pac-learning

Here are 9 public repositories matching this topic...

Robby955 / FormalSLT

Machine-checked statistical learning theory in Lean 4: empirical-Bernstein and time-uniform PAC-Bayes, Markov risk, Rademacher/VC, and Dudley chaining.

machine-learning theorem-proving mathematics statistical-learning formal-verification pac-bayes pac-learning lean4 concentration-inequalities mathlib4

Updated Aug 20, 2026
Lean

marfvr / pdfa-learning

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Implementation of PDFAs and PDFA learning algorithm.

automata pac automaton pdfa pfa probabilistic-automata pac-learning probabilistic-automaton

Updated Jan 8, 2021
Python

diochnos / pac-imbalanced

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Learning Reliable Rules under Class Imbalance (SDM 2021)

imbalanced-data imbalanced-learning uniform-distribution find-s pac-learning monotone-conjunctions swapping-algorithm

Updated Jan 20, 2021
C++

yafo1948 / ML_Reichman_Spring2022

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Machine Learning for Data 3141 Reichman University Spring 2022 - 6 Homework Projects

svm linear-regression ml naive-bayes-classifier logistic-regression gradient-descent k-means polynomial-regression knn decision-tree-classifier em-algorithm multivariate-regression lagrange-multipliers unsupervised-machine-learning mle-estimation pac-learning k-fold-cross-validation mean-squared-error

Updated Nov 8, 2022
Jupyter Notebook

LiorErenreich / Introduction-to-Machine-Learning-TAU

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My solutions to the assignments in Introduction to Machine Learning course at Tel Aviv University (course number: 0368-3235)

machine-learning neural-networks gradient-descent academic-project convex deep-convolutional-neural-networks pac-learning

Updated Jun 17, 2023
Python

sherwinshen / learning_OTA_by_testing

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🔨 A prototype tool on learning DOTAs by testing.

active-learning timed-automata pac-learning

Updated Mar 29, 2021
Python

Razvan48 / Homework-Advanced-Machine-Learning-AML

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Homework Advanced Machine Learning (AML), MSc Artificial Intelligence, Year 1, Semester 2, Faculty of Mathematics and Computer Science, University of Bucharest

agnostic learnable pac-learning vc-dimension

Updated May 5, 2026

mbastola / PAC-Learning-foundations-in-AI

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This project dives into mathematical foundations of PAC learning theory while adding Python examples that make core ideas like generalization, sample complexity, VC dimension, halfspaces, perceptrons, and logical semantics executable and easier to inspect.

perceptron learning-theory generalization pac-learning vc-dimension sample-complexity ai-foundations theoretical-machine-learning probably-approximately-correct-learning pac-semantics