Jason D. Lee
- Gradient Descent Finds Global Minima of Deep Neural Networks
2018/11/09 by Simon S. Du, Jason D. Lee, Du, Simon S. +7 · 1 voice · 48 citations
Engineering · Computer Science · #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #Machine Learning and ELM
- Fine-Tuning Language Models with Just Forward Passes
2023/05/27 by Sadhika Malladi, Malladi, Sadhika, Tianyu Gao +11 · 1 voice · 59 citations
Computer Science · Engineering · #Ferroelectric and Negative Capacitance Devices #Natural Language Processing Techniques #Topic Modeling #cs.CL #cs.LG
- Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads
2024/01/19 by Tianle Cai, Yuhong Li, Cai, Tianle +11 · 157 citations
Computer Science · Social Sciences · #Computation and Language (cs.CL) #Computational and Text Analysis Methods #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Topic Modeling
- A Kernelized Stein Discrepancy for Goodness-of-fit Tests and Model Evaluation
2016/02/10 by Qiang Liu, Jason D. Lee, Liu, Qiang +3 · 23 citations
Decision Sciences · Mathematics · #FOS: Computer and information sciences #Machine Learning (stat.ML) #Probabilistic and Robust Engineering Design #Statistical Distribution Estimation and Applications #Statistical Methods and Bayesian Inference
- Teaching Arithmetic to Small Transformers
2023/07/07 by Nayoung Lee, Lee, Nayoung, Kartik K. Sreenivasan +8 · 1 voice · 14 citations
Computer Science · #Computational Physics and Python Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Topic Modeling #cs.LG
- Looped Transformers as Programmable Computers
2023/01/30 by Angeliki Giannou, Giannou, Angeliki, Shashank Rajput +9 · 34 citations
Computer Science · Engineering · #Parallel Computing and Optimization Techniques #Ferroelectric and Negative Capacitance Devices #Neural Networks and Reservoir Computing
- Implicit Bias of Gradient Descent on Linear Convolutional Networks
2018/06/01 by Suriya Gunasekar, Gunasekar, Suriya, Jason D. Lee +5 · 19 citations
Computer Science · Engineering · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Matrix Theory and Algorithms #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Optimal transport mapping via input convex neural networks
2019/08/28 by Ashok Vardhan Makkuva, Amirhossein Taghvaei, Makkuva, Ashok Vardhan +5 · 22 citations
Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Stochastic Gradient Optimization Techniques
- Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods
2019/02/21 by Maher Nouiehed, Nouiehed, Maher, Maziar Sanjabi +7 · 20 citations
Computer Science · Decision Sciences · #Stochastic Gradient Optimization Techniques #Advanced Bandit Algorithms Research #Adversarial Robustness in Machine Learning
- Gradient Descent Converges to Minimizers
2016/02/16 by Jason D. Lee, Lee, Jason D., Max Simchowitz +5 · 31 citations
Computer Science · Mathematics · #Stochastic Gradient Optimization Techniques #Markov Chains and Monte Carlo Methods #Mathematical Biology Tumor Growth
- Algorithmic Regularization in Learning Deep Homogeneous Models: Layers\n are Automatically Balanced
2018/06/03 by Simon S. Du, Du, Simon S., Wei Hu +3 · 19 citations
Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Matrix Theory and Algorithms #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Matrix Completion has No Spurious Local Minimum
2016/05/24 by Rong Ge, Jason D. Lee, Ge, Rong +3 · 14 citations
Computer Science · Engineering · #Data Structures and Algorithms (cs.DS) #Distributed Sensor Networks and Detection Algorithms #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- Learning One-hidden-layer Neural Networks with Landscape Design
2017/11/01 by Rong Ge, Ge, Rong, Jason D. Lee +3 · 30 citations
Computer Science · #Stochastic Gradient Optimization Techniques #Machine Learning and Algorithms #Machine Learning and ELM
- Few-Shot Learning via Learning the Representation, Provably
2020/02/21 by Simon S. Du, Wei Hu, Du, Simon S. +7 · 28 citations
Computer Science · Engineering · #Domain Adaptation and Few-Shot Learning #Machine Learning and ELM #Sparse and Compressive Sensing Techniques
- Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel
2018/10/12 by Colin Wei, Jason D. Lee, Wei, Colin +5 · 18 citations
Computer Science · #Advanced Neural Network Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Stochastic Gradient Optimization Techniques
- How Transformers Learn Causal Structure with Gradient Descent
2024/02/22 by Eshaan Nichani, Alex Damian, Nichani, Eshaan +3 · 25 citations
Computer Science · #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- REST: Retrieval-Based Speculative Decoding
2023/11/14 by Zhenyu He, Zexuan Zhong, He, Zhenyu +7 · 21 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Machine Learning (cs.LG) #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling
- Self-Stabilization: The Implicit Bias of Gradient Descent at the Edge of Stability
2022/09/30 by Alex Damian, Damian, Alex, Eshaan Nichani +3 · 16 citations
Physics and Astronomy · Computer Science · #Model Reduction and Neural Networks #Neural Networks and Applications #Stochastic Gradient Optimization Techniques
- Predicting What You Already Know Helps: Provable Self-Supervised\n Learning
2020/08/03 by Jason D. Lee, Qi Lei, Lee, Jason D. +5 · 24 citations
Computer Science · #Domain Adaptation and Few-Shot Learning #Topic Modeling #Machine Learning and Data Classification
- Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark
2024/02/18 by Yihua Zhang, Pingzhi Li, Zhang, Yihua +23 · 24 citations
Computer Science · Engineering · Mathematics · #Advanced Control Systems Design #Computation and Language (cs.CL) #Digital Filter Design and Implementation #FOS: Computer and information sciences #Machine Learning (cs.LG) #Numerical methods for differential equations
- Statistical Inference for Model Parameters in Stochastic Gradient Descent
2016/10/27 by Xi Chen, Jason D. Lee, Chen, Xi +5 · 11 citations
Computer Science · Mathematics · #Stochastic Gradient Optimization Techniques #Markov Chains and Monte Carlo Methods #Statistical Methods and Inference
- Shape Matters: Understanding the Implicit Bias of the Noise Covariance
2020/06/15 by Jeff Z. HaoChen, Colin Wei, HaoChen, Jeff Z. +5 · 14 citations
Computer Science · #Machine Learning and Algorithms #Stochastic Gradient Optimization Techniques #Adversarial Robustness in Machine Learning
- Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks
2019/10/03 by Yu Bai, Bai, Yu, Jason D. Lee +1 · 17 citations
Computer Science · #Stochastic Gradient Optimization Techniques #Neural Networks and Applications #Domain Adaptation and Few-Shot Learning
- On the Theory of Policy Gradient Methods: Optimality, Approximation, and\n Distribution Shift
2019/08/01 by Alekh Agarwal, Sham M. Kakade, Agarwal, Alekh +5 · 9 citations
Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Fuel Cells and Related Materials #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics
- Scaling Laws in Linear Regression: Compute, Parameters, and Data
2024/06/12 by Licong Lin, Jingfeng Wu, Lin, Licong +7 · 15 citations
Mathematics · #Advanced Statistical Methods and Models #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Statistics Theory (math.ST)
- Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters
2020/06/16 by Kaiyi Ji, Ji, Kaiyi, Jason D. Lee +5 · 9 citations
Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Machine Learning and ELM #Optimization and Control (math.OC)
- Policy Mirror Descent for Regularized Reinforcement Learning: A Generalized Framework with Linear Convergence
2021/05/24 by Wenhao Zhan, Shicong Cen, Zhan, Wenhao +9 · 8 citations
Computer Science · Decision Sciences · #Adaptive Dynamic Programming Control #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Reinforcement Learning in Robotics
- Convergence of Gradient Descent on Separable Data
2018/03/05 by Mor Shpigel Nacson, Nacson, Mor Shpigel, Jason D. Lee +9 · 10 citations
Computer Science · Engineering · Mathematics · #Stochastic Gradient Optimization Techniques #Sparse and Compressive Sensing Techniques #Markov Chains and Monte Carlo Methods
- When is a Convolutional Filter Easy To Learn?
2017/09/18 by Simon S. Du, Jason D. Lee, Du, Simon S. +3 · 17 citations
Computer Science · #Neural Networks and Applications #Anomaly Detection Techniques and Applications #Speech and Audio Processing
- Distributed Stochastic Variance Reduced Gradient Methods and A Lower Bound for Communication Complexity
2015/07/27 by Jason D. Lee, Qihang Lin, Lee, Jason D. +5 · 9 citations
Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Privacy-Preserving Technologies in Data #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- REBEL: Reinforcement Learning via Regressing Relative Rewards
2024/04/25 by Zhaolin Gao, Gao, Zhaolin, Jonathan Chang +17 · 12 citations
Computer Science · #Reinforcement Learning in Robotics
- What Makes a Reward Model a Good Teacher? An Optimization Perspective
2025/03/19 by Noam Razin, Zixuan Wang, Razin, Noam +8 · 25 citations
Social Sciences · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #Education and Islamic Studies #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Correcting the Mythos of KL-Regularization: Direct Alignment without Overoptimization via Chi-Squared Preference Optimization
2024/07/18 by Audrey Huang, Wenhao Zhan, Huang, Audrey +11 · 1 voice · 11 citations
Computer Science · Engineering · #Advanced Multi-Objective Optimization Algorithms #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Neural Networks and Applications #Topology Optimization in Engineering #cs.AI #cs.CL #cs.LG
- Offline Reinforcement Learning with Realizability and Single-policy\n Concentrability
2022/02/09 by Wenhao Zhan, Zhan, Wenhao, Baihe Huang +7 · 7 citations
Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Mobile Crowdsensing and Crowdsourcing #Reinforcement Learning in Robotics
- BitDelta: Your Fine-Tune May Only Be Worth One Bit
2024/02/15 by James Liu, Guangxuan Xiao, Liu, James +11 · 1 voice · 3 citations
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #cs.CL #cs.LG
- AI-Driven Review Systems: Evaluating LLMs in Scalable and Bias-Aware Academic Reviews
2024/08/19 by Keith Tyser, Tyser, Keith, Ben Segev +21 · 13 citations
Computer Science · Decision Sciences · #Artificial Intelligence (cs.AI) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Scientific Computing and Data Management
- Neural Temporal-Difference and Q-Learning Provably Converge to Global Optima
2019/05/24 by Zhuoran Yang, Cai, Qi, Jason D. Lee +4 · 8 citations
Computer Science · #Reinforcement Learning in Robotics #Adaptive Dynamic Programming Control #Machine Learning and ELM
- Learning Halfspaces and Neural Networks with Random Initialization
2015/11/25 by Yuchen Zhang, Jason D. Lee, Zhang, Yuchen +5 · 6 citations
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Machine Learning and ELM #Stochastic Gradient Optimization Techniques
- Provable Offline Preference-Based Reinforcement Learning
2023/05/24 by Wenhao Zhan, Masatoshi Uehara, Zhan, Wenhao +7 · 7 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · #Receptor Mechanisms and Signaling #Reinforcement Learning in Robotics #Formal Methods in Verification
- An Information-Theoretic Analysis of In-Context Learning
2024/01/28 by Hong Jun Jeon, Jeon, Hong Jun, Jason D. Lee +5 · 8 citations
Computer Science · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning and Data Classification #Machine Learning in Healthcare
- Implicit Bias in Deep Linear Classification: Initialization Scale vs\n Training Accuracy
2020/07/13 by Edward Moroshko, Suriya Gunasekar, Moroshko, Edward +9 · 4 citations
Computer Science · Mathematics · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #Model Reduction and Neural Networks #Stochastic Gradient Optimization Techniques
- Understanding Incremental Learning of Gradient Descent: A Fine-grained Analysis of Matrix Sensing
2023/01/27 by Jikai Jin, Zhiyuan Li, Jin, Jikai +7 · 5 citations
Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- On the Power of Over-parametrization in Neural Networks with Quadratic Activation
2018/03/03 by Simon S. Du, Du, Simon S., Jason D. Lee +1 · 3 citations
Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Optimization and Control (math.OC)
- Towards Optimal Statistical Watermarking
2023/12/13 by Baihe Huang, Huang, Baihe, Hanlin Zhu +10 · 6 citations
Computer Science · #Advanced Steganography and Watermarking Techniques #Chaos-based Image/Signal Encryption #Computation and Language (cs.CL) #Computer Graphics and Visualization Techniques #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Understanding Optimization in Deep Learning with Central Flows
2024/10/31 by Jeremy M. Cohen, Alex Damian, Cohen, Jeremy M. +7 · 9 citations
Decision Sciences · #Simulation Techniques and Applications
- Exact Post Model Selection Inference for Marginal Screening
2014/02/23 by Jason D. Lee, Jonathan Taylor, Lee, Jason D +1 · 3 citations
Biochemistry, Genetics and Molecular Biology · Mathematics · #FOS: Computer and information sciences #FOS: Mathematics #Genetic and phenotypic traits in livestock #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Statistics Theory (math.ST)
- Provable Reward-Agnostic Preference-Based Reinforcement Learning
2023/05/29 by Wenhao Zhan, Zhan, Wenhao, Masatoshi Uehara +5 · 5 citations
Computer Science · #Advanced Graph Neural Networks #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics #Statistics Theory (math.ST)
- Impact of Representation Learning in Linear Bandits
2020/10/13 by Jiaqi Yang, Yang, Jiaqi, Wei Hu +5 · 4 citations
Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Reinforcement Learning in Robotics
- Communication-efficient sparse regression: a one-shot approach
2015/03/14 by Jason D. Lee, Lee, Jason D., Yuekai Sun +5 · 4 citations
Computer Science · Engineering · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Sparse and Compressive Sensing Techniques #Statistical Methods and Inference #Stochastic Gradient Optimization Techniques
- Learning Mixed Graphical Models
2012/05/22 by Jason D. Lee, Lee, Jason D., Trevor Hastie +1 · 2 citations
Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Mathematics #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Medical Image Segmentation Techniques #Optimization and Control (math.OC)
- Understanding Factual Recall in Transformers via Associative Memories
2024/12/09 by Eshaan Nichani, Jason D. Lee, Nichani, Eshaan +3 · 8 citations
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Natural Language Processing Techniques #Speech and dialogue systems #Topic Modeling
- Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks
2020/07/02 by Cong Fang, Jason D. Lee, Fang, Cong +5 · 3 citations
Computer Science · Materials Science · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Machine Learning in Materials Science #Model Reduction and Neural Networks #Optimization and Control (math.OC) #Stochastic Gradient Optimization Techniques
- Asynchronous Tool Usage for Real-Time Agents
2024/10/28 by Antonio A. Ginart, Naveen Kodali, Ginart, Antonio A. +9 · 7 citations
Computer Science · #Distributed and Parallel Computing Systems #Robotic Path Planning Algorithms #Mobile Agent-Based Network Management
- Provably Efficient Reinforcement Learning in Partially Observable Dynamical Systems
2022/06/24 by Masatoshi Uehara, Uehara, Masatoshi, Ayush Sekhari +7 · 3 citations
Computer Science · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Reinforcement Learning in Robotics #Statistics Theory (math.ST)
- PAC Reinforcement Learning for Predictive State Representations
2022/07/12 by Wenhao Zhan, Zhan, Wenhao, Masatoshi Uehara +5 · 3 citations
Computer Science · #Data Stream Mining Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Algorithms #Reinforcement Learning in Robotics
- Anytime Acceleration of Gradient Descent
2024/11/26 by Zihan Zhang, Jason D. Lee, Zhang, Zihan +5 · 3 voices · 3 citations
Engineering · #Welding Techniques and Residual Stresses #cs.LG #eess.SY #math.OC #stat.ML
- Generalized Leverage Score Sampling for Neural Networks
2020/09/21 by Jason D. Lee, Lee, Jason D., Ruoqi Shen +7 · 3 citations
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Machine Learning and ELM #Stochastic Gradient Optimization Techniques
- Emergence and scaling laws in SGD learning of shallow neural networks
2025/04/28 by Yunwei Ren, Eshaan Nichani, Ren, Yunwei +5 · 1 voice · 8 citations
Computer Science · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and ELM #Neural Networks and Applications #Stochastic Gradient Optimization Techniques #cs.LG #stat.ML
- Learning Compositional Functions with Transformers from Easy-to-Hard Data
2025/05/29 by Zixuan Wang, Eshaan Nichani, Wang, Zixuan +11 · 12 citations
Computer Science · #Natural Language Processing Techniques #Topic Modeling #Advanced Graph Neural Networks
- Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and Distillation
2025/02/02 by Juno Kim, Denny Wu, Kim, Juno +5 · 7 citations
Computer Science · #Artificial Intelligence (cs.AI) #Computability, Logic, AI Algorithms #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Reward Collapse in Aligning Large Language Models
2023/05/28 by Ziang Song, Tianle Cai, Song, Ziang +5 · 3 citations
Computer Science · Medicine · #Artificial Intelligence (cs.AI) #Artificial Intelligence in Healthcare and Education #Computation and Language (cs.CL) #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Topic Modeling
- A Theory of Label Propagation for Subpopulation Shift
2021/02/22 by Tianle Cai, Ruiqi Gao, Cai, Tianle +5 · 2 citations
Computer Science · #Domain Adaptation and Few-Shot Learning #Machine Learning and ELM #Multimodal Machine Learning Applications
- How Fine-Tuning Allows for Effective Meta-Learning
2021/05/05 by Kurtland Chua, Chua, Kurtland, Qi Lei +3 · 2 citations
Computer Science · #Adversarial Robustness in Machine Learning #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification
- Incremental Methods for Weakly Convex Optimization
2019/07/26 by Li Xiao, Zhihui Zhu, Li, Xiao +5 · 3 citations
Engineering · Computer Science · Mathematics · #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques #Advanced Optimization Algorithms Research
- Convergence of Adversarial Training in Overparametrized Neural Networks
2019/06/19 by Ruiqi Gao, Gao, Ruiqi, Tianle Cai +9 · 2 citations
Computer Science · #Adversarial Robustness in Machine Learning #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
- Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials
2022/06/08 by Eshaan Nichani, Nichani, Eshaan, Y. Bai +3 · 2 citations
Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Neural Networks and Applications #Stochastic Gradient Optimization Techniques
- Reward-agnostic Fine-tuning: Provable Statistical Benefits of Hybrid Reinforcement Learning
2023/05/17 by Gen Li, Li, Gen, Wenhao Zhan +7 · 3 citations
Computer Science · Engineering · #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Mobile Crowdsensing and Crowdsourcing #Reinforcement Learning in Robotics #Statistics Theory (math.ST) #Transportation and Mobility Innovations
- Optimization-Based Separations for Neural Networks
2021/12/04 by Itay Safran, Safran, Itay, Jason D. Lee +1 · 2 citations
Computer Science · #Advanced Neural Network Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and ELM #Stochastic Gradient Optimization Techniques
- First-order Methods Almost Always Avoid Saddle Points
2017/10/20 by Jason D. Lee, Ioannis Panageas, Lee, Jason D. +9 · 2 citations
Computer Science · Engineering · Physics and Astronomy · #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques #Stochastic Gradient Optimization Techniques
- How Well Can Transformers Emulate In-context Newton's Method?
2024/03/05 by Angeliki Giannou, Yang Liu, Giannou, Angeliki +7 · 3 citations
Computer Science · Decision Sciences · Engineering · #Advanced Measurement and Metrology Techniques #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optimization and Control (math.OC) #Scientific Measurement and Uncertainty Evaluation #Sensor Technology and Measurement Systems
- Accelerating RL for LLM Reasoning with Optimal Advantage Regression
2025/05/27 by Kianté Brantley, Mingyu Chen, Brantley, Kianté +11 · 9 citations
Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Fuzzy Logic and Control Systems #Machine Learning (cs.LG) #Natural Language Processing Techniques
- Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF
2024/10/06 by Zhaolin Gao, Gao, Zhaolin, Wenhao Zhan +11 · 4 citations
Engineering · #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Reliability and Maintenance Optimization
- How Important is the Train-Validation Split in Meta-Learning?
2020/10/12 by Yu Bai, Bai, Yu, Minshuo Chen +13 · 3 citations
Computer Science · Engineering · #Domain Adaptation and Few-Shot Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Data Classification #Sparse and Compressive Sensing Techniques
- Black-box Importance Sampling
2016/10/17 by Qiang Liu, Liu, Qiang, Jason D. Lee +1 · 1 citation
Computer Science · Mathematics · #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (stat.ML) #Statistical Methods and Inference
- Fully Character-Level Neural Machine Translation without Explicit\n Segmentation
2016/10/10 by Jason D. Lee, Lee, Jason, Kyunghyun Cho +3 · 1 citation
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Handwritten Text Recognition Techniques #Machine Learning (cs.LG) #Natural Language Processing Techniques #Topic Modeling
- Provably Correct Automatic Subdifferentiation for Qualified Programs
2018/09/23 by Sham M. Kakade, Jason D. Lee, Kakade, Sham +1 · 1 citation
Computer Science · #Advanced Multi-Objective Optimization Algorithms #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Numerical Methods and Algorithms #Optimization and Control (math.OC)
- Solving Non-Convex Non-Concave Min-Max Games Under Polyak-Łojasiewicz Condition
2018/12/07 by Maziar Sanjabi, Meisam Razaviyayn, Sanjabi, Maziar +3 · 3 citations
Computer Science · Decision Sciences · Mathematics · #Advanced Bandit Algorithms Research #Advanced Optimization Algorithms Research #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC) #Stochastic Gradient Optimization Techniques
- When Does Non-Orthogonal Tensor Decomposition Have No Spurious Local\n Minima?
2019/11/21 by Maziar Sanjabi, Sina Baharlouei, Sanjabi, Maziar +5 · 2 citations
Mathematics · Computer Science · Engineering · #Tensor decomposition and applications #Advanced Neural Network Applications #Sparse and Compressive Sensing Techniques
- MUSBO: Model-based Uncertainty Regularized and Sample Efficient Batch Optimization for Deployment Constrained Reinforcement Learning
2021/02/23 by DiJia Su, Su, DiJia, Jason D. Lee +5 · 1 citation
Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Age of Information Optimization #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Reinforcement Learning in Robotics
- Going Beyond Linear RL: Sample Efficient Neural Function Approximation
2021/07/14 by Baihe Huang, Kaixuan Huang, Huang, Baihe +11 · 1 citation
Computer Science · Engineering · #Reinforcement Learning in Robotics #Neural Networks and Reservoir Computing #Ferroelectric and Negative Capacitance Devices
- Optimal Gradient-based Algorithms for Non-concave Bandit Optimization
2021/07/09 by Baihe Huang, Huang, Baihe, Kaixuan Huang +11 · 1 citation
Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics #Stochastic Gradient Optimization Techniques
- Offline Minimax Soft-Q-learning Under Realizability and Partial Coverage
2023/02/05 by Masatoshi Uehara, Nathan Kallus, Uehara, Masatoshi +5 · 2 citations
Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics
- Nearly Minimax Algorithms for Linear Bandits with Shared Representation
2022/03/29 by Jiaqi Yang, Lei Qi, Yang, Jiaqi +5 · 1 citation
Decision Sciences · Computer Science · #Advanced Bandit Algorithms Research #Optimization and Search Problems #Age of Information Optimization
- Transformers Provably Learn Sparse Token Selection While Fully-Connected Nets Cannot
2024/06/11 by Zixuan Wang, Stanley Wei, Wang, Zixuan +5 · 2 citations
Engineering · #Advanced Memory and Neural Computing #FOS: Computer and information sciences #Ferroelectric and Negative Capacitance Devices #Information Theory (cs.IT) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Radiation Effects in Electronics
- Decentralized Optimistic Hyperpolicy Mirror Descent: Provably No-Regret Learning in Markov Games
2022/06/03 by Wenhao Zhan, Jason D. Lee, Zhan, Wenhao +3 · 1 citation
Computer Science · Decision Sciences · Engineering · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics #Smart Grid Energy Management
- Learning and Transferring Sparse Contextual Bigrams with Linear Transformers
2024/10/30 by Yunwei Ren, Zixuan Wang, Ren, Yunwei +3 · 2 citations
Computer Science · Engineering · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Indoor and Outdoor Localization Technologies #Machine Learning (cs.LG) #Music and Audio Processing #Speech and Audio Processing
- Local Optimization Achieves Global Optimality in Multi-Agent Reinforcement Learning
2023/05/08 by Yulai Zhao, Zhuoran Yang, Zhao, Yulai +5 · 1 citation
Computer Science · Decision Sciences · #Computer Science and Game Theory (cs.GT) #Distributed Control Multi-Agent Systems #FOS: Computer and information sciences #Game Theory and Applications #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Multiagent Systems (cs.MA) #Reinforcement Learning in Robotics
- The Generative Leap: Sharp Sample Complexity for Efficiently Learning Gaussian Multi-Index Models
2025/06/05 by Alex Damian, Jason D. Lee, Damian, Alex +3 · 2 citations
Computer Science · Mathematics · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Tensor decomposition and applications
- TeraHAC: Hierarchical Agglomerative Clustering of Trillion-Edge Graphs
2023/08/07 by Laxman Dhulipala, Jason D. Lee, Dhulipala, Laxman +5 · 1 citation
Computer Science · Physics and Astronomy · #Advanced Clustering Algorithms Research #Complex Network Analysis Techniques #Caching and Content Delivery
- AI4SLT: Empirical Processes in Lean 4 for Formal Statistical Learning Theory
2026/02/02 by Yuanhe Zhang, Jason D. Lee, Fanghui Liu · 1 voice · 1 citation
#cs.LG #cs.CL #math.ST
- Towards General Function Approximation in Zero-Sum Markov Games
2021/07/30 by Baihe Huang, Huang, Baihe, Jason D. Lee +5 · 2 citations
Computer Science · Decision Sciences · Mathematics · #Reinforcement Learning in Robotics #Advanced Bandit Algorithms Research #Markov Chains and Monte Carlo Methods
- DiscoLoop: Looping Discrete Embeddings and Continuous Hidden States for Multi-hop Reasoning
2026/07/27 by Hengyu Fu, Tianyu Guo, Zixuan Wang +5
#cs.CL #cs.AI #cs.LG
- Algorithmic Separation between Constant-Depth and Logarithmic-Depth Neural Networks
2026/07/28 by Yunwei Ren, Zihao Wang, Jason D. Lee
#cs.LG #stat.ML