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Yingbin Liang

82 papers · 2013–2025 · 9 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (10) πŸƒ Academic Marathon (12) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (9) πŸ—ΊοΈ Taxonomy Completionist (18) 🏠 Conference Loyalist (22) πŸ† Keyword Champion (9) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ”¬ Deep Specialist (23) 🀝 Dynamic Duo (19) πŸ“ˆ Trend Setter πŸš€ Conference Pioneer πŸ”₯ Unstoppable (11) πŸ’Ž Century Club (82) πŸ—ƒοΈ Keyword Collector (57) ⚑ Prolific Year (11)

Conferences

ICLR (22) NIPS (22) ICML (15) AISTATS (7) JMLR (7) AAAI (3) UAI (3) IJCAI (2) COLT (1)

Top co-authors

Yi Zhou (19) Kaiyi Ji (15) Tengyu Xu (14) Zhe Wang (10) Jing Yang (10) Ness Shroff (9) Ruiquan Huang (7) Zhangyang Wang (7) Junjie Yang (6) Yuan Cheng (6)

Keywords

nonconvex optimization (11) convergence rate (9) convergence analysis (9) reinforcement learning (7) sample complexity (7) bilevel optimization (6) gradient descent (6) variance reduction (5) stochastic approximation (4) training dynamics (4) markov decision process (4) temporal difference learning (4) stochastic optimization (4) representation learning (3) stochastic gradient descent (3) model-agnostic meta-learning (3) off-policy learning (3) policy gradient (3) function approximation (3) few-shot learning (3)

Papers

Theory on Mixture-of-Experts in Continual Learning ICLR 2025
Theory on Score-Mismatched Diffusion Models and Zero-Shot Conditional Samplers ICLR 2025
Random Pruning Over-parameterized Neural Networks Can Improve Generalization: A Training Dynamics Analysis JMLR 2025
A Theoretical Analysis of Self-Supervised Learning for Vision Transformers ICLR 2025
DUET: Decentralized Bilevel Optimization without Lower-Level Strong Convexity ICLR 2025
Broadening Target Distributions for Accelerated Diffusion Models via a Novel Analysis Approach ICLR 2025
Transformers Provably Learn Two-Mixture of Linear Classification via Gradient Flow ICLR 2025
How Transformers Learn Regular Language Recognition: A Theoretical Study on Training Dynamics and Implicit Bias ICML 2025
Unlocking the Power of Rehearsal in Continual Learning: A Theoretical Perspective ICML 2025
Dynamic Loss-Based Sample Reweighting for Improved Large Language Model Pretraining ICLR 2025
Provable Benefits of Multi-task RL under Non-Markovian Decision Making Processes ICLR 2024
On the Hardness of Online Nonconvex Optimization with Single Oracle Feedback ICLR 2024
In-context Convergence of Transformers ICML 2024
Training Dynamics of Transformers to Recognize Word Co-occurrence via Gradient Flow Analysis NIPS 2024
Non-asymptotic Convergence of Training Transformers for Next-token Prediction NIPS 2024
In-Context Learning with Representations: Contextual Generalization of Trained Transformers NIPS 2024
Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games ICML 2024
Neural Networks with Sparse Activation Induced by Large Bias: Tighter Analysis with Bias-Generalized NTK JMLR 2024
Sample Complexity Characterization for Linear Contextual MDPs AISTATS 2024
Doubly Robust Instance-Reweighted Adversarial Training ICLR 2024
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations ICLR 2024
Safe Exploration Incurs Nearly No Additional Sample Complexity for Reward-Free RL ICLR 2023
M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation ICLR 2023
Non-stationary Reinforcement Learning under General Function Approximation ICML 2023
Improved Sample Complexity for Reward-free Reinforcement Learning under Low-rank MDPs ICLR 2023
Lower Bounds and Accelerated Algorithms for Bilevel Optimization JMLR 2023
Learning to Generalize Provably in Learning to Optimize AISTATS 2023
Near-Optimal Adversarial Reinforcement Learning with Switching Costs ICLR 2023
Online Nonconvex Optimization with Limited Instantaneous Oracle Feedback COLT 2023
Generalized-Smooth Nonconvex Optimization is As Efficient As Smooth Nonconvex Optimization ICML 2023
Provably Efficient Algorithm for Nonstationary Low-Rank MDPs NIPS 2023
Non-Convex Bilevel Optimization with Time-Varying Objective Functions NIPS 2023
Theoretical Characterization of the Generalization Performance of Overfitted Meta-Learning ICLR 2023
Global Convergence of Two-Timescale Actor-Critic for Solving Linear Quadratic Regulator AAAI 2023
A Near-Optimal Algorithm for Safe Reinforcement Learning Under Instantaneous Hard Constraints ICML 2023
Theory on Forgetting and Generalization of Continual Learning ICML 2023
Will Bilevel Optimizers Benefit from Loops NIPS 2022
PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning Method ICLR 2022
Data sampling affects the complexity of online SGD over dependent data UAI 2022
Deterministic policy gradient: Convergence analysis UAI 2022
Theoretical Convergence of Multi-Step Model-Agnostic Meta-Learning JMLR 2022
Model-Based Offline Meta-Reinforcement Learning with Regularization ICLR 2022
On the Convergence Theory for Hessian-Free Bilevel Algorithms NIPS 2022
A Unifying Framework of Off-Policy General Value Function Evaluation NIPS 2022
Provable Generalization of Overparameterized Meta-learning Trained with SGD NIPS 2022
Provable Benefit of Multitask Representation Learning in Reinforcement Learning NIPS 2022
Doubly Robust Off-Policy Actor-Critic: Convergence and Optimality ICML 2021
Faster Non-asymptotic Convergence for Double Q-learning NIPS 2021
Provably Faster Algorithms for Bilevel Optimization NIPS 2021
Non-asymptotic Convergence of Adam-type Reinforcement Learning Algorithms under Markovian Sampling AAAI 2021
Sample Complexity Bounds for Two Timescale Value-based Reinforcement Learning Algorithms AISTATS 2021
When Will Generative Adversarial Imitation Learning Algorithms Attain Global Convergence AISTATS 2021
Proximal Gradient Descent-Ascent: Variable Convergence under KŁ Geometry ICLR 2021
Bilevel Optimization: Convergence Analysis and Enhanced Design ICML 2021
CRPO: A New Approach for Safe Reinforcement Learning with Convergence Guarantee ICML 2021
Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters NIPS 2020
Finite-Time Analysis for Double Q-learning NIPS 2020
Robust Stochastic Bandit Algorithms under Probabilistic Unbounded Adversarial Attack AAAI 2020
History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms ICML 2020
Spectral Algorithms for Community Detection in Directed Networks JMLR 2020
Analysis of Q-learning with Adaptation and Momentum Restart for Gradient Descent IJCAI 2020
Proximal Gradient Algorithm with Momentum and Flexible Parameter Restart for Nonconvex Optimization IJCAI 2020
Improving Sample Complexity Bounds for (Natural) Actor-Critic Algorithms NIPS 2020
Reanalysis of Variance Reduced Temporal Difference Learning ICLR 2020
SGD Converges to Global Minimum in Deep Learning via Star-convex Path ICLR 2019
Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex Optimization ICML 2019
Stochastic Variance-Reduced Cubic Regularization for Nonconvex Optimization AISTATS 2019
Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples NIPS 2019
Finite-Sample Analysis for SARSA with Linear Function Approximation NIPS 2019
SpiderBoost and Momentum: Faster Variance Reduction Algorithms NIPS 2019
Cubic Regularization with Momentum for Nonconvex Optimization UAI 2019
Critical Points of Linear Neural Networks: Analytical Forms and Landscape Properties ICLR 2018
Distributed Proximal Gradient Algorithm for Partially Asynchronous Computer Clusters JMLR 2018
Convergence of Cubic Regularization for Nonconvex Optimization under KL Property NIPS 2018
Minimax Estimation of Neural Net Distance NIPS 2018
Convergence Analysis of Proximal Gradient with Momentum for Nonconvex Optimization ICML 2017
A Nonconvex Approach for Phase Retrieval: Reshaped Wirtinger Flow and Incremental Algorithms JMLR 2017
Reshaped Wirtinger Flow for Solving Quadratic System of Equations NIPS 2016
Provable Non-convex Phase Retrieval with Outliers: Median TruncatedWirtinger Flow ICML 2016
On Convergence of Model Parallel Proximal Gradient Algorithm for Stale Synchronous Parallel System AISTATS 2016
Analysis of Robust PCA via Local Incoherence NIPS 2015
Block Regularized Lasso for Multivariate Multi-Response Linear Regression AISTATS 2013