# S. Sathiya Keerthi

According to our database

Collaborative distances:

^{1}, S. Sathiya Keerthi authored at least 110 papers between 1987 and 2018.Collaborative distances:

## Timeline

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## Bibliography

2018

Distributed Newton Methods for Deep Neural Networks.

Neural Computation, 2018

An efficient distributed learning algorithm based on effective local functional approximations.

Journal of Machine Learning Research, 2018

Learning State Representations for Query Optimization with Deep Reinforcement Learning.

CoRR, 2018

Distributed Newton Methods for Deep Neural Networks.

CoRR, 2018

Learning State Representations for Query Optimization with Deep Reinforcement Learning.

Proceedings of the Second Workshop on Data Management for End-To-End Machine Learning, 2018

Batch-Expansion Training: An Efficient Optimization Framework.

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

A distributed block coordinate descent method for training l1 regularized linear classifiers.

Journal of Machine Learning Research, 2017

Efficient Estimation of Generalization Error and Bias-Variance Components of Ensembles.

CoRR, 2017

Batch-Expansion Training: An Efficient Optimization Paradigm for Machine Learning.

CoRR, 2017

Gradient Boosted Decision Trees for High Dimensional Sparse Output.

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Hashtag Recommendation for Enterprise Applications.

Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

2015

Towards a Better Understanding of Predict and Count Models.

CoRR, 2015

Learning a Hierarchical Monitoring System for Detecting and Diagnosing Service Issues.

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Near Real-Time Service Monitoring Using High-Dimensional Time Series.

Proceedings of the IEEE International Conference on Data Mining Workshop, 2015

2014

A distributed block coordinate descent method for training $l_1$ regularized linear classifiers.

CoRR, 2014

A Distributed Algorithm for Training Nonlinear Kernel Machines.

CoRR, 2014

2013

An Empirical Evaluation of Sequence-Tagging Trainers.

CoRR, 2013

A Quantitative Evaluation Framework for Missing Value Imputation Algorithms.

CoRR, 2013

A Parallel SGD method with Strong Convergence.

CoRR, 2013

A Functional Approximation Based Distributed Learning Algorithm.

CoRR, 2013

A Structured Prediction Approach for Missing Value Imputation.

CoRR, 2013

Tractable Semi-supervised Learning of Complex Structured Prediction Models.

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

2012

Deterministic Annealing for Semi-Supervised Structured Output Learning.

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Extension of TSVM to Multi-Class and Hierarchical Text Classification Problems With General Losses

CoRR, 2012

Predictive Approaches For Gaussian Process Classifier Model Selection

CoRR, 2012

Transductive Classification Methods for Mixed Graphs

CoRR, 2012

Graph Based Classification Methods Using Inaccurate External Classifier Information

CoRR, 2012

Automatic web-scale information extraction.

Proceedings of the ACM SIGMOD International Conference on Management of Data, 2012

Regularized Structured Output Learning with Partial Labels.

Proceedings of the Twelfth SIAM International Conference on Data Mining, 2012

Extension of TSVM to Multi-Class and Hierarchical Text Classification Problems With General Losses.

Proceedings of the COLING 2012, 2012

2011

Mean Field Methods for a Special Class of Belief Networks

CoRR, 2011

A Sequential Dual Method for Structural SVMs.

Proceedings of the Eleventh SIAM International Conference on Data Mining, 2011

Semi-supervised SVMs for classification with unknown class proportions and a small labeled dataset.

Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011

A pairwise ranking based approach to learning with positive and unlabeled examples.

Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011

Semi-supervised multi-task learning of structured prediction models for web information extraction.

Proceedings of the 20th ACM Conference on Information and Knowledge Management, 2011

2010

Efficient algorithms for ranking with SVMs.

Inf. Retr., 2010

2009

A web of concepts.

Proceedings of the Twenty-Eigth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, 2009

2008

Trust Region Newton Method for Logistic Regression.

Journal of Machine Learning Research, 2008

Optimization Techniques for Semi-Supervised Support Vector Machines.

Journal of Machine Learning Research, 2008

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

Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

A dual coordinate descent method for large-scale linear SVM.

Proceedings of the Machine Learning, 2008

2007

A Fast Tracking Algorithm for Generalized LARS/LASSO.

IEEE Trans. Neural Networks, 2007

Fast Generalized Cross-Validation Algorithm for Sparse Model Learning.

Neural Computation, 2007

Support Vector Ordinal Regression.

Neural Computation, 2007

Constructing a maximum utility slate of on-line advertisements

CoRR, 2007

Semi-Supervised Gaussian Process Classifiers.

Proceedings of the IJCAI 2007, 2007

Trust region Newton methods for large-scale logistic regression.

Proceedings of the Machine Learning, 2007

2006

Parallel sequential minimal optimization for the training of support vector machines.

IEEE Trans. Neural Networks, 2006

Building Support Vector Machines with Reduced Classifier Complexity.

Journal of Machine Learning Research, 2006

Developing parallel sequential minimal optimization for fast training support vector machine.

Neurocomputing, 2006

Large scale semi-supervised linear SVMs.

Proceedings of the SIGIR 2006: Proceedings of the 29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2006

An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models.

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Relational Learning with Gaussian Processes.

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Branch and Bound for Semi-Supervised Support Vector Machines.

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Deterministic annealing for semi-supervised kernel machines.

Proceedings of the Machine Learning, 2006

2005

An improved conjugate gradient scheme to the solution of least squares SVM.

IEEE Trans. Neural Networks, 2005

Analyzing textual databases using data mining to enable fast product development processes.

Rel. Eng. & Sys. Safety, 2005

A Fast Dual Algorithm for Kernel Logistic Regression.

Machine Learning, 2005

A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs.

Journal of Machine Learning Research, 2005

A matching pursuit approach to sparse Gaussian process regression.

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

Which Is the Best Multiclass SVM Method? An Empirical Study.

Proceedings of the Multiple Classifier Systems, 6th International Workshop, 2005

Generalized LARS as an effective feature selection tool for text classification with SVMs.

Proceedings of the Machine Learning, 2005

New approaches to support vector ordinal regression.

Proceedings of the Machine Learning, 2005

2004

An efficient method for computing leave-one-out error in support vector machines with Gaussian kernels.

IEEE Trans. Neural Networks, 2004

Bayesian support vector regression using a unified loss function.

IEEE Trans. Neural Networks, 2004

Stability regions for constrained nonlinear systems and their functional characterization via support-vector-machine learning.

Automatica, 2004

Predictive Approaches for Sparse Model Learning.

Proceedings of the Neural Information Processing, 11th International Conference, 2004

2003

SMO Algorithm for Least-Squares SVM Formulation.

Neural Computation, 2003

Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel.

Neural Computation, 2003

Bayesian Trigonometric Support Vector Classifier.

Neural Computation, 2003

Evaluation of simple performance measures for tuning SVM hyperparameters.

Neurocomputing, 2003

Special issue on support vector machines.

Neurocomputing, 2003

A simple and efficient algorithm for gene selection using sparse logistic regression.

Bioinformatics, 2003

Multi-category Classification by Soft-Max Combination of Binary Classifiers.

Proceedings of the Multiple Classifier Systems, 4th International Workshop, 2003

Automated Text Classification for Fast Feedback - Investigating the Effects of Document Representation.

Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2003

A Machine Learning Approach for the Curation of Biomedical Literature.

Proceedings of the Advances in Information Retrieval, 2003

2002

Efficient tuning of SVM hyperparameters using radius/margin bound and iterative algorithms.

IEEE Trans. Neural Networks, 2002

A Machine Learning Approach for the Curation of Biomedical Literature - KDD Cup 2002 (Task 1).

SIGKDD Explorations, 2002

Convergence of a Generalized SMO Algorithm for SVM Classifier Design.

Machine Learning, 2002

A Fast Dual Algorithm for Kernel Logistic Regression.

Proceedings of the Machine Learning, 2002

2001

Rule prepending and post-pruning approach to incremental learning of decision lists.

Pattern Recognition, 2001

Predictive Approaches for Choosing Hyperparameters in Gaussian Processes.

Neural Computation, 2001

Improvements to Platt's SMO Algorithm for SVM Classifier Design.

Neural Computation, 2001

Computation of a penetration measure between 3D convex polyhedral objects for collision detection.

J. Field Robotics, 2001

Mean Field Methods for a Special Class of Belief Networks.

J. Artif. Intell. Res., 2001

A Unified Loss Function in Bayesian Framework for Support Vector Regression.

Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28, 2001

2000

A stochastic connectionist approach for global optimization with application to pattern clustering.

IEEE Trans. Systems, Man, and Cybernetics, Part B, 2000

Improvements to the SMO algorithm for SVM regression.

IEEE Trans. Neural Netw. Learning Syst., 2000

A fast iterative nearest point algorithm for support vector machine classifier design.

IEEE Trans. Neural Netw. Learning Syst., 2000

A Variational Mean-Field Theory for Sigmoidal Belief Networks.

Proceedings of the Advances in Neural Information Processing Systems 13, 2000

1999

Predictive App roaches for Choosing Hyperparameters in Gaussian Processes.

Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999

EquiDistance Diagram: A New Roadmap Method for Path Planning.

Proceedings of the 1999 IEEE International Conference on Robotics and Automation, 1999

A Study of Representations for Pen based Handwriting Recognition of Tamil Characters.

Proceedings of the Fifth International Conference on Document Analysis and Recognition, 1999

Context Filters for Document-based Information Filtering.

Proceedings of the Fifth International Conference on Document Analysis and Recognition, 1999

1998

Synthesis of fault-tolerant feedforward neural networks using minimax optimization.

IEEE Trans. Neural Networks, 1998

An efficient approach for the numerical simulation of multibody systems.

Applied Mathematics and Computation, 1998

Numerical approaches for solution of differential equations on manifolds.

Applied Mathematics and Computation, 1998

1995

An Augmented Voronoi Roadmap for 3D Translational Motion Planning for a Convex Polyhedron Moving Amidst Convex Polyhedral Obstacles.

Theor. Comput. Sci., 1995

Algorithms for the Optimal Loading of Recursive Neural Nets.

Proceedings of the Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 1995

1994

Distance Measures on Intersecting Objects and Their Applications.

Inf. Process. Lett., 1994

1993

On Computing a Distance Measure for Path Planning.

Proceedings of the 1993 IEEE International Conference on Robotics and Automation, 1993

Numerical Determination of Optimal Non-Holonomic Paths in the Presence of Obstacles.

Proceedings of the 1993 IEEE International Conference on Robotics and Automation, 1993

Optimal Control of a Somersaulting Platform Diver: A Numerical Approach.

Proceedings of the 1993 IEEE International Conference on Robotics and Automation, 1993

Translational Motion Planning for a Convex Polyhedron in a 3D Polyhedral World Using an Efficient and New Roadmap.

Proceedings of the 5th Canadian Conference on Computational Geometry, 1993

1992

A homotopy approach for stabilizing single-input systems with control structure constraints.

Automatica, 1992

Path planning: an approach based on connecting all the minimizers and maximizers of a potential function.

Proceedings of the 1992 IEEE International Conference on Robotics and Automation, 1992

Computation of certain measures of proximity between convex polytopes: a complexity viewpoint.

Proceedings of the 1992 IEEE International Conference on Robotics and Automation, 1992

A new approach to the numerical solution of constrained mechanical system dynamics.

Proceedings of the 1992 IEEE International Conference on Robotics and Automation, 1992

1988

A fast procedure for computing the distance between complex objects in three-dimensional space.

IEEE J. Robotics and Automation, 1988

1987

A fast procedure for computing the distance between complex objects in three space.

Proceedings of the 1987 IEEE International Conference on Robotics and Automation, Raleigh, North Carolina, USA, March 31, 1987