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

Online learning approaches to optimize database join operations in PostgreSQL.

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

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

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

Adversarial multi-armed bandit algorithms

Reinforcement learning

A/B testing metrics collection with golang

Movie Recommendation using Cascading Bandits namely CascadeLinTS and CascadeLinUCB

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.

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

Privacy-Preserving Bandits (MLSys'20)

Another A/B test library

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

Thompson Sampling Tutorial