368 citations · 693 across the 10 of their papers we have counts for
11 papers
"Sound and Fury": Nonlinear Functionals of Volatility Matrix in the Presence of Jump and Noise
Richard Y. Chen
This paper resolves a pivotal open problem on nonparametric inference for nonlinear functionals of volatility matrix. Multiple prominent statistical tasks can be formulated as func…
The Fourier Transform Method for Volatility Functional Inference by Asynchronous Observations
Richard Y. Chen
We study the volatility functional inference by Fourier transforms. This spectral framework is advantageous in that it harnesses the power of harmonic analysis to handle missing da…
Inference for Volatility Functionals of Multivariate Itô Semimartingales Observed with Jump and Noise
Richard Y. Chen
This paper presents the nonparametric inference for nonlinear volatility functionals of general multivariate Itô semimartingales, in high-frequency and noisy setting. Pre-averaging…
Evolved Policy Gradients
Rein Houthooft, Richard Y. Chen, Phillip Isola +4
We propose a metalearning approach for learning gradient-based reinforcement learning (RL) algorithms. The idea is to evolve a differentiable loss function, such that an agent, whi…
Learning with Opponent-Learning Awareness
Jakob N. Foerster, Richard Y. Chen, Maruan Al-Shedivat +3
Multi-agent settings are quickly gathering importance in machine learning. This includes a plethora of recent work on deep multi-agent reinforcement learning, but also can be exten…
Parameter Space Noise for Exploration
Matthias Plappert, Rein Houthooft, Prafulla Dhariwal +6
Deep reinforcement learning (RL) methods generally engage in exploratory behavior through noise injection in the action space. An alternative is to add noise directly to the agent'…
UCB Exploration via Q-Ensembles
Richard Y. Chen, Szymon Sidor, Pieter Abbeel +1
We show how an ensemble of -functions can be leveraged for more effective exploration in deep reinforcement learning. We build on well established algorithms from the bandit s…
Model-Free Approaches to Discern Non-Stationary Microstructure Noise and Time-Varying Liquidity in High-Frequency Data
Richard Y. Chen, Per A. Mykland
In this paper, we provide non-parametric statistical tools to test stationarity of microstructure noise in general hidden Ito semimartingales, and discuss how to measure liquidity…
Subadditivity of Matrix phi-Entropy and Concentration of Random Matrices
Joel A. Tropp, Richard Y. Chen
Matrix concentration inequalities provide a direct way to bound the typical spectral norm of a random matrix. The methods for establishing these results often parallel classical ar…
Matrix concentration inequalities via the method of exchangeable pairs
Lester Mackey, Michael I. Jordan, Richard Y. Chen +2
This paper derives exponential concentration inequalities and polynomial moment inequalities for the spectral norm of a random matrix. The analysis requires a matrix extension of t…
The Masked Sample Covariance Estimator: An Analysis via Matrix Concentration Inequalities
Richard Y. Chen, Alex Gittens, Joel A. Tropp
Covariance estimation becomes challenging in the regime where the number p of variables outstrips the number n of samples available to construct the estimate. One way to circumvent…