Ryan D'Orazio

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I am a PhD student at MILA and the Université de Montréal within the DIRO department. I am co-supervised by Ioannis Mitliagkas and Pierre-Luc Bacon. My current research interests include (but are not limited to), online learning, optimization, reinforcement learning and algorithmic game theory. Previously, I completed my masters in statistical machine learning at the University of Alberta under the co-supervision of James Wright and Matthew Taylor where I worked on combining function approximation and online learning for saddle point computation. Before attending the University of Alberta I completed my bachelor of science in actuarial mathematics at Concordia University and worked as an actuarial analyst for several insurance companies.

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Contact: ryan.dorazio [at] mila.quebec

Publications

Hindsight and Sequential Rationality of Correlated Play
Dustin Morrill, Ryan D’Orazio, Reca Sarfati, Marc Lanctot, James R. Wright, Amy Greenwald, Michael Bowling
AAAI 2021
Paper

Solving Common-Payoff Games with Approximate Policy Iteration
Samuel Sokota*, Edward Lockhart*, Finbarr Timbers, Elnaz Davoodi, Ryan D’Orazio, Neil Burch, Martin Schmid, Michael Bowling, Marc Lanctot
AAAI 2021
Paper / Code

Alternative Function Approximation Parameterizations for Solving Games: An Analysis of f-Regression Counterfactual Regret Minimization
Ryan D’Orazio*, Dustin Morrill*, James Wright, Michael Bowling
AAMAS 2020
Paper

Simultaneous Prediction Intervals for Patient-Specific Survival Curves
Samuel Sokota*, Ryan D’Orazio*, Khurram Javed, Humza Haider, Russell Greiner
IJCAI 2019
Paper / Code

Workshop Papers

Optimistic and Adaptive Lagrangian Hedging
Ryan D’Orazio, Ruitong Huang
Workshop on Reinforcement Learning and Games, AAAI 2021
Paper / Poster

Bounds for Approximate Regret-Matching Algorithms
Ryan D’Orazio, Dustin Morrill, James R. Wright
Smooth Games Optimization and Machine Learning Workshop, NeurIPS 2019
Paper

Thesis

Regret Minimization with Function Approximation in Extensive-Form Games
Ryan D’Orazio
Masters Thesis
University of Alberta
Paper