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Found 5 papers, 2 papers with code
Monte Carlo Sampling for Regret Minimization in Extensive Games
In the domain of poker, CFR has proven effective, particularly when using a domain-specific augmentation involving chance outcome sampling.
Computing Robust Counter-Strategies
Adaptation to other initially unknown agents often requires computing an effective counter-strategy.
Safe Exploration for Identifying Linear Systems via Robust Optimization
Motivated by the cooling of Google's data centers, we study how one can safely identify the parameters of a system model with a desired accuracy and confidence level.
Parallelized Stochastic Gradient Descent
With the increase in available data parallel machine learning has become an increasingly pressing problem.
Slow Learners are Fast
Online learning algorithms have impressive convergence properties when it comes to risk minimization and convex games on very large problems.
