bandit-algorithms

🔬 Research Framework for Single and Multi-Players 🎰 Multi-Arms Bandits (MAB) Algorithms, implementing all the state-of-the-art algorithms for single-player (UCB, KL-UCB, Thompson...) and multi-player (MusicalChair, MEGA, rhoRand, MCTop/RandTopM etc).. Available on PyPI: https://pypi.org/project/SMPyBandits/ and documentation on

A hyperparameter optimization framework, inspired by Optuna.

Yahoo! news article recommendation system by linUCB

My solutions to Yandex Practical Reinforcement Learning course in PyTorch and Tensorflow

Big Data's open seminars: An Interactive Introduction to Reinforcement Learning

Bandit algorithms

A lightweight python library for bandit algorithms

Privacy-Preserving Bandits (MLSys'20)

More about the exploration-exploitation tradeoff with harder bandits

Code for our ACML and INTERSPEECH papers: "Speaker Diarization as a Fully Online Bandit Learning Problem in MiniVox".

Python implementation of UCB, EXP3 and Epsilon greedy algorithms

Personal reimplementation of some ML algorithms for learning purposes

Artificial Intelligence series

Personalized and Interactive Music Recommendation with Bandit approach

A curated list on papers about combinatorial multi-armed bandit problems.

🐍 🔬 Fast Python implementation of various Kullback-Leibler divergences for 1D and 2D parametric distributions. Also provides optimized code for kl-UCB indexes

The 14th place submission in the Kaggle competition Santa-2020: The Candy Cane Contest

💫 Fast Julia implementation of various Kullback-Leibler divergences for 1D parametric distributions. 🏋 Also provides optimized code for kl-UCB indexes

Building recommender Systems using contextual bandit methods to address cold-start issue and online real-time learning

Source code for blog post on Thompson Sampling

Implementation of famous Bandits algortihm: Explore then commit, UCB & Thompson sampling in python.

Contextual Bandit algorithms for Warfarin Treatment

Implementation for paper "Locally Differentially Private (Contextual) Bandits Learning" (https://arxiv.org/abs/2006.00701)

C++ implementation of Multi-Armed Bandits (Gaussian and Bernoulli)

Bandit and Evolutionary Algorithms using Python

An illustrative project including some multi-armed bandit algorithms and contextual bandit algorithms

This repository aims at learning most popular MAB and CMAB algorithms and watch how they run. It is interesting for those wishing to start learning these topics.

Bandit algorithms in OCaml

DPE code - Code used in "Optimal Algorithms for Multiplayer Multi-Armed Bandits" (AISTATS 2020)