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

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PC-PG: Policy Cover Directed Exploration for Provable Policy Gradient Learning

Aug 13, 2020
Alekh Agarwal, Mikael Henaff, Sham Kakade, Wen Sun

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Information Theoretic Regret Bounds for Online Nonlinear Control

Jun 22, 2020
Sham Kakade, Akshay Krishnamurthy, Kendall Lowrey, Motoya Ohnishi, Wen Sun

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FLAMBE: Structural Complexity and Representation Learning of Low Rank MDPs

Jun 18, 2020
Alekh Agarwal, Sham Kakade, Akshay Krishnamurthy, Wen Sun

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Robust Meta-learning for Mixed Linear Regression with Small Batches

Jun 18, 2020
Weihao Kong, Raghav Somani, Sham Kakade, Sewoong Oh

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* 52 pages, 2 figures 

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Soft Threshold Weight Reparameterization for Learnable Sparsity

Mar 11, 2020
Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham Kakade, Ali Farhadi

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* 17 pages, 9 figures 

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Optimal Regularization Can Mitigate Double Descent

Mar 04, 2020
Preetum Nakkiran, Prayaag Venkat, Sham Kakade, Tengyu Ma

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The Implicit and Explicit Regularization Effects of Dropout

Mar 02, 2020
Colin Wei, Sham Kakade, Tengyu Ma

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Provable Representation Learning for Imitation Learning via Bi-level Optimization

Feb 24, 2020
Sanjeev Arora, Simon S. Du, Sham Kakade, Yuping Luo, Nikunj Saunshi

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* 26 pages 

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Meta-learning for mixed linear regression

Feb 20, 2020
Weihao Kong, Raghav Somani, Zhao Song, Sham Kakade, Sewoong Oh

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Meta-Learning with Implicit Gradients

Sep 10, 2019
Aravind Rajeswaran, Chelsea Finn, Sham Kakade, Sergey Levine

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* NeurIPS 2019. First two authors contributed equally 

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On the Optimality of Sparse Model-Based Planning for Markov Decision Processes

Jul 04, 2019
Alekh Agarwal, Sham Kakade, Lin F. Yang

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Online Meta-Learning

Feb 22, 2019
Chelsea Finn, Aravind Rajeswaran, Sham Kakade, Sergey Levine

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* The first two authors contributed equally 

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Plan Online, Learn Offline: Efficient Learning and Exploration via Model-Based Control

Jan 28, 2019
Kendall Lowrey, Aravind Rajeswaran, Sham Kakade, Emanuel Todorov, Igor Mordatch

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* The first two authors contributed equally. Accepted at ICLR 2019. Supplementary videos available at: https://sites.google.com/view/polo-mpc 

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Provably Correct Automatic Subdifferentiation for Qualified Programs

Sep 23, 2018
Sham Kakade, Jason D. Lee

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Variance Reduction Methods for Sublinear Reinforcement Learning

Aug 25, 2018
Sham Kakade, Mengdi Wang, Lin F. Yang

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* Fixed a bug of a previous version 

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Prediction with a Short Memory

Jun 28, 2018
Vatsal Sharan, Sham Kakade, Percy Liang, Gregory Valiant

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* Updates for STOC camera ready 

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Learning Overcomplete HMMs

Jun 28, 2018
Vatsal Sharan, Sham Kakade, Percy Liang, Gregory Valiant

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* Added acknowledgements 

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Stochastic subgradient method converges on tame functions

May 26, 2018
Damek Davis, Dmitriy Drusvyatskiy, Sham Kakade, Jason D. Lee

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* 32 pages, 1 figure 

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Towards Generalization and Simplicity in Continuous Control

Mar 20, 2018
Aravind Rajeswaran, Kendall Lowrey, Emanuel Todorov, Sham Kakade

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* NIPS 2017, Project page: https://sites.google.com/view/simple-pol 

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Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines

Mar 20, 2018
Cathy Wu, Aravind Rajeswaran, Yan Duan, Vikash Kumar, Alexandre M Bayen, Sham Kakade, Igor Mordatch, Pieter Abbeel

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* Accepted to ICLR 2018, Oral (2%) 

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Leverage Score Sampling for Faster Accelerated Regression and ERM

Nov 22, 2017
Naman Agarwal, Sham Kakade, Rahul Kidambi, Yin Tat Lee, Praneeth Netrapalli, Aaron Sidford

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