Online Deep Learning: Learning Deep Neural Networks on the Fly / Non-linear Contextual Bandit Algorithm (ONN_THS)

👤 Multi-Armed Bandit Algorithms Library (MAB) 👮

This repository contains the source code for “Thompson sampling efficient multiobjective optimization” (TSEMO).

Library for multi-armed bandit selection strategies, including efficient deterministic implementations of Thompson sampling and epsilon-greedy.

Thompson Sampling Tutorial

All codes, both created and optimized for best results from the SuperDataScience Course

In This repository I made some simple to complex methods in machine learning. Here I try to build template style code.

Bandit algorithms

🌾 OAT: Online AlignmenT for LLMs

pyrff: Python implementation of random fourier feature approximations for gaussian processes

Offline evaluation of multi-armed bandit algorithms

Study of the paper 'Neural Thompson Sampling' published in October 2020

A Julia Package for providing Multi Armed Bandit Experiments

Bayesian Optimization for Categorical and Continuous Inputs

Implementations of basic concepts dealt under the Reinforcement Learning umbrella. This project is collection of assignments in CS747: Foundations of Intelligent and Learning Agents (Autumn 2017) at IIT Bombay

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

Thompson Sampling based Monte Carlo Tree Search for MDPs and POMDPs

Optimizing the best Ads using Reinforcement learning Algorithms such as Thompson Sampling and Upper Confidence Bound.

Author's implementation of the paper Correlated Age-of-Information Bandits.