There are 8 repositories under contextual-bandits topic.
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
Python implementations of contextual bandits algorithms
Online Deep Learning: Learning Deep Neural Networks on the Fly / Non-linear Contextual Bandit Algorithm (ONN_THS)
:bust_in_silhouette: Multi-Armed Bandit Algorithms Library (MAB) :cop:
Contextual Bandits in R - simulation and evaluation of Multi-Armed Bandit Policies
🐈⬛ Contextual bandits library for continuous action trees with smoothing in JAX
Code accompanying the paper "Learning Permutations with Sinkhorn Policy Gradient"
Contextual bandit algorithm called LinUCB / Linear Upper Confidence Bounds as proposed by Li, Langford and Schapire
implement basic and contextual MAB algorithms for recommendation system
Privacy-Preserving Bandits (MLSys'20)
Contextual Multi-Armed Bandit Platform for Scoring, Ranking & Decisions
Study of the paper 'Neural Thompson Sampling' published in October 2020
Implementation of provably Rawlsian fair ML algorithms for contextual bandits.
lightweight contextual bandit library for ts/js
Easily Score & Rank Codable Objects with ML
OCaml bindings to vowpal wabbit
The Contextual Meta-Bandit (CMB) can be used to select models using the context with online learning based on Reiforcement Learning problem. It's can be used for recommender system ensemble, A/B test, and other dynamic model selector problem.
Building recommender Systems using contextual bandit methods to address cold-start issue and online real-time learning
Code to trade the financial markets using Contextual Bandits
Client that handles the administration of StreamingBandit online, or straight from your desktop. Setup and run streaming (contextual) bandit experiments in your browser.
Contextual Multi-Armed Bandit Item/Reward Tracker & Model Trainer
Business Process Improvement with Reinforcement Learning and Human-in-the-Loop.
Contextual multi-armed bandit recommender system using Vowpal Wabbit
Experiment results using MAB algorithms in Yahoo! Front Page Today Module User Click Log dataset
Reduction-based machine learning framework with a focus on contextual bandits
Experiments for paper "Online Learning with Costly Features in Non-stationary Environments"
Code of the NeuralBandit paper