Chih-Jen Lin

Ming-Wei Chang, Chih-Jen Lin, Ruby C. Weng, 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

Efficient test-point selection for scan-based BIST

Kwang-Ting Cheng, Chih-Jen Lin, Huan-Chih Tsai, 1998, IEEE Trans. Very Large Scale Integr. Syst..

Combination of feature engineering and ranking models for paper-author identification in KDD Cup 2013

Shou-De Lin, Chun-Liang Li, Hsuan-Tien Lin, 2013, KDD Cup '13.

Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel

Chih-Jen Lin, S. Sathiya Keerthi, Chih-Jen Lin, 2003, Neural Computation.

Training v-Support Vector Regression: Theory and Algorithms

Chih-Jen Lin, Chih-Chung Chang, Chih-Jen Lin, 2002, Neural Computation.

An improved GLMNET for l1-regularized logistic regression

Chia-Hua Ho, Chih-Jen Lin, Guo-Xun Yuan, 2011, J. Mach. Learn. Res..

Solving General Capacity Problem by Relaxed Cutting Plane Approach

Chih-Jen Lin, Shu-Cherng Fang, Soon-Yi Wu, 2001, Ann. Oper. Res..

Formulations of Support Vector Machines: A Note from an Optimization Point of View

Chih-Jen Lin, Chih-Jen Lin, 2001, Neural Computation.

Training nu-Support Vector Classifiers: Theory and Algorithms

Chih-Jen Lin, Chih-Chung Chang, Chih-Chung Chang, 2001, Neural Comput..

Scaling Up Machine Learning: Large-Scale Spectral Clustering with Map Reduce and MPI

Edward Y. Chang, Chih-Jen Lin, Wen-Yen Chen, 2011 .

Projected Gradient Methods for Nonnegative Matrix Factorization

Chih-Jen Lin, Chih-Jen Lin, 2007, Neural Computation.

Improving Ad Click Prediction by Considering Non-displayed Events

Chih-Jen Lin, Hong Zhu, Chih-Yao Chang, 2019, CIKM.

A Simple Decomposition Method for Support Vector Machines

Chih-Jen Lin, Chih-Wei Hsu, Chih-Jen Lin, 2002, Machine Learning.

A Unified Algorithm for One-Cass Structured Matrix Factorization with Side Information

Chih-Jen Lin, Inderjit S. Dhillon, Hsiang-Fu Yu, 2017, AAAI.

A Learning-Rate Schedule for Stochastic Gradient Methods to Matrix Factorization

Chih-Jen Lin, Wei-Sheng Chin, Yu-Chin Juan, 2015, PAKDD.

Integration of partial scan and built-in self-test

Yervant Zorian, Chih-Jen Lin, Sudipta Bhawmik, 1995, J. Electron. Test..

Dense Non-rigid Point-Matching Using Random Projections

Chih-Jen Lin, Dennis DeCoste, Raffay Hamid, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

A fast parallel SGD for matrix factorization in shared memory systems

Chih-Jen Lin, Wei-Sheng Chin, Yu-Chin Juan, 2013, RecSys.

Incomplete Cholesky Factorizations with Limited Memory

Chih-Jen Lin, Jorge J. Moré, J. J. Moré, 1999, SIAM J. Sci. Comput..

Leave-One-Out Bounds for Support Vector Regression Model Selection

Ming-Wei Chang, Chih-Jen Lin, Ming-Wei Chang, 2005, Neural Computation.

Large-Scale Linear RankSVM

Chih-Jen Lin, Ching-Pei Lee, Chih-Jen Lin, 2014, Neural Computation.

Dual Coordinate-Descent Methods for Linear One-Class SVM and SVDD

Chih-Jen Lin, Hung-Yi Chou, Pin-Yen Lin, 2020, SDM.

On the convergence of the decomposition method for support vector machines

Chih-Jen Lin, Chih-Jen Lin, Chih-Wei Hsu, 2001, IEEE Trans. Neural Networks.

A dual coordinate descent method for large-scale linear SVM

Chih-Jen Lin, Cho-Jui Hsieh, Kai-Wei Chang, 2008, ICML '08.

A comparison of methods for multiclass support vector machines

Chih-Jen Lin, Chih-Wei Hsu, Chih-Jen Lin, 2002, IEEE Trans. Neural Networks.

Preconditioned Conjugate Gradient Methods in Truncated Newton Frameworks for Large-scale Linear Classification

Chih-Jen Lin, Chih-Yang Hsia, Wei-Lin Chiang, 2018, ACML.

An Ensemble of Three Classifiers for KDD Cup 2009: Expanded Linear Model, Heterogeneous Boosting, and Selective Naive Bayes

Shou-De Lin, Hsuan-Tien Lin, Chih-Jen Lin, 2009, KDD Cup.

A Guide to Support Vector Machines

Chih-Jen Lin, Chih-Jen Lin, 2006 .

Field-aware Factorization Machines for CTR Prediction

Chih-Jen Lin, Wei-Sheng Chin, Yu-Chin Juan, 2016, RecSys.

Probability Estimates for Multi-class Classification by Pairwise Coupling

Chih-Jen Lin, Ruby C. Weng, Ting-Fan Wu, 2003, J. Mach. Learn. Res..

IJCNN 2001 challenge: generalization ability and text decoding

Chih-Jen Lin, Chih-Chung Chang, Chih-Jen Lin, 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

Fast Matrix-Vector Multiplications for Large-Scale Logistic Regression on Shared-Memory Systems

Chih-Jen Lin, Wei-Lin Chiang, Mu-Chu Lee, 2015, 2015 IEEE International Conference on Data Mining.

Ranking individuals by group comparisons

Chih-Jen Lin, Tzu-Kuo Huang, Ruby C. Weng, 2006, ICML.

Linear and Kernel Classification: When to Use Which?

Chih-Jen Lin, Hsin-Yuan Huang, Chih-Jen Lin, 2016, SDM.

Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines

Chih-Jen Lin, Cho-Jui Hsieh, Kai-Wei Chang, 2008, J. Mach. Learn. Res..

Feature Extraction, Foundations and Applications

Chih-Jen Lin, Y. W. Chen, Y. W. Chen, 2006 .

A sequential dual method for large scale multi-class linear svms

Chih-Jen Lin, Cho-Jui Hsieh, Kai-Wei Chang, 2008, KDD.

A Study on SMO-Type Decomposition Methods for Support Vector Machines

Chih-Jen Lin, Pai-Hsuen Chen, Rong-En Fan, 2006, IEEE Transactions on Neural Networks.

An Efficient Newton Method for Extreme Similarity Learning with Nonlinear Embeddings pdf

Chih-Jen Lin, Pengrui Quan, Yu-Sheng Li, 2020, ArXiv.

Dual coordinate descent methods for logistic regression and maximum entropy models

Chih-Jen Lin, Hsiang-Fu Yu, Fang-Lan Huang, 2011, Machine Learning.

LIBMF: A Library for Parallel Matrix Factorization in Shared-memory Systems

Chih-Jen Lin, Wei-Sheng Chin, Yu-Chin Juan, 2016, J. Mach. Learn. Res..

LIBLINEAR: A Library for Large Linear Classification

Chih-Jen Lin, Cho-Jui Hsieh, Kai-Wei Chang, 2008, J. Mach. Learn. Res..

A Generalized Bradley-Terry Model: From Group Competition to Individual Skill

Chih-Jen Lin, Tzu-Kuo Huang, Ruby C. Weng, 2004, NIPS.

Load Forecasting Using Support Vector Machines: A Study on EUNITE Competition 2001

Ming-Wei Chang, Chih-Jen Lin, Bo-Juen Chen, 2004, IEEE Transactions on Power Systems.

Enhanced controllability for IDDQ test sets using partial scan

Chih-Jen Lin, Sudipta Bhawmik, Tapan J. Chakraborty, 1991, 28th ACM/IEEE Design Automation Conference.

Support Vector Machines

Chih-Jen Lin, Po-Wei Wang, Chih-Jen Lin, 2014, Data Classification: Algorithms and Applications.

A hybrid algorithm for test point selection for scan-based BIST

Kwang-Ting Cheng, Chih-Jen Lin, Huan-Chih Tsai, 1997, DAC.

Incremental and decremental training for linear classification

Cheng-Hao Tsai, Chieh-Yen Lin, Chih-Jen Lin, 2014, KDD.

Distributed Newton Methods for Regularized Logistic Regression

Chih-Jen Lin, Wei-Sheng Chin, Yu-Chin Juan, 2015, PAKDD.

The NTU Toolkit and Framework for High-Level Feature Detection at TRECVID 2007

Yi-Hsuan Yang, Chih-Jen Lin, Yung-Yu Chuang, 2007, TRECVID.

Large-Scale Video Summarization Using Web-Image Priors

Chih-Jen Lin, Neel Sundaresan, Raffay Hamid, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

Large-scale linear support vector regression

Chia-Hua Ho, Chih-Jen Lin, Chih-Jen Lin, 2012, J. Mach. Learn. Res..

Limited-memory Common-directions Method for Distributed Ll-regularized Linear Classification

Chih-Jen Lin, Yu-Sheng Li, Wei-Lin Chiang, 2018, SDM.

Generalized Bradley-Terry Models and Multi-Class Probability Estimates

Chih-Jen Lin, Tzu-Kuo Huang, Ruby C. Weng, 2006, J. Mach. Learn. Res..

Large Linear Classification When Data Cannot Fit in Memory

Chih-Jen Lin, Cho-Jui Hsieh, Kai-Wei Chang, 2011, TKDD.

A predictor corrector method for semi-definite linear programming

Chih-Jen Lin, Romesh. Saigal, R. Saigal, 1995 .

Cross-generation and cross-laboratory predictions of Affymetrix microarrays by rank-based methods

Chih-Jen Lin, Chien-Yu Chen, Yu-Ting Liu, 2008, J. Biomed. Informatics.

A note on Platt’s probabilistic outputs for support vector machines

Hsuan-Tien Lin, Chih-Jen Lin, Ruby C. Weng, 2007, Machine Learning.

Errata to "A comparison of methods for multiclass support vector machines"

Chih-Jen Lin, Chih-Jen Lin, 2002, IEEE Trans. Neural Networks.

Designing, Analyzing and Exploiting Stake-Based Social Networks

Shou-De Lin, Chih-Jen Lin, Tsung-Ting Kuo, 2010, 2010 International Conference on Advances in Social Networks Analysis and Mining.

Trust region Newton methods for large-scale logistic regression

Chih-Jen Lin, S. Sathiya Keerthi, Ruby C. Weng, 2007, ICML '07.

Iterative Scaling and Coordinate Descent Methods for Maximum Entropy

Chih-Jen Lin, Cho-Jui Hsieh, Kai-Wei Chang, 2009, ACL.

Active learning strategies using SVMs

Chia-Hua Ho, Chih-Jen Lin, Ming-Hen Tsai, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Large-scale logistic regression and linear support vector machines using spark

Cheng-Hao Tsai, Chieh-Yen Lin, Chih-Jen Lin, 2014, 2014 IEEE International Conference on Big Data (Big Data).

Newton's Method for Large Bound-Constrained Optimization Problems

Chih-Jen Lin, Jorge J. Moré, J. J. Moré, 1999, SIAM J. Optim..

Novel Models and Ensemble Techniques to Discriminate Favorite Items from Unrated Ones for Personalized Music Recommendation

Shou-De Lin, Chun-Liang Li, Hsuan-Tien Lin, 2012, KDD Cup.

Newton Methods for Convolutional Neural Networks

Chih-Jen Lin, Chien-Chih Wang, Kent Loong Tan, 2018, ACM Trans. Intell. Syst. Technol..

A Study on L2-Loss (Squared Hinge-Loss) Multiclass SVM

Chih-Jen Lin, Ching-Pei Lee, Chih-Jen Lin, 2013, Neural Computation.

PSBIST: A partial-scan based built-in self-test scheme

Yervant Zorian, Chih-Jen Lin, Sudipta Bhawmik, 1993, Proceedings of IEEE International Test Conference - (ITC).

Naive Parallelization of Coordinate Descent Methods and an Application on Multi-core L1-regularized Classification

Chih-Jen Lin, Yu-Chin Juan, Yong Zhuang, 2018, CIKM.

Working Set Selection Using Second Order Information for Training Support Vector Machines

Chih-Jen Lin, Pai-Hsuen Chen, Rong-En Fan, 2005, J. Mach. Learn. Res..

A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification

Chih-Jen Lin, Cho-Jui Hsieh, Kai-Wei Chang, 2010, J. Mach. Learn. Res..

Large-scale Kernel RankSVM

Chih-Jen Lin, Tzu-Ming Kuo, Ching-Pei Lee, 2014, SDM.

Large linear classification when data cannot fit in memory

Chih-Jen Lin, Hsiang-Fu Yu, Cho-Jui Hsieh, 2011, IJCAI 2011.

Parallel Spectral Clustering

Edward Y. Chang, Chih-Jen Lin, Wen-Yen Chen, 2008, ECML/PKDD.

Optical Coating Designs Using the Family Competition Evolutionary Algorithm

Cheng-Yan Kao, Jorng-Tzong Horng, Chih-Jen Lin, 2001, Evolutionary Computation.

Training and Testing Low-degree Polynomial Data Mappings via Linear SVM

Chih-Jen Lin, Cho-Jui Hsieh, Kai-Wei Chang, 2010, J. Mach. Learn. Res..

Parallel Dual Coordinate Descent Method for Large-scale Linear Classification in Multi-core Environments

Chih-Jen Lin, Wei-Lin Chiang, Mu-Chu Lee, 2016, KDD.

Experiences and lessons in developing industry-strength machine learning and data mining software

Chih-Jen Lin, 2012, KDD.

A tutorial on?-support vector machines

Chih-Jen Lin, Pai-Hsuen Chen, Bernhard Sch lkopf, 2005 .

A Bayesian Approximation Method for Online Ranking

Chih-Jen Lin, Ruby C. Weng, Chih-Jen Lin, 2011, J. Mach. Learn. Res..

The Common-directions Method for Regularized Empirical Risk Minimization

Chih-Jen Lin, Ching-Pei Lee, Po-Wei Wang, 2019, J. Mach. Learn. Res..

Distributed Newton Methods for Deep Neural Networks

Chih-Jen Lin, S. Sundararajan, S. Sathiya Keerthi, 2018, Neural Computation.

A study on reduced support vector machines

Chih-Jen Lin, Kuan-Ming Lin, Chih-Jen Lin, 2003, IEEE Trans. Neural Networks.

Chapter 12 Combining SVMs with Various Feature Selection Strategies

Chih-Jen Lin, Yi-Wei Chen, 2006 .

A formal analysis of stopping criteria of decomposition methods for support vector machines

Chih-Jen Lin, Chih-Jen Lin, 2002, IEEE Trans. Neural Networks.

Training Support Vector Machines via SMO-Type Decomposition Methods

Chih-Jen Lin, Pai-Hsuen Chen, Rong-En Fan, 2005, ALT.

Combining SVMs with Various Feature Selection Strategies

Chih-Jen Lin, Yi-Wei Chen, Chih-Jen Lin, 2006, Feature Extraction.

Limited-memory Common-directions Method for Distributed Optimization and its Application on Empirical Risk Minimization

Chih-Jen Lin, Weizhu Chen, Po-Wei Wang, 2017, SDM.

A Study on Threshold Selection for Multi-label Classification

Chih-Jen Lin, Rong-En Fan, Chih-Jen Lin, 2007 .

Analysis of switching dynamics with competing support vector machines

Ming-Wei Chang, Chih-Jen Lin, Ruby Chiu-Hsing Weng, 2004, IEEE Transactions on Neural Networks.

Special issue on support vector machines

Chih-Jen Lin, Colin Campbell, S. Sathiya Keerthi, 2003, Neurocomputing.

An infeasable start predictor corrector method for semi-definite linear programming

Chih-Jen Lin, Romesh. Saigal, R. Saigal, 1995 .

Fine‐grained protein fold assignment by support vector machines using generalized npeptide coding schemes and jury voting from multiple‐parameter sets

Chih-Jen Lin, Jung-Ying Wang, Jinn-Moon Yang, 2003, Proteins.

Subsampled Hessian Newton Methods for Supervised Learning

Chih-Jen Lin, Chien-Chih Wang, Chun-Heng Huang, 2015, Neural Computation.

Parallel Spectral Clustering in Distributed Systems

Edward Y. Chang, Chih-Jen Lin, Wen-Yen Chen, 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Decomposition Methods for Linear Support Vector Machines

Chih-Jen Lin, Kai-Min Chung, Tony Sun, 2003, Neural Computation.

LIBSVM: A library for support vector machines

Chih-Jen Lin, Chih-Chung Chang, Chih-Jen Lin, 2011, TIST.

Iterative Scaling and Coordinate Descent Methods for Maximum Entropy

Chih-Jen Lin, Cho-Jui Hsieh, Kai-Wei Chang, 2009, ACL/IJCNLP.

Efficient Optimization Methods for Extreme Similarity Learning with Nonlinear Embeddings

Chih-Jen Lin, Pengrui Quan, Yu-Sheng Li, 2021, KDD.

A Two-Level Decomposition Framework Exploiting First and Second Order Information for SVM Training Problems

Chih-Jen Lin, Marco Sciandrone, Giulio Galvan, 2021, J. Mach. Learn. Res..

A Dual Affine Scaling Based Algorithm for Solving Linear Semi-Infinite Programming Problems

Chih-Jen Lin, Shu-Cherng Fang, Soon-Yi Wu, 1994 .

Solving quadratic semi-infinite programming problems by using relaxed cutting-plane scheme

Chih-Jen Lin, Shu-Cherng Fang, Soon-Yi Wu, 2001 .

Relaxed Cutting Plane Method for Solving Linear Semi-Infinite Programming Problems

Chih-Jen Lin, Shu-Cherng Fang, Soon-Yi Wu, 1998 .

Asymptotic Behaviors of Support Vector Machines with

Chih-Jen Lin, S. Sathiya Keerthi, 2003 .

Product Title Classification versus Text Classification

Chia-Hua Ho, Chih-Jen Lin, Hsiang-Fu Yu, 2012 .

Implementation of an inexact approach to solving linear semi-infinite programming problems

Chih-Jen Lin, Shu-Cherng Fang, Soon-Yi Wu, 1995 .

Analytic Center Based Cutting Plane Method for Linear Semi-Infinite Programming

Chih-Jen Lin, Shu-Cherng Fang, Soon-Yi Wu, 2001 .