learning-theory

Fast and flexible AutoML with learning guarantees.

Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning

🔬 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

Repository for collection of research papers on privacy.

Distributional Generalization in NLP. A roadmap.

AI Learning Hub for Machine Learning, Deep Learning, Computer Vision and Statistics

Model Zoos for Continual Learning (ICLR 22)

Formal Psychological Models of Categorization and Learning

Material for 'Mathematics of Deep Learning Workshop' (Invited Talk)

Scinis-learn is a package of non-OOP functions for Machine Learning developed by young Moroccan AI engineering students from scratch.

Code for paper "Efficient Sparse Coding using Hierarchical Riemannian Pursuit," in IEEE Transactions on Signal Processing, Y. Xue, V. K. N. Lau and S. Cai, doi: 10.1109/TSP.2021.3093769.

#UAI2020 Codes for PAC-Bayesian Contrastive Unsupervised Representation Learning

Solutions and Codes Example for Assignments of Machine Learning Foundation, Fall 2020, National Taiwan University

Official implementation of On-Demand Sampling: Learning Optimally from Multiple Distributions (Neurips 2022)

Implementation of https://arxiv.org/abs/2106.03027

A Python implementation of the Neural Tangent Kernel (jacot et al, 2018)

source code of NeurIPS 2021 paper: "Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound"

A program that learns your polynomial using just two queries

PAC-Bayesian Binary Activated Deep Neural Networks

This repository contains the code to reproduce all of the results in our paper: Making Learners (More) Monotone, T J Viering, A Mey, M Loog, IDA 2020.