Structured Evolution with Compact Architectures for Scalable Policy Optimization

6 April 2018

Papers citing "Structured Evolution with Compact Architectures for Scalable Policy Optimization"

36 / 36 papers shown

Title
Robotic Table Tennis: A Case Study into a High Speed Learning System David B. DÁmbrosio Jonathan Abelian Saminda Abeyruwan Michael Ahn Alex Bewley ... Vikas Sindhwani Avi Singh Vincent Vanhoucke Grace Vesom Peng Xu 60 13 0 20 Feb 2025
An Enhanced Zeroth-Order Stochastic Frank-Wolfe Framework for Constrained Finite-Sum Optimization Haishan Ye Yinghui Huang Hao Di Xiangyu Chang 43 0 0 13 Jan 2025
Obtaining Lower Query Complexities through Lightweight Zeroth-Order Proximal Gradient Algorithms Bin Gu Xiyuan Wei Hualin Zhang Yi Chang Heng-Chiao Huang FedML 23 0 0 03 Oct 2024
Gradient-Free Method for Heavily Constrained Nonconvex Optimization Wanli Shi Hongchang Gao Bin Gu 21 5 0 31 Aug 2024
Comparisons Are All You Need for Optimizing Smooth Functions Chenyi Zhang Tongyang Li AAML 37 1 0 19 May 2024
Agile Catching with Whole-Body MPC and Blackbox Policy Learning Saminda Abeyruwan Alex Bewley Nicholas M. Boffi K. Choromanski David B. DÁmbrosio ... Anish Shankar Vikas Sindhwani Sumeet Singh Jean-Jacques E. Slotine Stephen Tu 8 9 0 14 Jun 2023
Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies Oscar Li James Harrison Jascha Narain Sohl-Dickstein Virginia Smith Luke Metz 56 5 0 21 Apr 2023
Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization Le‐Yu Chen Jing Xu Luo Luo 31 15 0 16 Jan 2023
Generalizing Gaussian Smoothing for Random Search Katelyn Gao Ozan Sener 36 14 0 27 Nov 2022
GoalsEye: Learning High Speed Precision Table Tennis on a Physical Robot Tianli Ding L. Graesser Saminda Abeyruwan David B. DÁmbrosio Anish Shankar P. Sermanet Pannag R. Sanketi Corey Lynch 59 20 0 07 Oct 2022
Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients Hualin Zhang Huan Xiong Bin Gu 35 7 0 04 Oct 2022
Towards A Unified Policy Abstraction Theory and Representation Learning Approach in Markov Decision Processes Hao Fei Hongyao Tang Jianye Hao Yan Zheng OffRL 28 0 0 16 Sep 2022
Implicit Two-Tower Policies Yunfan Zhao Qingkai Pan K. Choromanski Deepali Jain Vikas Sindhwani OffRL 31 3 0 02 Aug 2022
TTOpt: A Maximum Volume Quantized Tensor Train-based Optimization and its Application to Reinforcement Learning Konstantin Sozykin Andrei Chertkov R. Schutski Anh-Huy Phan A. Cichocki Ivan Oseledets 16 35 0 30 Apr 2022
Dimensionality Reduction and Prioritized Exploration for Policy Search Marius Memmel Puze Liu Davide Tateo Jan Peters 23 3 0 09 Mar 2022
Deep Reinforcement Learning Versus Evolution Strategies: A Comparative Survey Amjad Yousef Majid Serge Saaybi Tomas van Rietbergen Vincent François-Lavet R. V. Prasad Chris Verhoeven OffRL 62 55 0 28 Sep 2021
Curvature-Aware Derivative-Free Optimization Bumsu Kim HanQin Cai Daniel McKenzie W. Yin ODL 35 10 0 27 Sep 2021
An Accelerated Variance-Reduced Conditional Gradient Sliding Algorithm for First-order and Zeroth-order Optimization Xiyuan Wei Bin Gu Heng-Chiao Huang 31 1 0 18 Sep 2021
Robust Stability of Neural Network-controlled Nonlinear Systems with Parametric Variability Soumyabrata Talukder Ratnesh Kumar 18 7 0 13 Sep 2021
EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning S. Vargaftik Ran Ben-Basat Amit Portnoy Gal Mendelson Y. Ben-Itzhak Michael Mitzenmacher FedML 46 46 0 19 Aug 2021
On the Expressive Power of Self-Attention Matrices Valerii Likhosherstov K. Choromanski Adrian Weller 37 34 0 07 Jun 2021
MLGO: a Machine Learning Guided Compiler Optimizations Framework Mircea Trofin Yundi Qian E. Brevdo Zinan Lin K. Choromanski Didong Li 44 62 0 13 Jan 2021
Improving Neural Network Training in Low Dimensional Random Bases Frithjof Gressmann Zach Eaton-Rosen Carlo Luschi 30 28 0 09 Nov 2020
Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves Luke Metz Niru Maheswaranathan C. Freeman Ben Poole Jascha Narain Sohl-Dickstein 33 62 0 23 Sep 2020
Sample-efficient Cross-Entropy Method for Real-time Planning Cristina Pinneri Shambhuraj Sawant Sebastian Blaes Jan Achterhold Joerg Stueckler Michal Rolínek Georg Martius 34 98 0 14 Aug 2020
An adaptive stochastic gradient-free approach for high-dimensional blackbox optimization Anton Dereventsov Clayton Webster Joseph Daws 22 10 0 18 Jun 2020
Robotic Table Tennis with Model-Free Reinforcement Learning Wenbo Gao L. Graesser K. Choromanski Xingyou Song N. Lazić Pannag R. Sanketi Vikas Sindhwani Navdeep Jaitly 19 44 0 31 Mar 2020
Zeroth-Order Regularized Optimization (ZORO): Approximately Sparse Gradients and Adaptive Sampling HanQin Cai Daniel McKenzie W. Yin Zhenliang Zhang 63 49 0 29 Mar 2020
BinaryDuo: Reducing Gradient Mismatch in Binary Activation Network by Coupling Binary Activations Hyungjun Kim Kyungsu Kim Jinseok Kim Jae-Joon Kim MQ 27 47 0 16 Feb 2020
Effective Diversity in Population Based Reinforcement Learning Jack Parker-Holder Aldo Pacchiano K. Choromanski Stephen J. Roberts 22 158 0 03 Feb 2020
Population-Guided Parallel Policy Search for Reinforcement Learning Whiyoung Jung Giseung Park Y. Sung OffRL 24 38 0 09 Jan 2020
Linear interpolation gives better gradients than Gaussian smoothing in derivative-free optimization A. Berahas Liyuan Cao K. Choromanski K. Scheinberg 19 19 0 29 May 2019
Provably Robust Blackbox Optimization for Reinforcement Learning K. Choromanski Aldo Pacchiano Jack Parker-Holder Yunhao Tang Deepali Jain Yuxiang Yang Atil Iscen Jasmine Hsu Vikas Sindhwani 13 5 0 07 Mar 2019
Understanding and Training Deep Diagonal Circulant Neural Networks Alexandre Araujo Benjamin Négrevergne Y. Chevaleyre Jamal Atif 27 4 0 29 Jan 2019
Zeroth-order Nonconvex Stochastic Optimization: Handling Constraints, High-Dimensionality and Saddle-Points Krishnakumar Balasubramanian Saeed Ghadimi ODL 14 100 0 17 Sep 2018
Variational Optimization J. Staines David Barber DRL 65 53 0 18 Dec 2012