Pinned Repositories
Collective-Low-rank-Subspace
Dual-Low-rank-Decompostion
AAAI 16 work
grpsel
:exclamation: This is a read-only mirror of the CRAN R package repository. grpsel — Group Subset Selection. Homepage: https://github.com/ryan-thompson/grpsel Report bugs for this package: https://github.com/ryan-thompson/grpsel/issues
lihang-code
《统计学习方法》的代码实现
Low-rank-Common-Subspace
ICDM-14 work
Mplasso
Pliable lasso for multinomial logistic regression
MvCCDA
Multi-view Common Component Discriminant Analysis for Cross-view Classification
MvHE
Multi-view Hybrid Embedding: A Divide-and-Conquer Approach
nbm-spam
Training and evaluating NBM and SPAM for interpretable machine learning.
node
Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data
Penny-hust's Repositories
Penny-hust/nbm-spam
Training and evaluating NBM and SPAM for interpretable machine learning.
Penny-hust/STATS_GAM
This procedure estimates a generalied additive model. GAM s are linear in predictor terms that can be simple variables or vario us kinds of splines or polynomials. You can specify the error distri bution and link function for the model.
Penny-hust/grpsel
:exclamation: This is a read-only mirror of the CRAN R package repository. grpsel — Group Subset Selection. Homepage: https://github.com/ryan-thompson/grpsel Report bugs for this package: https://github.com/ryan-thompson/grpsel/issues
Penny-hust/Mplasso
Pliable lasso for multinomial logistic regression
Penny-hust/node
Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data
Penny-hust/ranking
Learning to Rank in TensorFlow
Penny-hust/lihang-code
《统计学习方法》的代码实现
Penny-hust/PliableLasso
Python implementation of the pliable lasso
Penny-hust/Collective-Low-rank-Subspace
Penny-hust/MvHE
Multi-view Hybrid Embedding: A Divide-and-Conquer Approach
Penny-hust/MvCCDA
Multi-view Common Component Discriminant Analysis for Cross-view Classification
Penny-hust/Transferable-Adversarial-Training
Code release for Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers (ICML2019)
Penny-hust/VIGAN
PyTorch implementation of VIGAN
Penny-hust/Dual-Low-rank-Decompostion
AAAI 16 work
Penny-hust/Low-rank-Common-Subspace
ICDM-14 work