superlj666
Associate Senior Researcher at Institute of Information Engineering, CAS
IIE, CASBeijing, China
Pinned Repositories
Agnostic-DKRR
Approximate-Manifold-Regularization-Scalable-Algorithm-and-Generalization-Analysis
Experiement in paper "Approximate Manifold Regularization: Scalable Algorithm and Generalization Analysis", published in IJCAI 2019
Automated-Spectral-Kernel-Learning
Codes and experiments for paper "Automated Spectral Kernel Learning". Preprint.
Distributed-Learning-with-Random-Features
Codes and experiments for paper "Distributed Learning with Random Features". Preprint.
Learning-Vector-valued-Functions-with-Local-Rademacher-Complexity
Codes and experiments for the paper "Learning Vector-valued Functions with Local Rademacher Complexity". Preprint.
Multi-Class-Learning-From-Theory-to-Algorithm
Codes and experiments for "Multi-Class Learning: From Theory to Algorithm", published in NeurIPS 2018
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
NGAE
The implementation of NGAE
Ridgeless-Regression-with-Random-Features
superlj666.github.io
Github Pages template for academic personal websites
superlj666's Repositories
superlj666/superlj666.github.io
Github Pages template for academic personal websites
superlj666/Automated-Spectral-Kernel-Learning
Codes and experiments for paper "Automated Spectral Kernel Learning". Preprint.
superlj666/Ridgeless-Regression-with-Random-Features
superlj666/Distributed-Learning-with-Random-Features
Codes and experiments for paper "Distributed Learning with Random Features". Preprint.
superlj666/Approximate-Manifold-Regularization-Scalable-Algorithm-and-Generalization-Analysis
Experiement in paper "Approximate Manifold Regularization: Scalable Algorithm and Generalization Analysis", published in IJCAI 2019
superlj666/Learning-Vector-valued-Functions-with-Local-Rademacher-Complexity
Codes and experiments for the paper "Learning Vector-valued Functions with Local Rademacher Complexity". Preprint.
superlj666/Multi-Class-Learning-From-Theory-to-Algorithm
Codes and experiments for "Multi-Class Learning: From Theory to Algorithm", published in NeurIPS 2018
superlj666/NGAE
The implementation of NGAE
superlj666/Agnostic-DKRR
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
superlj666/Agnostic-RF
Experiments for the TNNLS paper "Optimal Convergence for Agnostic Kernel Learning with Random Features"
superlj666/CSKN
Convolutional Spectral Kernel Network
superlj666/DISTRE
Fine-tuning Pre-Trained Transformer Language Models to Distantly Supervised Relation Extraction - ACL 2019
superlj666/DNystroem
Experiments for the JMLR paper "Optimal Convergence Rates for Distributed Nystroem Approximation"
superlj666/FALKON_paper
FALKON implementation used in the experimental section of "FALKON: An Optimal Large Scale Kernel Method"
superlj666/FedNS
superlj666/Max-Diversity-Distributed-Learning-Theory-and-Algorithms
Codes and experiments for the paper "Max-Discrepancy Distributed Learning: Fast Risk Bounds and Algorithms"
superlj666/NonlinearHDA
superlj666/rdpwrap.ini
RDPWrap.ini for RDP Wrapper Library by Stas'M