On the limited memory BFGS method for large scale optimization
Mathematical Programming: Series A and B
A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Inducing Features of Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of truncated-Newton methods
Journal of Computational and Applied Mathematics - Special issue on numerical analysis 2000 Vol. IV: optimization and nonlinear equations
Newton's Method for Large Bound-Constrained Optimization Problems
SIAM Journal on Optimization
RCV1: A New Benchmark Collection for Text Categorization Research
The Journal of Machine Learning Research
A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs
The Journal of Machine Learning Research
A comparison of algorithms for maximum entropy parameter estimation
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Training linear SVMs in linear time
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Deciphering mobile search patterns: a study of Yahoo! mobile search queries
Proceedings of the 17th international conference on World Wide Web
Contextual advertising by combining relevance with click feedback
Proceedings of the 17th international conference on World Wide Web
Optimized cutting plane algorithm for support vector machines
Proceedings of the 25th international conference on Machine learning
Trust Region Newton Method for Logistic Regression
The Journal of Machine Learning Research
Improving object detection by removing noisy samples from training sets
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Learning to analyze binary computer code
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Efficient Object Pixel-Level Categorization Using Bag of Features
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Optimized Cutting Plane Algorithm for Large-Scale Risk Minimization
The Journal of Machine Learning Research
Fast online learning through offline initialization for time-sensitive recommendation
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Robust weighted kernel logistic regression in imbalanced and rare events data
Computational Statistics & Data Analysis
Fast and Scalable Local Kernel Machines
The Journal of Machine Learning Research
Learning to aggregate vertical results into web search results
Proceedings of the 20th ACM international conference on Information and knowledge management
An intelligent dynamic MRI system for automatic nasal tumor detection
Advances in Fuzzy Systems - Special issue on Hybrid Biomedical Intelligent Systems
Scalable subspace logistic regression models for high dimensional data
APWeb'12 Proceedings of the 14th Asia-Pacific international conference on Web Technologies and Applications
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Large-scale logistic regression arises in many applications such as document classification and natural language processing. In this paper, we apply a trust region Newton method to maximize the log-likelihood of the logistic regression model. The proposed method uses only approximate Newton steps in the beginning, but achieves fast convergence in the end. Experiments show that it is faster than the commonly used quasi Newton approach for logistic regression. We also compare it with linear SVM implementations.