Wang, Shengjie

23 publications

ICML 2025 ToMA: Token Merge with Attention for Diffusion Models Wenbo Lu, Shaoyi Zheng, Yuxuan Xia, Shengjie Wang

CoRL 2024 DexCatch: Learning to Catch Arbitrary Objects with Dexterous Hands Fengbo Lan, Shengjie Wang, Yunzhe Zhang, Haotian Xu, Oluwatosin OluwaPelumi Oseni, Ziye Zhang, Yang Gao, Tao Zhang

ICML 2024 EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data Shengjie Wang, Shaohuai Liu, Weirui Ye, Jiacheng You, Yang Gao

CoLLAs 2024 Enhanced Label Propagation Through Affinity Matrix Fusion for Source-Free Domain Adaptation Li Guo, Yuxuan Xia, Shengjie Wang

CoRL 2024 Reinforcement Learning with Foundation Priors: Let Embodied Agent Efficiently Learn on Its Own Weirui Ye, Yunsheng Zhang, Haoyang Weng, Xianfan Gu, Shengjie Wang, Tong Zhang, Mengchen Wang, Pieter Abbeel, Yang Gao

CoRL 2023 A Policy Optimization Method Towards Optimal-Time Stability Shengjie Wang, Lan Fengb, Xiang Zheng, Yuxue Cao, Oluwatosin OluwaPelumi Oseni, Haotian Xu, Tao Zhang, Yang Gao

ICML 2023 Machine Learning Force Fields with Data Cost Aware Training Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao

NeurIPSW 2023 Machine Learning Force Fields with Data Cost Aware Training Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao

NeurIPS 2022 Retrospective Adversarial Replay for Continual Learning Lilly Kumari, Shengjie Wang, Tianyi Zhou, Jeff A Bilmes

NeurIPS 2022 Towards Human-Level Bimanual Dexterous Manipulation with Reinforcement Learning Yuanpei Chen, Tianhao Wu, Shengjie Wang, Xidong Feng, Jiechuan Jiang, Zongqing Lu, Stephen McAleer, Hao Dong, Song-Chun Zhu, Yaodong Yang

AISTATS 2021 Curriculum Learning by Optimizing Learning Dynamics Tianyi Zhou, Shengjie Wang, Jeff Bilmes

NeurIPS 2021 Constrained Robust Submodular Partitioning Shengjie Wang, Tianyi Zhou, Chandrashekhar Lavania, Jeff A Bilmes

ICLR 2021 Robust Curriculum Learning: From Clean Label Detection to Noisy Label Self-Correction Tianyi Zhou, Shengjie Wang, Jeff Bilmes

NeurIPS 2020 Curriculum Learning by Dynamic Instance Hardness Tianyi Zhou, Shengjie Wang, Jeffrey Bilmes

ICML 2020 Time-Consistent Self-Supervision for Semi-Supervised Learning Tianyi Zhou, Shengjie Wang, Jeff Bilmes

ICML 2019 Bias Also Matters: Bias Attribution for Deep Neural Network Explanation Shengjie Wang, Tianyi Zhou, Jeff Bilmes

AISTATS 2019 Fixing Mini-Batch Sequences with Hierarchical Robust Partitioning Shengjie Wang, Wenruo Bai, Chandrashekhar Lavania, Jeff Bilmes

ICML 2019 Jumpout : Improved Dropout for Deep Neural Networks with ReLUs Shengjie Wang, Tianyi Zhou, Jeff Bilmes

NeurIPS 2018 Diverse Ensemble Evolution: Curriculum Data-Model Marriage Tianyi Zhou, Shengjie Wang, Jeff A. Bilmes

ICLR 2017 Do Deep Convolutional Nets Really Need to Be Deep and Convolutional? Gregor Urban, Krzysztof J. Geras, Samira Ebrahimi Kahou, Özlem Aslan, Shengjie Wang, Abdelrahman Mohamed, Matthai Philipose, Matthew Richardson, Rich Caruana

ICLR 2017 Training Compressed Fully-Connected Networks with a Density-Diversity Penalty Shengjie Wang, Haoran Cai, Jeff A. Bilmes, William S. Noble

ICML 2016 Analysis of Deep Neural Networks with Extended Data Jacobian Matrix Shengjie Wang, Abdel-rahman Mohamed, Rich Caruana, Jeff Bilmes, Matthai Plilipose, Matthew Richardson, Krzysztof Geras, Gregor Urban, Ozlem Aslan

NeurIPS 2015 Mixed Robust/Average Submodular Partitioning: Fast Algorithms, Guarantees, and Applications Kai Wei, Rishabh K Iyer, Shengjie Wang, Wenruo Bai, Jeff A. Bilmes