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.
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Updated
May 23, 2024 - C++
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.
Contextual Multi-Armed Bandit Reward Tracker & Model Trainer
Easily Score & Rank JSON-Encodable Objects with ML
This project encompasses my master's thesis titled: Audio-Visual Attention Modeling via Reinforcement Learning.
TF-Agents: A reliable, scalable and easy to use TensorFlow library for Contextual Bandits and Reinforcement Learning.
[IJAIT 2021] MABWiser: Contextual Multi-Armed Bandits Library
This project aims to implement those algorithms from different papers related to online learning
Experiments for paper "Online Learning with Costly Features in Non-stationary Environments"
Multi-objective Stochastic Linear Bandits
lightweight contextual bandit library for ts/js
Reduction-based machine learning framework with a focus on contextual bandits
Open Bandit Pipeline: a python library for bandit algorithms and off-policy evaluation
Contextual Bandit Engine
Easily Score & Rank Codable Objects with ML
Python implementations of contextual bandits algorithms
Contextual Multi-Armed Bandit Platform for Scoring, Ranking & Decisions
Code for the paper "Truncated LinUCB for Stochastic Linear Bandits"
Proof of concept for a recommender system for Yelp, using bandit algorithms.
Business Process Improvement with Reinforcement Learning and Human-in-the-Loop.
Official Implementation of On Optimal Private Online Stochastic Optimization and High Dimensional Decision Making
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