun Zhang, Wei-Wei Tu:
Efficient Stochastic Approximation of Minimax Excess Risk Optimization. CoRR abs/2306.00026 (2023) - [i31]Xu Wang, Huan Zhao, Weiwei Tu, Quanming Yao:
Automated 3D Pre-Training for Molecular Property Prediction. CoRR abs/2306.07812 (2023) - [i30]Fanqi Lin, Shiyu Huang, Weiwei Tu:
Diverse Policies Converge in Reward-free Markov Decision Processe. CoRR abs/2308.11924 (2023) - [i29]Haixu Song, Shiyu Huang, Yinpeng Dong, Wei-Wei Tu:
Robustness and Generalizability of Deepfake Detection: A Study with Diffusion Models. CoRR abs/2309.02218 (2023) - [i28]Shiyu Huang, Wentse Chen, Yiwen Sun, Fuqing Bie, Wei-Wei Tu:
OpenRL: A Unified Reinforcement Learning Framework. CoRR abs/2312.16189 (2023) - 2022
- [j10]Joseph Pedersen, Rafael Muñoz-Gómez, Jiangnan Huang, Haozhe Sun, Wei-Wei Tu, Isabelle Guyon:
LTU Attacker for Membership Inference. Algorithms 15(7): 254 (2022) - [j9]Yuanyu Wan, Wei-Wei Tu, Lijun Zhang:
Strongly adaptive online learning over partial intervals. Sci. China Inf. Sci. 65(10) (2022) - [j8]Tong Wei, Hai Wang, Weiwei Tu, Yufeng Li:
Robust model selection for positive and unlabeled learning with constraints. Sci. China Inf. Sci. 65(11) (2022) - [j7]Zhen Xu, Lanning Wei, Huan Zhao, Rex Ying, Quanming Yao, Wei-Wei Tu, Isabelle Guyon:
Bridging the Gap of AutoGraph Between Academia and Industry: Analyzing AutoGraph Challenge at KDD Cup 2020. Frontiers Artif. Intell. 5 (2022) - [j6]Yuanyu Wan, Guanghui Wang, Wei-Wei Tu, Lijun Zhang:
Projection-free Distributed Online Learning with Sublinear Communication Complexity. J. Mach. Learn. Res. 23: 172:1-172:53 (2022) - [j5]Yuanyu Wan, Wei-Wei Tu, Lijun Zhang:
Online strongly convex optimization with unknown delays. Mach. Learn. 111(3): 871-893 (2022) - [j4]Zhen Xu, Sergio Escalera, Adrien Pavão, Magali Richard, Wei-Wei Tu, Quanming Yao, Huan Zhao, Isabelle Guyon:
Codabench: Flexible, easy-to-use, and reproducible meta-benchmark platform. Patterns 3(7): 100543 (2022) - [c28]Xiaochen Cai, Hengxing Cai, Boqing Zhu, Kele Xu, Weiwei Tu, Dawei Feng:
Multiple Temporal Fusion based Weakly-supervised Pre-training Techniques for Video Categorization. ACM Multimedia 2022: 7089-7093 - [c27]Xiaochen Cai, Hengxing Cai, Kele Xu, Wei-Wei Tu, Wu-Jun Li:
VSM: A Versatile Semi-supervised Model for Multi-modal Cell Instance Segmentation. Cell Segmentation Challenge @ NeurIPS 2022: 1-13 - [c26]Yuanyu Wan, Wei-Wei Tu, Lijun Zhang:
Online Frank-Wolfe with Arbitrary Delays. NeurIPS 2022 - [c25]Fanqi Lin, Shiyu Huang, Wei-Wei Tu:
Diverse Policies Converge in Reward-Free Markov Decision Processes. PRICAI (1) 2022: 125-136 - [c24]Chenwei Lou, Jun Gao, Changlong Yu, Wei Wang, Huan Zhao, Weiwei Tu, Ruifeng Xu:
Translation-Based Implicit Annotation Projection for Zero-Shot Cross-Lingual Event Argument Extraction. SIGIR 2022: 2076-2081 - [i27]Xu Wang, Huan Zhao, Weiwei Tu, Hao Li, Yu Sun, Xiaochen Bo:
Graph Neural Networks for Double-Strand DNA Breaks Prediction. CoRR abs/2201.01855 (2022) - [i26]Haozhe Sun, Wei-Wei Tu, Isabelle Guyon:
OmniPrint: A Configurable Printed Character Synthesizer. CoRR abs/2201.06648 (2022) - [i25]Joseph Pedersen, Rafael Muñoz-Gómez, Jiangnan Huang, Haozhe Sun, Wei-Wei Tu, Isabelle Guyon:
LTU Attacker for Membership Inference. CoRR abs/2202.02278 (2022) - [i24]Germán Barquero, Johnny Núñez, Sergio Escalera, Zhen Xu, Wei-Wei Tu, Isabelle Guyon, Cristina Palmero:
Didn't see that coming: a survey on non-verbal social human behavior forecasting. CoRR abs/2203.02480 (2022) - [i23]Germán Barquero, Johnny Núñez, Zhen Xu, Sergio Escalera, Wei-Wei Tu, Isabelle Guyon, Cristina Palmero:
Comparison of Spatio-Temporal Models for Human Motion and Pose Forecasting in Face-to-Face Interaction Scenarios. CoRR abs/2203.03245 (2022) - [i22]Zhen Xu, Lanning Wei, Huan Zhao, Rex Ying, Quanming Yao, Wei-Wei Tu, Isabelle Guyon:
Bridging the Gap of AutoGraph between Academia and Industry: Analysing AutoGraph Challenge at KDD Cup 2020. CoRR abs/2204.02625 (2022) - [i21]Yuanyu Wan, Wei-Wei Tu, Lijun Zhang:
Online Frank-Wolfe with Unknown Delays. CoRR abs/2204.04964 (2022) - [i20]Tong Wei, Qian-Yu Liu, Jiang-Xin Shi, Wei-Wei Tu, Lan-Zhe Guo:
Transfer and Share: Semi-Supervised Learning from Long-Tailed Data. CoRR abs/2205.13358 (2022) - 2021
- [j3]Weiwei Tu, Jiuxiang Dong, Ding Zhai:
Optimal ϵ -stealthy attack in cyber-physical systems. J. Frankl. Inst. 358(1): 151-171 (2021) - [j2]Hugo Jair Escalante, Quanming Yao, Wei-Wei Tu, Nelishia Pillay, Rong Qu, Yang Yu, Neil Houlsby:
Guest Editorial: Automated Machine Learning. IEEE Trans. Pattern Anal. Mach. Intell. 43(9): 2887-2890 (2021) - [c23]Tao Han, Wei-Wei Tu, Yufeng Li:
Explanation Consistency Training: Facilitating Consistency-Based Semi-Supervised Learning with Interpretability. AAAI 2021: 7639-7646 - [c22]Cristina Palmero, Júlio C. S. Jacques Júnior, Albert Clapés, Isabelle Guyon, Wei-Wei Tu, Thomas B. Moeslund, Sergio Escalera:
Understanding Social Behavior in Dyadic and Small Group Interactions: Preface. DYAD@ICCV 2021: 1-3 - [c21]Cristina Palmero, Germán Barquero, Júlio C. S. Jacques Júnior, Albert Clapés, Johnny Núñez, David Curto, Sorina Smeureanu, Javier Selva, Zejian Zhang, David Saeteros, David Gallardo-Pujol, Georgina Guilera, David Leiva, Feng Han, Xiaoxue Feng, Jennifer He, Wei-Wei Tu, Thomas B. Moeslund, Isabelle Guyon, Sergio Escalera:
ChaLearn LAP Challenges on Self-Reported Personality Recognition and Non-Verbal Behavior Forecasting During Social Dyadic Interactions: Dataset, Design, and Results. DYAD@ICCV 2021: 4-52 - [c20]Germán Barquero, Johnny Núñez, Zhen Xu, Sergio Escalera, Wei-Wei Tu, Isabelle Guyon, Cristina Palmero:
Comparison of Spatio-Temporal Models for Human Motion and Pose Forecasting in Face-to-Face Interaction Scenarios. DYAD@ICCV 2021: 107-138 - [c19]Germán Barquero, Johnny Núñez, Sergio Escalera, Zhen Xu, Wei-Wei Tu, Isabelle Guyon, Cristina Palmero:
Didn't see that coming: a survey on non-verbal social human behavior forecasting. DYAD@ICCV 2021: 139-178 - [c18]Huan Zhao, Quanming Yao, Weiwei Tu:
Search to aggregate neighborhood for graph neural network. ICDE 2021: 552-563 - [c17]Jingsong Wang, Yuxuan He, Chunyu Zhao, Qijie Shao, Wei-Wei Tu, Tom Ko, Hung-yi Lee, Lei Xie:
Auto-KWS 2021 Challenge: Task, Datasets, and Baselines. Interspeech 2021: 4244-4248 - [c16]Tong Wei, Wei-Wei Tu, Yufeng Li, Guo-Ping Yang:
Towards Robust Prediction on Tail Labels. KDD 2021: 1812-1820 - [c15]Mingcheng Chen, Zhenghui Wang, Zhiyun Zhao, Weinan Zhang, Xiawei Guo, Jian Shen, Yanru Qu, Jieli Lu, Min Xu, Yu Xu, Tiange Wang, Mian Li, Weiwei Tu, Yong Yu, Yufang Bi, Weiqing Wang, Guang Ning:
Task-wise Split Gradient Boosting Trees for Multi-center Diabetes Prediction. KDD 2021: 2663-2673 - [c14]Haozhe Sun, Wei-Wei Tu, Isabelle Guyon:
OmniPrint: A Configurable Printed Character Synthesizer. NeurIPS Datasets and Benchmarks 2021 - [c13]Lijun Zhang, Guanghui Wang, Wei-Wei Tu, Wei Jiang, Zhi-Hua Zhou:
Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions. NeurIPS 2021: 24968-24980 - [c12]Zhen Xu, Wei-Wei Tu, Isabelle Guyon:
AutoML Meets Time Series Regression Design and Analysis of the AutoSeries Challenge. ECML/PKDD (5) 2021: 36-51 - [e1]Cristina Palmero, Júlio C. S. Jacques Júnior, Albert Clapés, Isabelle Guyon, Wei-Wei Tu, Thomas B. Moeslund, Sergio Escalera:
ChaLearn LAP Challenge on Understanding Social Behavior in Dyadic and Small Group Interactions, DYAD 2021, held in conjunction with ICCV 2021, Virtual, October 16, 2021. Proceedings of Machine Learning Research 173, PMLR 2021 [contents] - [i19]Yuanyu Wan, Wei-Wei Tu, Lijun Zhang:
Online Strongly Convex Optimization with Unknown Delays. CoRR abs/2103.11354 (2021) - [i18]Jingsong Wang, Yuxuan He, Chunyu Zhao, Qijie Shao, Wei-Wei Tu, Tom Ko, Hung-yi Lee, Lei Xie:
Auto-KWS 2021 Challenge: Task, Datasets, and Baselines. CoRR abs/2104.00513 (2021) - [i17]Huan Zhao, Quanming Yao, Wei-Wei Tu:
Search to aggregate neighborhood for graph neural network. CoRR abs/2104.06608 (2021) - [i16]Zhen Xu, Wei-Wei Tu, Isabelle Guyon:
AutoML Meets Time Series Regression Design and Analysis of the AutoSeries Challenge. CoRR abs/2107.13186 (2021) - [i15]Mingcheng Chen, Zhenghui Wang, Zhiyun Zhao, Weinan Zhang, Xiawei Guo, Jian Shen, Yanru Qu, Jieli Lu, Min Xu, Yu Xu, Tiange Wang, Mian Li, Wei-Wei Tu, Yong Yu, Yufang Bi, Weiqing Wang, Guang Ning:
Task-wise Split Gradient Boosting Trees for Multi-center Diabetes Prediction. CoRR abs/2108.07107 (2021) - [i14]Xiawei Guo, Yuhan Quan, Huan Zhao, Quanming Yao, Yong Li, Weiwei Tu:
TabGNN: Multiplex Graph Neural Network for Tabular Data Prediction. CoRR abs/2108.09127 (2021) - [i13]Tong Wei, Jiang-Xin Shi, Wei-Wei Tu, Yu-Feng Li:
Robust Long-Tailed Learning under Label Noise. CoRR abs/2108.11569 (2021) - [i12]Zhen Xu, Huan Zhao, Wei-Wei Tu, Magali Richard, Sergio Escalera, Isabelle Guyon:
Codabench: Flexible, Easy-to-Use and Reproducible Benchmarking for Everyone. CoRR abs/2110.05802 (2021) - 2020
- [j1]Zhengying Liu, Zhen Xu, Sergio Escalera, Isabelle Guyon, Júlio C. S. Jacques Júnior, Meysam Madadi, Adrien Pavao, Sébastien Treguer, Wei-Wei Tu:
Towards automated computer vision: analysis of the AutoCV challenges 2019. Pattern Recognit. Lett. 135: 196-203 (2020) - [c11]Quanming Yao, Ju Xu, Wei-Wei Tu, Zhanxing Zhu:
Efficient Neural Architecture Search via Proximal Iterations. AAAI 2020: 6664-6671 - [c10]Guanghui Wang, Shiyin Lu, Quan Cheng, Weiwei Tu, Lijun Zhang:
SAdam: A Variant of Adam for Strongly Convex Functions. ICLR 2020 - [c9]Yuanyu Wan, Wei-Wei Tu, Lijun Zhang:
Projection-free Distributed Online Convex Optimization with $O(\sqrt{T})$ Communication Complexity. ICML 2020: 9818-9828 - [c8]Jingsong Wang, Tom Ko, Zhen Xu, Xiawei Guo, Souxiang Liu, Wei-Wei Tu, Lei Xie:
AutoSpeech 2020: The Second Automated Machine Learning Challenge for Speech Classification. INTERSPEECH 2020: 1967-1971 - [c7]Yuanfei Luo, Hao Zhou, Wei-Wei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang:
Network On Network for Tabular Data Classification in Real-world Applications. SIGIR 2020: 2317-2326 - [p2]Xiawei Guo, Quanming Yao, James T. Kwok, Wei-Wei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang:
Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction. Federated Learning 2020: 269-283 - [i11]Tong Wei, Feng Shi, Hai Wang, Wei-Wei Tu, Yu-Feng Li:
MixPUL: Consistency-based Augmentation for Positive and Unlabeled Learning. CoRR abs/2004.09388 (2020) - [i10]Yuanfei Luo, Hao Zhou, Wei-Wei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang:
Network On Network for Tabular Data Classification in Real-world Applications. CoRR abs/2005.10114 (2020) - [i9]Jingsong Wang, Tom Ko, Zhen Xu, Xiawei Guo, Souxiang Liu, Wei-Wei Tu, Lei Xie:
AutoSpeech 2020: The Second Automated Machine Learning Challenge for Speech Classification. CoRR abs/2010.13130 (2020)
2010 – 2019
- 2019
- [c6]Yi-Qi Hu, Yang Yu, Wei-Wei Tu, Qiang Yang, Yuqiang Chen, Wenyuan Dai:
Multi-Fidelity Automatic Hyper-Parameter Tuning via Transfer Series Expansion. AAAI 2019: 3846-3853 - [c5]Yufeng Li, Hai Wang, Tong Wei, Wei-Wei Tu:
Towards Automated Semi-Supervised Learning. AAAI 2019: 4237-4244 - [c4]Tong Wei, Wei-Wei Tu, Yufeng Li:
Learning for Tail Label Data: A Label-Specific Feature Approach. IJCAI 2019: 3842-3848 - [c3]Quanming Yao, Xiawei Guo, James T. Kwok, Wei-Wei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang:
Privacy-Preserving Stacking with Application to Cross-organizational Diabetes Prediction. IJCAI 2019: 4114-4120 - [c2]Yuanfei Luo, Mengshuo Wang, Hao Zhou, Quanming Yao, Wei-Wei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang:
AutoCross: Automatic Feature Crossing for Tabular Data in Real-World Applications. KDD 2019: 1936-1945 - [c1]Zhengying Liu, Zhen Xu, Shangeth Rajaa, Meysam Madadi, Júlio C. S. Jacques Júnior, Sergio Escalera, Adrien Pavao, Sébastien Treguer, Wei-Wei Tu, Isabelle Guyon:
Towards Automated Deep Learning: Analysis of the AutoDL challenge series 2019. NeurIPS (Competition and Demos) 2019: 242-252 - [p1]Isabelle Guyon, Lisheng Sun-Hosoya, Marc Boullé, Hugo Jair Escalante, Sergio Escalera, Zhengying Liu, Damir Jajetic, Bisakha Ray, Mehreen Saeed, Michèle Sebag, Alexander R. Statnikov, Wei-Wei Tu, Evelyne Viegas:
Analysis of the AutoML Challenge Series 2015-2018. Automated Machine Learning 2019: 177-219 - [i8]Hugo Jair Escalante, Wei-Wei Tu, Isabelle Guyon, Daniel L. Silver, Evelyne Viegas, Yuqiang Chen, Wenyuan Dai, Qiang Yang:
AutoML @ NeurIPS 2018 challenge: Design and Results. CoRR abs/1903.05263 (2019) - [i7]Yuanfei Luo, Mengshuo Wang, Hao Zhou, Quanming Yao, Wei-Wei Tu, Yuqiang Chen, Qiang Yang, Wenyuan Dai:
AutoCross: Automatic Feature Crossing for Tabular Data in Real-World Applications. CoRR abs/1904.12857 (2019) - [i6]Guanghui Wang, Shiyin Lu, Weiwei Tu, Lijun Zhang:
SAdam: A Variant of Adam for Strongly Convex Functions. CoRR abs/1905.02957 (2019) - [i5]Quanming Yao, Ju Xu, Wei-Wei Tu, Zhanxing Zhu:
Differentiable Neural Architecture Search via Proximal Iterations. CoRR abs/1905.13577 (2019) - [i4]Lijun Zhang, Guanghui Wang, Weiwei Tu, Zhi-Hua Zhou:
Dual Adaptivity: A Universal Algorithm for Minimizing the Adaptive Regret of Convex Functions. CoRR abs/1906.10851 (2019) - [i3]Jorge G. Madrid, Hugo Jair Escalante, Eduardo F. Morales, Wei-Wei Tu, Yang Yu, Lisheng Sun-Hosoya, Isabelle Guyon, Michèle Sebag:
Towards AutoML in the presence of Drift: first results. CoRR abs/1907.10772 (2019) - 2018
- [i2]Quanming Yao, Mengshuo Wang, Hugo Jair Escalante, Isabelle Guyon, Yi-Qi Hu, Yu-Feng Li, Wei-Wei Tu, Qiang Yang, Yang Yu:
Taking Human out of Learning Applications: A Survey on Automated Machine Learning. CoRR abs/1810.13306 (2018) - [i1]Xiawei Guo, Quanming Yao, Wei-Wei Tu, Yuqiang Chen, Wenyuan Dai, Qiang Yang:
Privacy-preserving Transfer Learning for Knowledge Sharing. CoRR abs/1811.09491 (2018)
Coauthor Index
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