FTRL proximal algorithm according to McMahan et al. 2013
Code to accompany the paper "AMP-Inspired Deep Networks for Sparse Linear Inverse Problems"
Python numerical optimization toolbox
Some fundamental machine learning and data-analysis techniques are explained through realistic ex...
rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compa...
Minimal Learning Machine implementation using the scikit-learn API.
Extends scikit-learn with new models, transformers, metrics, plotting.
Machine Learning algorithms in Python and C/C++ written from scratch using the respective standar...
Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in ...
[ACL 2024] Self-Training with Direct Preference Optimization Improves Chain-of-Thought Reasoning
A PyTorch reinforcement learning library for generalizable and reproducible algorithm implementat...
Code for "Structured Sparsity Inducing Adaptive Optimizers for Deep Learning" in PyTorch
Implementation of different ML Algorithms from scratch, written in Python 3.x
Hyperparameter optimization with approximate gradient
PFRL: a PyTorch-based deep reinforcement learning library
Framework for Analysis of Class-Incremental Learning with 12 state-of-the-art methods and 3 basel...