Efficient And Robust Algorithms For Adversarial Linear Contextual Bandits

Efficient and robust algorithms for adversarial linear contextual bandits

COLT

Generalized Policy Elimination: an efficient algorithm for Nonparametric Contextual Bandits

Uncertainty in Artificial Intelligence

Ankur Moitra: Rethinking Robustness: From Classification to Contextual Bandits (MIT)

USC Probability and Statistics Seminar

Efficient Contextual Bandits in Non-stationary Worlds

COLT

SquareCB: An optimal algorithm for contextual bandits

Karthik Abinav Sankararaman

Efficient Pure Exploration for Combinatorial Bandits with Semi-Bandit Feedback

Algorithmic Learning Theory

Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits

Microsoft Research

Multi-Armed Bandits 3- Contextual

An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives

COLT

Robust Algorithms for Secretaries and Bandits

Simons Institute

Amazon AI Conclave 2019 - Contextual Bandits for Efficient A/B Testing

An efficient bandit algorithm for realtime multivariate optimization

Contextual Bandits

Reinforcement Learning

The Contextual Bandits Problem

Simons Institute

Contextual Bandits: better than A/B tests for production ML

Super Data Science: ML & AI Podcast with Jon Krohn

The Contextual Bandits Problem: A New, Fast, and Simple Algorithm

Microsoft Research

Robust Design Discovery and Exploration in Bayesian Optimization

Google TechTalks

Adaptivity and Confounding in Multi-Armed Bandit Experiments

Stanford Research Talks

Randomized Exploration for Non-Stationary Stochastic Linear Bandits

Uncertainty in Artificial Intelligence

Multi-Armed Bandit : Data Science Concepts