Code and datasets for the Tsetlin Machine
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Updated
Apr 26, 2024 - Cython
Code and datasets for the Tsetlin Machine
Contextual Bandits in R - simulation and evaluation of Multi-Armed Bandit Policies
Implements the Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, Weighted Tsetlin Machine, and Embedding Tsetlin Machine, with support for continuous features, multigranularity, clause indexing, and literal budget
A checkers reinforcement learning AI, and all the tools needed to train it.
Tutorial on the Convolutional Tsetlin Machine
Contextual bandit algorithm called LinUCB / Linear Upper Confidence Bounds as proposed by Li, Langford and Schapire
Multi-threaded implementation of the Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, and Weighted Tsetlin Machine, with support for continuous features and multigranularity.
Privacy-Preserving Bandits (MLSys'20)
Some visualizations of bandit algorithm outputs.
Bandit learning on top of Neural Monkey, an open-source tool for sequence learning in NLP built on TensorFlow. Bandit online learning objectives in branch bandits-acl (ACL17) and counterfactual learning objectives in branch acl-2018 (ACL18).
Client that handles the administration of StreamingBandit online, or straight from your desktop. Setup and run streaming (contextual) bandit experiments in your browser.
Based on Gentile-Li-Zapella article "Online Clustering of Bandits"
Implementing RL algorithms
Bayesian bandits in Python3.
A policy gradient approach to a multi-armed bandit problem
Detailed solution of solving wargames of over the wire which includes bandit and in future many more.
Leveling up on the Bandit Wargames
UCL COMP0089 Reinforcement Learning (2023/24)
A virtual whiteboard so I don't forget the ideas that come to me
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