Get our free extension to see links to code for papers anywhere online!

 Add to Chrome

 Add to Firefox

CatalyzeX Code Finder - Browser extension linking code for ML papers across the web! | Product Hunt Embed
Provable Benefits of Representation Learning in Linear Bandits

Oct 13, 2020
Jiaqi Yang, Wei Hu, Jason D. Lee, Simon S. Du

* 28 pages, 6 figures 

  Access Paper or Ask Questions

How Important is the Train-Validation Split in Meta-Learning?

Oct 12, 2020
Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason D. Lee, Sham Kakade, Huan Wang, Caiming Xiong


  Access Paper or Ask Questions

Sanity-Checking Pruning Methods: Random Tickets can Win the Jackpot

Sep 22, 2020
Jingtong Su, Yihang Chen, Tianle Cai, Tianhao Wu, Ruiqi Gao, Liwei Wang, Jason D. Lee

* Original submission to NeurIPS 2020. Under review 

  Access Paper or Ask Questions

Generalized Leverage Score Sampling for Neural Networks

Sep 21, 2020
Jason D. Lee, Ruoqi Shen, Zhao Song, Mengdi Wang, Zheng Yu


  Access Paper or Ask Questions

Predicting What You Already Know Helps: Provable Self-Supervised Learning

Aug 03, 2020
Jason D. Lee, Qi Lei, Nikunj Saunshi, Jiacheng Zhuo


  Access Paper or Ask Questions

Implicit Bias in Deep Linear Classification: Initialization Scale vs Training Accuracy

Jul 13, 2020
Edward Moroshko, Suriya Gunasekar, Blake Woodworth, Jason D. Lee, Nathan Srebro, Daniel Soudry


  Access Paper or Ask Questions

Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks

Jul 03, 2020
Cong Fang, Jason D. Lee, Pengkun Yang, Tong Zhang


  Access Paper or Ask Questions

Towards Understanding Hierarchical Learning: Benefits of Neural Representations

Jun 24, 2020
Minshuo Chen, Yu Bai, Jason D. Lee, Tuo Zhao, Huan Wang, Caiming Xiong, Richard Socher


  Access Paper or Ask Questions

Shape Matters: Understanding the Implicit Bias of the Noise Covariance

Jun 18, 2020
Jeff Z. HaoChen, Colin Wei, Jason D. Lee, Tengyu Ma


  Access Paper or Ask Questions

Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters

Jun 16, 2020
Kaiyi Ji, Jason D. Lee, Yingbin Liang, H. Vincent Poor

* 28 pages, 8 figures, 2 tables 

  Access Paper or Ask Questions

Distributed Estimation for Principal Component Analysis: a Gap-free Approach

Apr 05, 2020
Xi Chen, Jason D. Lee, He Li, Yun Yang


  Access Paper or Ask Questions

Steepest Descent Neural Architecture Optimization: Escaping Local Optimum with Signed Neural Splitting

Mar 23, 2020
Lemeng Wu, Mao Ye, Qi Lei, Jason D. Lee, Qiang Liu


  Access Paper or Ask Questions

Kernel and Rich Regimes in Overparametrized Models

Feb 24, 2020
Blake Woodworth, Suriya Gunasekar, Jason D. Lee, Edward Moroshko, Pedro Savarese, Itay Golan, Daniel Soudry, Nathan Srebro

* This updates and significantly extends a previous article (arXiv:1906.05827), Sections 6 and 7.1 are the most major additions. 30 pages. arXiv admin note: text overlap with arXiv:1906.05827 

  Access Paper or Ask Questions

Few-Shot Learning via Learning the Representation, Provably

Feb 21, 2020
Simon S. Du, Wei Hu, Sham M. Kakade, Jason D. Lee, Qi Lei


  Access Paper or Ask Questions

Agnostic Q-learning with Function Approximation in Deterministic Systems: Tight Bounds on Approximation Error and Sample Complexity

Feb 17, 2020
Simon S. Du, Jason D. Lee, Gaurav Mahajan, Ruosong Wang


  Access Paper or Ask Questions

When Does Non-Orthogonal Tensor Decomposition Have No Spurious Local Minima?

Nov 22, 2019
Maziar Sanjabi, Sina Baharlouei, Meisam Razaviyayn, Jason D. Lee


  Access Paper or Ask Questions

SGD Learns One-Layer Networks in WGANs

Oct 15, 2019
Qi Lei, Jason D. Lee, Alexandros G. Dimakis, Constantinos Daskalakis

* 21 pages, 4 figures 

  Access Paper or Ask Questions

Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks

Oct 03, 2019
Yu Bai, Jason D. Lee


  Access Paper or Ask Questions

Optimality and Approximation with Policy Gradient Methods in Markov Decision Processes

Aug 29, 2019
Alekh Agarwal, Sham M. Kakade, Jason D. Lee, Gaurav Mahajan

* Additional references and discussion of prior work 

  Access Paper or Ask Questions

Optimal transport mapping via input convex neural networks

Aug 28, 2019
Ashok Vardhan Makkuva, Amirhossein Taghvaei, Sewoong Oh, Jason D. Lee


  Access Paper or Ask Questions

Convergence of Adversarial Training in Overparametrized Networks

Jun 19, 2019
Ruiqi Gao, Tianle Cai, Haochuan Li, Liwei Wang, Cho-Jui Hsieh, Jason D. Lee

* 33 pages 

  Access Paper or Ask Questions

Neural Temporal-Difference Learning Converges to Global Optima

May 24, 2019
Qi Cai, Zhuoran Yang, Jason D. Lee, Zhaoran Wang


  Access Paper or Ask Questions

Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models

May 17, 2019
Mor Shpigel Nacson, Suriya Gunasekar, Jason D. Lee, Nathan Srebro, Daniel Soudry

* ICML Camera ready version 

  Access Paper or Ask Questions

Solving Non-Convex Non-Concave Min-Max Games Under Polyak-ŇĀojasiewicz Condition

Dec 07, 2018
Maziar Sanjabi, Meisam Razaviyayn, Jason D. Lee


  Access Paper or Ask Questions

Gradient Descent Finds Global Minima of Deep Neural Networks

Nov 30, 2018
Simon S. Du, Jason D. Lee, Haochuan Li, Liwei Wang, Xiyu Zhai


  Access Paper or Ask Questions

Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced

Oct 31, 2018
Simon S. Du, Wei Hu, Jason D. Lee

* In NIPS 2018 

  Access Paper or Ask Questions

On the Margin Theory of Feedforward Neural Networks

Oct 12, 2018
Colin Wei, Jason D. Lee, Qiang Liu, Tengyu Ma


  Access Paper or Ask Questions

Provably Correct Automatic Subdifferentiation for Qualified Programs

Sep 23, 2018
Sham Kakade, Jason D. Lee


  Access Paper or Ask Questions

Matrix Completion has No Spurious Local Minimum

Jul 22, 2018
Rong Ge, Jason D. Lee, Tengyu Ma

* NIPS'16 best student paper. fixed Theorem 2.3 in preliminary section in the previous version. The results are not affected 

  Access Paper or Ask Questions