Thompson Sampling Tutorial

Contextual bandit algorithm called LinUCB / Linear Upper Confidence Bounds as proposed by Li, Langford and Schapire

Another A/B test library

Privacy-Preserving Bandits (MLSys'20)

Solutions and figures for problems from Reinforcement Learning: An Introduction Sutton&Barto

Network-Oriented Repurposing of Drugs Python Package

Client that handles the administration of StreamingBandit online, or straight from your desktop. Setup and run streaming (contextual) bandit experiments in your browser.

Movie Recommendation using Cascading Bandits namely CascadeLinTS and CascadeLinUCB

Adversarial multi-armed bandit algorithms

Reinforcement learning

A/B testing metrics collection with golang

A small collection of Bandit Algorithms (ETC, E-Greedy, Elimination, UCB, Exp3, LinearUCB, and Thompson Sampling)

Solutions to the Stanford CS:234 Reinforcement Learning 2022 course assignments.

Code for the paper "Best-Arm Identification in Unimodal Bandits" (AISTATS 2025)

Research project on automated A/B testing of software by evolutionary bandits.

This presentation contains very precise yet detailed explanation of concepts of a very interesting topic -- Reinforcement Learning.