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Structured Evolution with Compact Architectures for Scalable Policy
  Optimization

Structured Evolution with Compact Architectures for Scalable Policy Optimization

6 April 2018
K. Choromanski
Mark Rowland
Vikas Sindhwani
Richard E. Turner
Adrian Weller
ArXivPDFHTML

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

27 / 27 papers shown
Title
Robotic Table Tennis: A Case Study into a High Speed Learning System
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-Tao Xu
60
13
0
20 Feb 2025
An Enhanced Zeroth-Order Stochastic Frank-Wolfe Framework for Constrained Finite-Sum Optimization
An Enhanced Zeroth-Order Stochastic Frank-Wolfe Framework for Constrained Finite-Sum Optimization
Haishan Ye
Yinghui Huang
Hao Di
Xiangyu Chang
38
0
0
13 Jan 2025
Obtaining Lower Query Complexities through Lightweight Zeroth-Order
  Proximal Gradient Algorithms
Obtaining Lower Query Complexities through Lightweight Zeroth-Order Proximal Gradient Algorithms
Bin Gu
Xiyuan Wei
Hualin Zhang
Yi Chang
Heng-Chiao Huang
FedML
21
0
0
03 Oct 2024
Comparisons Are All You Need for Optimizing Smooth Functions
Comparisons Are All You Need for Optimizing Smooth Functions
Chenyi Zhang
Tongyang Li
AAML
31
1
0
19 May 2024
Agile Catching with Whole-Body MPC and Blackbox Policy Learning
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
6
9
0
14 Jun 2023
Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution
  Strategies
Variance-Reduced Gradient Estimation via Noise-Reuse in Online Evolution Strategies
Oscar Li
James Harrison
Jascha Narain Sohl-Dickstein
Virginia Smith
Luke Metz
44
5
0
21 Apr 2023
Generalizing Gaussian Smoothing for Random Search
Generalizing Gaussian Smoothing for Random Search
Katelyn Gao
Ozan Sener
19
14
0
27 Nov 2022
GoalsEye: Learning High Speed Precision Table Tennis on a Physical Robot
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
47
20
0
07 Oct 2022
Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without
  Gradients
Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients
Hualin Zhang
Huan Xiong
Bin Gu
22
7
0
04 Oct 2022
Towards A Unified Policy Abstraction Theory and Representation Learning
  Approach in Markov Decision Processes
Towards A Unified Policy Abstraction Theory and Representation Learning Approach in Markov Decision Processes
M. Zhang
Hongyao Tang
Jianye Hao
Yan Zheng
OffRL
25
0
0
16 Sep 2022
Implicit Two-Tower Policies
Implicit Two-Tower Policies
Yunfan Zhao
Qingkai Pan
K. Choromanski
Deepali Jain
Vikas Sindhwani
OffRL
31
3
0
02 Aug 2022
Dimensionality Reduction and Prioritized Exploration for Policy Search
Dimensionality Reduction and Prioritized Exploration for Policy Search
Marius Memmel
Puze Liu
Davide Tateo
Jan Peters
15
3
0
09 Mar 2022
Deep Reinforcement Learning Versus Evolution Strategies: A Comparative
  Survey
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
57
54
0
28 Sep 2021
Robust Stability of Neural Network-controlled Nonlinear Systems with
  Parametric Variability
Robust Stability of Neural Network-controlled Nonlinear Systems with Parametric Variability
Soumyabrata Talukder
Ratnesh Kumar
11
7
0
13 Sep 2021
EDEN: Communication-Efficient and Robust Distributed Mean Estimation for
  Federated Learning
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
22
45
0
19 Aug 2021
On the Expressive Power of Self-Attention Matrices
On the Expressive Power of Self-Attention Matrices
Valerii Likhosherstov
K. Choromanski
Adrian Weller
37
33
0
07 Jun 2021
MLGO: a Machine Learning Guided Compiler Optimizations Framework
MLGO: a Machine Learning Guided Compiler Optimizations Framework
Mircea Trofin
Yundi Qian
E. Brevdo
Zinan Lin
K. Choromanski
D. Li
36
62
0
13 Jan 2021
Improving Neural Network Training in Low Dimensional Random Bases
Improving Neural Network Training in Low Dimensional Random Bases
Frithjof Gressmann
Zach Eaton-Rosen
Carlo Luschi
22
28
0
09 Nov 2020
Tasks, stability, architecture, and compute: Training more effective
  learned optimizers, and using them to train themselves
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
22
62
0
23 Sep 2020
Sample-efficient Cross-Entropy Method for Real-time Planning
Sample-efficient Cross-Entropy Method for Real-time Planning
Cristina Pinneri
Shambhuraj Sawant
Sebastian Blaes
Jan Achterhold
Joerg Stueckler
Michal Rolínek
Georg Martius
24
98
0
14 Aug 2020
Robotic Table Tennis with Model-Free Reinforcement Learning
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
Zeroth-Order Regularized Optimization (ZORO): Approximately Sparse Gradients and Adaptive Sampling
HanQin Cai
Daniel McKenzie
W. Yin
Zhenliang Zhang
22
48
0
29 Mar 2020
BinaryDuo: Reducing Gradient Mismatch in Binary Activation Network by
  Coupling Binary Activations
BinaryDuo: Reducing Gradient Mismatch in Binary Activation Network by Coupling Binary Activations
Hyungjun Kim
Kyungsu Kim
Jinseok Kim
Jae-Joon Kim
MQ
6
47
0
16 Feb 2020
Linear interpolation gives better gradients than Gaussian smoothing in
  derivative-free optimization
Linear interpolation gives better gradients than Gaussian smoothing in derivative-free optimization
A. Berahas
Liyuan Cao
K. Choromanski
K. Scheinberg
6
19
0
29 May 2019
Provably Robust Blackbox Optimization for Reinforcement Learning
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
11
5
0
07 Mar 2019
Understanding and Training Deep Diagonal Circulant Neural Networks
Understanding and Training Deep Diagonal Circulant Neural Networks
Alexandre Araujo
Benjamin Négrevergne
Y. Chevaleyre
Jamal Atif
19
4
0
29 Jan 2019
Variational Optimization
Variational Optimization
J. Staines
David Barber
DRL
65
53
0
18 Dec 2012
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