Songtao Lu
41 papers · 2017–2025 · 9 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
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Machine Learning
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Optimization & Theory
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Mathematics & Optimization
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Optimization
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Learning Types · Machine Learning
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Artificial Intelligence
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Keywords
bilevel optimization
(11)
non-convex optimization
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decentralized optimization
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sample complexity
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stochastic optimization
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gradient tracking
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multi-agent reinforcement learning
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representation learning
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federated learning
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distributed learning
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augmented lagrangian method
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convergence analysis
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constrained optimization
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adversarial attack
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communication complexity
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few-shot learning
(2)
primal-dual algorithm
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convergence rate
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reinforcement learning
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black-box optimization
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Papers
Decentralized Bilevel Optimization: A Perspective from Transient Iteration Complexity
JMLR 2025
DUET: Decentralized Bilevel Optimization without Lower-Level Strong Convexity
ICLR 2025
Q-function Decomposition with Intervention Semantics for Factored Action Spaces
AISTATS 2025
Training Nonlinear Transformers for Chain-of-Thought Inference: A Theoretical Generalization Analysis
ICLR 2025
TSP: A Two-Sided Smoothed Primal-Dual Method for Nonconvex Bilevel Optimization
ICML 2025
Distributed Bilevel Optimization with Communication Compression
ICML 2024
FADAS: Towards Federated Adaptive Asynchronous Optimization
ICML 2024
Federated Neuro-Symbolic Learning
ICML 2024
How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?
ICML 2024
M2ASR: Multilingual Multi-task Automatic Speech Recognition via Multi-objective Optimization
Interspeech 2024
PILOT: An O(1/K)-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation
ICLR 2024
SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning
ICML 2024
SPARKLE: A Unified Single-Loop Primal-Dual Framework for Decentralized Bilevel Optimization
NeurIPS 2024
An Alternating Optimization Method for Bilevel Problems under the Polyak-Łojasiewicz Condition
NeurIPS 2023
Bilevel Optimization with Coupled Decision-Dependent Distributions
ICML 2023
Compressed Decentralized Proximal Stochastic Gradient Method for Nonconvex Composite Problems with Heterogeneous Data
ICML 2023
Distributed Offline Policy Optimization Over Batch Data
AISTATS 2023
Joint Edge-Model Sparse Learning is Provably Efficient for Graph Neural Networks
ICLR 2023
Min-Max Multi-objective Bilevel Optimization with Applications in Robust Machine Learning
ICLR 2023
On the Convergence and Sample Complexity Analysis of Deep Q-Networks with ε-Greedy Exploration
NeurIPS 2023
Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning
ICML 2023
SLM: A Smoothed First-Order Lagrangian Method for Structured Constrained Nonconvex Optimization
NeurIPS 2023
Adversarial Examples Can Be Effective Data Augmentation for Unsupervised Machine Learning
AAAI 2022
A Single-Loop Gradient Descent and Perturbed Ascent Algorithm for Nonconvex Functional Constrained Optimization
ICML 2022
A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization
NeurIPS 2022
Distributed adversarial training to robustify deep neural networks at scale
UAI 2022
Finite-Time Convergence and Sample Complexity of Multi-Agent Actor-Critic Reinforcement Learning with Average Reward
ICLR 2022
Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations
IJCAI 2022
Understanding Benign Overfitting in Gradient-Based Meta Learning
NeurIPS 2022
Understanding Latent Correlation-Based Multiview Learning and Self-Supervision: An Identifiability Perspective
ICLR 2022
Zeroth-Order Optimization for Composite Problems with Functional Constraints
AAAI 2022
Decentralized Policy Gradient Descent Ascent for Safe Multi-Agent Reinforcement Learning
AAAI 2021
Rate-improved inexact augmented Lagrangian method for constrained nonconvex optimization
AISTATS 2021
Taming Communication and Sample Complexities in Decentralized Policy Evaluation for Cooperative Multi-Agent Reinforcement Learning
NeurIPS 2021
Decentralized TD Tracking with Linear Function Approximation and its Finite-Time Analysis
NeurIPS 2020
Finding Second-Order Stationary Points Efficiently in Smooth Nonconvex Linearly Constrained Optimization Problems
NeurIPS 2020
Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: Joint Gradient Estimation and Tracking
ICML 2020
Min-Max Optimization without Gradients: Convergence and Applications to Black-Box Evasion and Poisoning Attacks
ICML 2020
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training
NeurIPS 2020
PA-GD: On the Convergence of Perturbed Alternating Gradient Descent to Second-Order Stationary Points for Structured Nonconvex Optimization
ICML 2019
A Stochastic Nonconvex Splitting Method for Symmetric Nonnegative Matrix Factorization
AISTATS 2017