Lu, Songtao

50 publications

ICLR 2025 DUET: Decentralized Bilevel Optimization Without Lower-Level Strong Convexity Zhen Qin, Zhuqing Liu, Songtao Lu, Yingbin Liang, Jia Liu

JMLR 2025 Decentralized Bilevel Optimization: A Perspective from Transient Iteration Complexity Boao Kong, Shuchen Zhu, Songtao Lu, Xinmeng Huang, Kun Yuan

NeurIPS 2025 Meta-D2AG: Causal Graph Learning with Interventional Dynamic Data Tian Gao, Songtao Lu, Junkyu Lee, Elliot Nelson, Debarun Bhattacharjya, Yue Yu, Miao Liu

NeurIPS 2025 Objective Soups: Multilingual Multi-Task Modeling for Speech Processing A F M Saif, Lisha Chen, Xiaodong Cui, Songtao Lu, Brian Kingsbury, Tianyi Chen

NeurIPS 2025 Optimality and NP-Hardness of Transformers in Learning Markovian Dynamical Functions Yanna Ding, Songtao Lu, Yingdong Lu, Tomasz J Nowicki, Jianxi Gao

AISTATS 2025 Q-Function Decomposition with Intervention Semantics for Factored Action Spaces Junkyu Lee, Tian Gao, Elliot Nelson, Miao Liu, Debarun Bhattacharjya, Songtao Lu

ICLRW 2025 Reinforcement Learning in Inference Time: A Perspective from Successive Policy Iterations Xinnan Zhang, Chenliang Li, Siliang Zeng, Jiaxiang Li, Zhongruo Wang, Songtao Lu, Alfredo Garcia, Mingyi Hong

ICML 2025 TSP: A Two-Sided Smoothed Primal-Dual Method for Nonconvex Bilevel Optimization Songtao Lu

ICLR 2025 Training Nonlinear Transformers for Chain-of-Thought Inference: A Theoretical Generalization Analysis Hongkang Li, Songtao Lu, Pin-Yu Chen, Xiaodong Cui, Meng Wang

ICML 2024 Distributed Bilevel Optimization with Communication Compression Yutong He, Jie Hu, Xinmeng Huang, Songtao Lu, Bin Wang, Kun Yuan

ICML 2024 FADAS: Towards Federated Adaptive Asynchronous Optimization Yujia Wang, Shiqiang Wang, Songtao Lu, Jinghui Chen

ICML 2024 Federated Neuro-Symbolic Learning Pengwei Xing, Songtao Lu, Han Yu

ICMLW 2024 How Do Nonlinear Transformers Acquire Generalization-Guaranteed CoT Ability? Hongkang Li, Meng Wang, Songtao Lu, Xiaodong Cui, Pin-Yu Chen

ICMLW 2024 How Do Nonlinear Transformers Acquire Generalization-Guaranteed CoT Ability? Hongkang Li, Meng Wang, Songtao Lu, Xiaodong Cui, Pin-Yu Chen

ICML 2024 How Do Nonlinear Transformers Learn and Generalize in In-Context Learning? Hongkang Li, Meng Wang, Songtao Lu, Xiaodong Cui, Pin-Yu Chen

ICLR 2024 PILOT: An $\mathcal{O}(1/K)$-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation Zhuqing Liu, Xin Zhang, Jia Liu, Zhengyuan Zhu, Songtao Lu

ICML 2024 SF-DQN: Provable Knowledge Transfer Using Successor Feature for Deep Reinforcement Learning Shuai Zhang, Heshan Devaka Fernando, Miao Liu, Keerthiram Murugesan, Songtao Lu, Pin-Yu Chen, Tianyi Chen, Meng Wang

NeurIPS 2024 SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization Shuchen Zhu, Boao Kong, Songtao Lu, Xinmeng Huang, Kun Yuan

NeurIPS 2023 An Alternating Optimization Method for Bilevel Problems Under the Polyak-Łojasiewicz Condition Quan Xiao, Songtao Lu, Tianyi Chen

ICML 2023 Bilevel Optimization with Coupled Decision-Dependent Distributions Songtao Lu

ICML 2023 Compressed Decentralized Proximal Stochastic Gradient Method for Nonconvex Composite Problems with Heterogeneous Data Yonggui Yan, Jie Chen, Pin-Yu Chen, Xiaodong Cui, Songtao Lu, Yangyang Xu

AISTATS 2023 Distributed Offline Policy Optimization over Batch Data Han Shen, Songtao Lu, Xiaodong Cui, Tianyi Chen

ICLR 2023 Joint Edge-Model Sparse Learning Is Provably Efficient for Graph Neural Networks Shuai Zhang, Meng Wang, Pin-Yu Chen, Sijia Liu, Songtao Lu, Miao Liu

ICLR 2023 Min-Max Multi-Objective Bilevel Optimization with Applications in Robust Machine Learning Alex Gu, Songtao Lu, Parikshit Ram, Tsui-Wei Weng

NeurIPS 2023 On the Convergence and Sample Complexity Analysis of Deep Q-Networks with $\epsilon$-Greedy Exploration Shuai Zhang, Hongkang Li, Meng Wang, Miao Liu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Keerthiram Murugesan, Subhajit Chaudhury

ICML 2023 Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning Zhuqing Liu, Xin Zhang, Prashant Khanduri, Songtao Lu, Jia Liu

NeurIPS 2023 SLM: A Smoothed First-Order Lagrangian Method for Structured Constrained Nonconvex Optimization Songtao Lu

NeurIPSW 2023 Transformers as Multi-Task Feature Selectors: Generalization Analysis of In-Context Learning Hongkang Li, Meng Wang, Songtao Lu, Hui Wan, Xiaodong Cui, Pin-Yu Chen

ICML 2022 A Single-Loop Gradient Descent and Perturbed Ascent Algorithm for Nonconvex Functional Constrained Optimization Songtao Lu

NeurIPS 2022 A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization Songtao Lu, Siliang Zeng, Xiaodong Cui, Mark Squillante, Lior Horesh, Brian Kingsbury, Jia Liu, Mingyi Hong

AAAI 2022 Adversarial Examples Can Be Effective Data Augmentation for Unsupervised Machine Learning Chia-Yi Hsu, Pin-Yu Chen, Songtao Lu, Sijia Liu, Chia-Mu Yu

NeurIPSW 2022 Conditional Moment Alignment for Improved Generalization in Federated Learning Jayanth Reddy Regatti, Songtao Lu, Abhishek Gupta, Ness Shroff

UAI 2022 Distributed Adversarial Training to Robustify Deep Neural Networks at Scale Gaoyuan Zhang, Songtao Lu, Yihua Zhang, Xiangyi Chen, Pin-Yu Chen, Quanfu Fan, Lee Martie, Lior Horesh, Mingyi Hong, Sijia Liu

ICLR 2022 Finite-Time Convergence and Sample Complexity of Multi-Agent Actor-Critic Reinforcement Learning with Average Reward Fnu Hairi, Jia Liu, Songtao Lu

IJCAI 2022 Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations Pu Zhao, Parikshit Ram, Songtao Lu, Yuguang Yao, Djallel Bouneffouf, Xue Lin, Sijia Liu

ECML-PKDD 2022 Overcoming Catastrophic Forgetting via Direction-Constrained Optimization Yunfei Teng, Anna Choromanska, Murray Campbell, Songtao Lu, Parikshit Ram, Lior Horesh

NeurIPSW 2022 SCERL: A Benchmark for Intersecting Language and Safe Reinforcement Learning Lan Hoang, Shivam Ratnakar, Nicolas Galichet, Akifumi Wachi, Keerthiram Murugesan, Songtao Lu, Mattia Atzeni, Michael Katz, Subhajit Chaudhury

NeurIPS 2022 Understanding Benign Overfitting in Gradient-Based Meta Learning Lisha Chen, Songtao Lu, Tianyi Chen

ICLR 2022 Understanding Latent Correlation-Based Multiview Learning and Self-Supervision: An Identifiability Perspective Qi Lyu, Xiao Fu, Weiran Wang, Songtao Lu

AAAI 2022 Zeroth-Order Optimization for Composite Problems with Functional Constraints Zichong Li, Pin-Yu Chen, Sijia Liu, Songtao Lu, Yangyang Xu

AISTATS 2021 Rate-Improved Inexact Augmented Lagrangian Method for Constrained Nonconvex Optimization Zichong Li, Pin-Yu Chen, Sijia Liu, Songtao Lu, Yangyang Xu

AAAI 2021 Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning Songtao Lu, Kaiqing Zhang, Tianyi Chen, Tamer Basar, Lior Horesh

NeurIPS 2021 Taming Communication and Sample Complexities in Decentralized Policy Evaluation for Cooperative Multi-Agent Reinforcement Learning Xin Zhang, Zhuqing Liu, Jia Liu, Zhengyuan Zhu, Songtao Lu

NeurIPS 2020 Decentralized TD Tracking with Linear Function Approximation and Its Finite-Time Analysis Gang Wang, Songtao Lu, Georgios Giannakis, Gerald Tesauro, Jian Sun

NeurIPS 2020 Finding Second-Order Stationary Points Efficiently in Smooth Nonconvex Linearly Constrained Optimization Problems Songtao Lu, Meisam Razaviyayn, Bo Yang, Kejun Huang, Mingyi Hong

ICML 2020 Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: Joint Gradient Estimation and Tracking Haoran Sun, Songtao Lu, Mingyi Hong

ICML 2020 Min-Max Optimization Without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks Sijia Liu, Songtao Lu, Xiangyi Chen, Yao Feng, Kaidi Xu, Abdullah Al-Dujaili, Mingyi Hong, Una-May O’Reilly

NeurIPS 2020 ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training Chia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Zhang, Kailash Gopalakrishnan

ICML 2019 PA-GD: On the Convergence of Perturbed Alternating Gradient Descent to Second-Order Stationary Points for Structured Nonconvex Optimization Songtao Lu, Mingyi Hong, Zhengdao Wang

AISTATS 2017 A Stochastic Nonconvex Splitting Method for Symmetric Nonnegative Matrix Factorization Songtao Lu, Mingyi Hong, Zhengdao Wang