Topic: "rademacher-complexity"
Decadz/Genetic-Programming-with-Rademacher-Complexity
Code for the GP-RC algorithm presented in "Genetic Programming with Rademacher Complexity for Symbolic Regression" (IEEE CEC2019). Paper Link: https://ieeexplore.ieee.org/document/8790341
Language: Python - Size: 35.1 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 11 - Forks: 4
RSv618/rademacher-anti-serum
An implementation of Giuseppe Paleologo's Rademacher Antiserum, designed to assess strategy performance consistency through Rademacher complexity and RAS-adjusted Sharpe Ratios. This code evaluates strategy robustness by applying Rademacher random vectors for anti-overfitting analysis.
Language: Python - Size: 745 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 2 - Forks: 0
mrvnthss/QuantFoundationsAI
Lecture notes taken in the Quantitative Foundations of Artificial Intelligence class in Fall 2023, taught by Prof. Dr. Ludger Overbeck at Justus Liebig University Giessen.
Language: TeX - Size: 174 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 2 - Forks: 0
superlj666/Multi-Class-Learning-From-Theory-to-Algorithm
Codes and experiments for "Multi-Class Learning: From Theory to Algorithm", published in NeurIPS 2018
Language: MATLAB - Size: 1.87 MB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 1 - Forks: 0
nr-parikh/machine_learning
Repository dealing with key concepts in Machine Learning
Language: Python - Size: 16.6 MB - Last synced at: about 2 years ago - Pushed at: over 7 years ago - Stars: 1 - Forks: 0
acdmammoths/Bavarian-code
Code for the paper "Bavarian: Betweenness Centrality Approximation with Variance-Aware Rademacher Averages", by Chloe Wohlgemuth, Cyrus Cousins, and Matteo Riondato, appearing in ACM KDD'21 and ACM TKDD'23
Language: C++ - Size: 76.3 MB - Last synced at: almost 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0
superlj666/Multi-Class-Learning-using-Unlabeled-Samples-Theory-and-Algorithm
Codes and experiments for "Multi-Class Learning using Unlabeled Samples: Theory and Algorithm", published in IJCAI 2019
Language: MATLAB - Size: 20.3 MB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 0 - Forks: 0
superlj666/Learning-Vector-valued-Functions-with-Local-Rademacher-Complexity
Codes and experiments for the paper "Learning Vector-valued Functions with Local Rademacher Complexity". Preprint.
Language: MATLAB - Size: 182 KB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 0 - Forks: 0