by Séb Arnold, June 10, 2019

\( % Universal Mathematics \newcommand{\paren}[1]{\left( #1 \right)} \newcommand{\brackets}[1]{\left[ #1 \right]} \newcommand{\braces}[1]{\left\{ #1 \right\}} \newcommand{\norm}[1]{\left\lVert#1\right\rVert} \newcommand{\case}[1]{\begin{cases} #1 \end{cases}} \newcommand{\bigO}[1]{\mathcal{O}\left(#1\right)} % Analysis % Linear Algebra \newcommand{\mat}[1]{\begin{pmatrix}#1\end{pmatrix}} \newcommand{\bmat}[1]{\begin{bmatrix}#1\end{bmatrix}} % Probability Theory \DeclareMathOperator*{\V}{\mathop{\mathrm{Var}}} \DeclareMathOperator*{\E}{\mathop{\mathbb{E}}} \newcommand{\Exp}[2][]{\E_{#1}\brackets{#2}} \newcommand{\Var}[2][]{\V_{#1}\brackets{#2}} \newcommand{\Cov}[2][]{\mathop{\mathrm{Cov}}_{#1}\brackets{#2}} % Optimization \newcommand{\minimize}{\operatorname*{minimize}} \newcommand{\maximize}{\operatorname*{maximize}} \DeclareMathOperator*{\argmin}{arg\,min} \DeclareMathOperator*{\argmax}{arg\,max} % Set Theory \newcommand{\C}{\mathbb{C}} \newcommand{\N}{\mathbb{N}} \newcommand{\Q}{\mathbb{Q}} \newcommand{\R}{\mathbb{R}} \newcommand{\Z}{\mathbb{Z}} \)

Reducing the variance in online optimization by transporting past gradients

S. Arnold, P.-A. Manzagol, R. Babanezhad, I. Mitliagkas, N. Le Roux, 2019, ArXiv

[ArXiv, pdf, website, code]

Understanding the Variance of Policy Gradient Estimators in Reinforcement Learning

S. Arnold*, J. Preiss*, C-Y. Wei*, M. Kloft, 2019, SoCal Machine Learning Symposium, Best Poster

Preprint available soon.

Shapechanger: Environments for Transfer Learning

S. Arnold, E. Pun, T. Denisart, F. Valero-Cuevas, 2017, SoCal Robotics Symposium

[ArXiv, pdf, website]

Accelerating SGD for Distributed Deep Learning Using an Approximated Hessian Matrix

S. Arnold, C. Wang, 2017, ICLR Workshop

[ArXiv, pdf]

A Performance Comparison between TRPO and CEM for Reinforcement Learning

S. Arnold, E. Chu, F. Valero-Cuevas, 2016, SoCal ML Symposium

A Greedy Algorithm to Cluster Specialists

S. Arnold, 2016, ArXiv Pre-prints

[ArXiv, pdf]