EarlyStoppingRKHS

Algorithms optimizer

Code for analyzing early stopping in kernel boosting algorithms

Code for production of the plots in the paper "Early stopping for kernel boosting algorithms: A general analysis with localized complexities"

GitHub

0 stars
2 watching
0 forks
last commit: almost 7 years ago
Linked from 1 awesome list


Backlinks from these awesome lists:

Related projects:

Repository Description Stars
springdaisy/gbdt An implementation of Gradient Boosted Decision Trees with sparse output for high-dimensional data 0
jiangoforit/yellowfin_pytorch An optimizer that automatically tunes momentum and learning rate using local quadratic approximation. 287
younghjung/onlinemlrboostingwithvfdt An implementation of online multi-label ranking boosting using VFDT as weak learners 4
hannah-zhou/optimization_algorithm A comprehensive collection of optimization algorithms implemented in MATLAB 178
sjsingh91/ib-cnn A library implementing a learning algorithm for improving classification accuracy with incremental updates and ensemble methods using neural networks 2
rentruewang/koila A lightweight wrapper around PyTorch to prevent CUDA out-of-memory errors and optimize model execution 1,821
cluebenchmark/electra Trains and evaluates a Chinese language model using adversarial training on a large corpus. 140
damirsvrtan/fasterer Tools for optimizing Ruby code performance 1,812
chasedehan/boostaroota An algorithm for fast feature selection using XGBoost and other tree-based classifiers 219
jiahuadong/fiss Implementations of federated incremental semantic segmentation in PyTorch. 33
shengroup/fmab Federated Multi-armed Bandits algorithm implementation for simulating cognitive radio systems and recommender systems 9
moskomule/eve.pytorch An implementation of an optimization algorithm inspired by a 2016 research paper 33
debcaldarola/fedsam Improving generalization in federated learning by seeking flat minima through optimization techniques 79
xidongwu/federated-minimax-and-conditional-stochastic-optimization This project presents optimization techniques for federated learning and minimax games in the context of machine learning 0
kadenzipfel/bytepeep An optimizer tool for low-level smart contract bytecode 119