Ian En-Hsu Yen

发表

Learning Tensor Latent Features pdf

Pradeep Ravikumar, Xun Zheng, Rose Yu, 2018, ArXiv.

DEEP-TRIM: REVISITING L1 REGULARIZATION FOR CONNECTION PRUNING OF DEEP NETWORK

Shou-De Lin, Pradeep Ravikumar, Ian En-Hsu Yen, 2018 .

Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability

Jie Chen, Rui Yan, Ian En-Hsu Yen, 2016, KDD.

Dual Decomposed Learning with Factorwise Oracle for Structural SVM of Large Output Domain

Pradeep Ravikumar, Inderjit S. Dhillon, Kai Zhong, 2016, NIPS.

Tackling the Achilles Heel of Social Networks: Influence Propagation based Language Model Smoothing

Xiaohua Hu, Cheng-Te Li, Rui Yan, 2015, WWW.

Random Warping Series: A Random Features Method for Time-Series Embedding

Jinfeng Yi, Fangli Xu, Michael Witbrock, 2018, AISTATS.

Large-scale Submodular Greedy Exemplar Selection with Structured Similarity Matrices

Dmitry Malioutov, Abhishek Kumar, Ian En-Hsu Yen, 2016, UAI.

Scalable Spectral Clustering Using Random Binning Features

Charu C. Aggarwal, Yinglong Xia, Fangli Xu, 2018, KDD.

A Dual Augmented Block Minimization Framework for Learning with Limited Memory

Shou-De Lin, Ian En-Hsu Yen, Shan-Wei Lin, 2015, NIPS.

Representer Point Selection for Explaining Deep Neural Networks

Pradeep Ravikumar, Ian En-Hsu Yen, Chih-Kuan Yeh, 2018, NeurIPS.

Efficient Global String Kernel with Random Features: Beyond Counting Substructures

Charu C. Aggarwal, Shouling Ji, Liang Zhao, 2019, KDD.

Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent

Pradeep Ravikumar, Inderjit S. Dhillon, Cho-Jui Hsieh, 2015, NIPS.

A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models

Pradeep Ravikumar, Inderjit S. Dhillon, Xin Lin, 2015, ICML.

Indexed block coordinate descent for large-scale linear classification with limited memory

Shou-De Lin, Chun-Fu Chang, Ting-Wei Lin, 2013, KDD.

D2KE: From Distance to Kernel and Embedding pdf

Pradeep Ravikumar, Fangli Xu, Michael Witbrock, 2018, ArXiv.

MixLasso: Generalized Mixed Regression via Convex Atomic-Norm Regularization

Shou-De Lin, Pradeep Ravikumar, Kai Zhong, 2018, NeurIPS.

Minimizing FLOPs to Learn Efficient Sparse Representations pdf

Barnabás Póczos, Pradeep Ravikumar, Biswajit Paria, 2020, ICLR.

Scalable Exemplar Clustering and Facility Location via Augmented Block Coordinate Descent with Column Generation

Dmitry Malioutov, Abhishek Kumar, Ian En-Hsu Yen, 2016, AISTATS.

Scalable Global Alignment Graph Kernel Using Random Features: From Node Embedding to Graph Embedding

Charu C. Aggarwal, Yinglong Xia, Liang Zhao, 2019, KDD.

Loss Decomposition for Fast Learning in Large Output Spaces

Pradeep Ravikumar, Ian En-Hsu Yen, Satyen Kale, 2018, ICML.

Greedy Direction Method of Multiplier for MAP Inference of Large Output Domain

Pradeep Ravikumar, Inderjit S. Dhillon, Qi-Xing Huang, 2017, AISTATS.

Latent Feature Lasso

Shou-De Lin, Pradeep Ravikumar, Sung-En Chang, 2017, ICML.

Proximal Quasi-Newton for Computationally Intensive L1-regularized M-estimators

Pradeep Ravikumar, Inderjit S. Dhillon, Kai Zhong, 2014, NIPS.

Constant Nullspace Strong Convexity and Fast Convergence of Proximal Methods under High-Dimensional Settings

Pradeep Ravikumar, Inderjit S. Dhillon, Cho-Jui Hsieh, 2014, NIPS.

A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery

Pradeep Ravikumar, Inderjit S. Dhillon, Xin Lin, 2016, ICML.

Cheng-Te Li, Ian En-Hsu Yen, Hsun-Ping Hsieh, 2019, Knowledge and Information Systems.

D2KE: From Distance to Kernel and Embedding via Random Features For Structured Inputs

Pradeep Ravikumar, Lingfei Wu, Fangli Xu, 2018 .

PPDsparse: A Parallel Primal-Dual Sparse Method for Extreme Classification

Pradeep Ravikumar, Inderjit S. Dhillon, Eric P. Xing, 2017, KDD.

Doubly Greedy Primal-Dual Coordinate Descent for Sparse Empirical Risk Minimization

Pradeep Ravikumar, Inderjit S. Dhillon, Ian En-Hsu Yen, 2017, ICML.

Word Mover’s Embedding: From Word2Vec to Document Embedding pdf

Pradeep Ravikumar, Michael J. Witbrock, Fangli Xu, 2018, EMNLP.

Sparse Random Feature Algorithm as Coordinate Descent in Hilbert Space

Shou-De Lin, Pradeep Ravikumar, Inderjit S. Dhillon, 2014, NIPS.

Scalable Convex Multiple Sequence Alignment via Entropy-Regularized Dual Decomposition

Pradeep Ravikumar, Inderjit S. Dhillon, Jiong Zhang, 2017, AISTATS.

PD-Sparse : A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification

Pradeep Ravikumar, Inderjit S. Dhillon, Kai Zhong, 2016, ICML.

From Node Embedding to Graph Embedding: Scalable Global Graph Kernel via Random Features

Yinglong Xia, Michael Witbrock, Ian En-Hsu Yen, 2018 .