S. Sathiya Keerthi

发表

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

Shwetabh Khanduja, Vinod Nair, S. Sundararajan, 2015, 2015 IEEE International Conference on Data Mining Workshop (ICDMW).

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

S. Sathiya Keerthi, Sundararajan Sellamanickam, Shirish K. Shevade, 2012, COLING.

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

Han Tong Loh, S. Sathiya Keerthi, Rakesh Menon, 2005, Reliab. Eng. Syst. Saf..

An Empirical Evaluation of Sequence-Tagging Trainers pdf

S. Sundararajan, S. Sathiya Keerthi, Shirish K. Shevade, 2013, ArXiv.

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

S. Sathiya Keerthi, Chiranjib Bhattacharyya, Shirish K. Shevade, 2000, IEEE Trans. Neural Networks Learn. Syst..

Building Support Vector Machines with Reduced Classifier Complexity

S. Sathiya Keerthi, Dennis DeCoste, Olivier Chapelle, 2006, J. Mach. Learn. Res..

Transductive Classification Methods for Mixed Graphs pdf

S. Sathiya Keerthi, Sundararajan Sellamanickam, S. Keerthi, 2012, ArXiv.

Parallel sequential minimal optimization for the training of support vector machines

S. Sathiya Keerthi, Chong Jin Ong, Lijuan Cao, 2006, IEEE Trans. Neural Networks.

Trust Region Newton Method for Logistic Regression

Chih-Jen Lin, S. Sathiya Keerthi, Ruby C. Weng, 2008, J. Mach. Learn. Res..

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

Han Tong Loh, S. Sathiya Keerthi, Aarnout Brombacher, 2003, KES.

Numerical approaches for solution of differential equations on manifolds

S. Sathiya Keerthi, R. Sudarsan, S. Keerthi, 1998, Appl. Math. Comput..

Fast Generalized Cross-Validation Algorithm for Sparse Model Learning

S. Sundararajan, S. Sathiya Keerthi, Shirish K. Shevade, 2007, Neural Computation.

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

S. V. N. Vishwanathan, S. Sathiya Keerthi, Markus Weimer, 2017, ArXiv.

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

S. Sathiya Keerthi, Abhi Dattasharma, S. Keerthi, 1995, Theor. Comput. Sci..

Which Is the Best Multiclass SVM Method? An Empirical Study

S. Sathiya Keerthi, Kaibo Duan, S. Keerthi, 2005, Multiple Classifier Systems.

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

S. Sathiya Keerthi, Abhi Dattasharma, 1993, CCCG.

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

S. Sathiya Keerthi, R. Sudarsan, N. K. Sancheti, 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

Convergence of a Generalized SMO Algorithm for SVM Classifier Design

S. Sathiya Keerthi, Elmer G. Gilbert, E. Gilbert, 2002, Machine Learning.

Deterministic Annealing for Semi-Supervised Structured Output Learning

S. Sathiya Keerthi, Paramveer S. Dhillon, Sundararajan Sellamanickam, 2012, AISTATS.

Branch and Bound for Semi-Supervised Support Vector Machines

S. Sathiya Keerthi, Vikas Sindhwani, Olivier Chapelle, 2006, NIPS.

Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel

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

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

S. Sathiya Keerthi, Elmer G. Gilbert, Daniel W. Johnson, 1987, Proceedings. 1987 IEEE International Conference on Robotics and Automation.

Learning State Representations for Query Optimization with Deep Reinforcement Learning

Magdalena Balazinska, Johannes Gehrke, S. Sathiya Keerthi, 2018, DEEM@SIGMOD.

Semi-Supervised Gaussian Process Classifiers

Wei Chu, S. Sathiya Keerthi, Vikas Sindhwani, 2007, IJCAI.

Ad Delivery with Budgeted Advertisers: A Comprehensive LP Approach

S. Sathiya Keerthi, Zoë Abrams, Ofer Mendelevitch, 2008 .

Learning a Hierarchical Monitoring System for Detecting and Diagnosing Service Issues

Shwetabh Khanduja, Vinod Nair, Ameya Raul, 2015, KDD.

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

S. Sathiya Keerthi, Paramveer S. Dhillon, Sundararajan Sellamanickam, 2011, CIKM '11.

EquiDistance diagram-a new roadmap method for path planning

S. Sathiya Keerthi, Elmer G. Gilbert, Chong Jin Ong, 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

Improvements to Platt's SMO Algorithm for SVM Classifier Design

S. Sathiya Keerthi, Chiranjib Bhattacharyya, Shirish K. Shevade, 2001, Neural Computation.

An Empirical Analysis of Deep Learning for Cardinality Estimation pdf

Magdalena Balazinska, Johannes Gehrke, S. Sathiya Keerthi, 2019, ArXiv.

Mean Field Methods for a Special Class of Belief Networks pdf

S. Sathiya Keerthi, Chiranjib Bhattacharyya, S. Keerthi, 2001, J. Artif. Intell. Res..

Predictive Approaches For Gaussian Process Classifier Model Selection pdf

S. Sathiya Keerthi, Sundararajan Sellamanickam, S. Keerthi, 2012, ArXiv.

SMO Algorithm for Least-Squares SVM Formulation

S. Sathiya Keerthi, Shirish K. Shevade, S. Keerthi, 2003, Neural Computation.

A matching pursuit approach to sparse Gaussian process regression

Wei Chu, S. Sathiya Keerthi, 2005, NIPS.

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

S. Sathiya Keerthi, Dennis DeCoste, D. DeCoste, 2005, J. Mach. Learn. Res..

Predictive Approaches for Sparse Model Learning

S. Sundararajan, S. Sathiya Keerthi, Shirish K. Shevade, 2004, ICONIP.

A dual coordinate descent method for large-scale linear SVM

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

Distance Measures on Intersecting Objects and Their Applications

K. Sridharan, S. Sathiya Keerthi, Harry E. Stephanou, 1994, Inf. Process. Lett..

A machine learning approach for the curation of biomedical literature: KDD Cup 2002 (task 1)

Wei Chu, Han Tong Loh, S. Sathiya Keerthi, 2002, SKDD.

A sharable instructable agent for information filtering

S. Sathiya Keerthi, M. N. Murty, Krk Murthy, 2001 .

An efficient approach for the numerical simulation of multibody systems

S. Sathiya Keerthi, R. Sudarsan, S. Keerthi, 1998, Appl. Math. Comput..

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

S. Sundararajan, S. Sathiya Keerthi, Dhruv Kumar Mahajan, 2014, J. Mach. Learn. Res..

Regularized Structured Output Learning with Partial Labels

S. Sathiya Keerthi, Charu Tiwari, Sundararajan Sellamanickam, 2012, SDM.

A study of representations for pen based handwriting recognition of Tamil characters

S. Sathiya Keerthi, C. S. Sundaresan, C. Sundaresan, 1999, Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318).

Targeted display advertising: the case of preferential attachment

S. Sathiya Keerthi, Saurav Manchanda, Khoa Doan, 2019, 2019 IEEE International Conference on Big Data (Big Data).

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

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

Bayesian support vector regression using a unified loss function

Wei Chu, S. Sathiya Keerthi, Chong Jin Ong, 2004, IEEE Transactions on Neural Networks.

Gradient Boosted Decision Trees for High Dimensional Sparse Output

Inderjit S. Dhillon, Cho-Jui Hsieh, Huan Zhang, 2017, ICML.

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

S. Sathiya Keerthi, Vikas Sindhwani, Olivier Chapelle, 2006, NIPS.

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

S. Sathiya Keerthi, Sundararajan Sellamanickam, Shirish K. Shevade, 2011, CIKM '11.

A Functional Approximation Based Distributed Learning Algorithm pdf

S. Sundararajan, S. Sathiya Keerthi, Léon Bottou, 2013, ArXiv.

Developing parallel sequential minimal optimization for fast training support vector machine

S. Sathiya Keerthi, Chong Jin Ong, Lijuan Cao, 2006, Neurocomputing.

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

S. Sathiya Keerthi, S. Keerthi, 2005, ICML.

Constructing a maximum utility slate of on-line advertisements pdf

S. Sathiya Keerthi, John A. Tomlin, J. Tomlin, 2007, ArXiv.

Conditional Generative Adversarial Networks for Regression

S. Sathiya Keerthi, Patrick Gallinari, Karan Aggarwal, 2019 .

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

S. Sathiya Keerthi, Makarand S. Phatak, 1992, Autom..

Regression via Implicit Models and Optimal Transport Cost Minimization pdf

S. Sathiya Keerthi, Saurav Manchanda, Khoa Doan, 2020, ArXiv.

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

S. Sathiya Keerthi, Priyanka Garg, Sundararajan Sellamanickam, 2011, CIKM '11.

Large scale semi-supervised linear SVMs

S. Sathiya Keerthi, Vikas Sindhwani, V. Sindhwani, 2006, SIGIR.

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

M. Narasimha Murty, S. Sathiya Keerthi, K. R. K. Murthy, 2001, Pattern Recognit..

Regression with Conditional GAN pdf

S. Sathiya Keerthi, Patrick Gallinari, Karan Aggarwal, 2019, ArXiv.

Efficient algorithms for ranking with SVMs

S. Sathiya Keerthi, Olivier Chapelle, O. Chapelle, 2010, Information Retrieval.

A Fast Tracking Algorithm for Generalized LARS/LASSO

S. Sathiya Keerthi, Shirish K. Shevade, S. Keerthi, 2007, IEEE Transactions on Neural Networks.

A Variational Mean-Field Theory for Sigmoidal Belief Networks

S. Sathiya Keerthi, Chiranjib Bhattacharyya, S. Keerthi, 2000, NIPS.

Improvements to the SMO algorithm for SVM regression

S. Sathiya Keerthi, Chiranjib Bhattacharyya, Shirish K. Shevade, 2000, IEEE Trans. Neural Networks Learn. Syst..

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

S. Sathiya Keerthi, Dennis DeCoste, Chong Jin Ong, 2004, IEEE Transactions on Neural Networks.

Trust region Newton methods for large-scale logistic regression

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

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

S. Sathiya Keerthi, Vivek Gupta, Dhruv Kumar Mahajan, 2017, ArXiv.

A Parallel SGD method with Strong Convergence pdf

S. Sundararajan, S. Sathiya Keerthi, Léon Bottou, 2013, ArXiv.

Support Vector Ordinal Regression

Wei Chu, S. Sathiya Keerthi, S. Keerthi, 2007, Neural Computation.

A Sequential Dual Method for Structural SVMs

S. Sundararajan, S. Sathiya Keerthi, Shirish K. Shevade, 2011, SDM.

Relational Learning with Gaussian Processes

Wei Chu, Zoubin Ghahramani, S. Sathiya Keerthi, 2006, NIPS.

Hashtag Recommendation for Enterprise Applications

Johannes Gehrke, S. Sathiya Keerthi, Chetan Bansal, 2016, CIKM.

New approaches to support vector ordinal regression

Wei Chu, S. Sathiya Keerthi, S. Keerthi, 2005, ICML.

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

Wei Chu, S. Sathiya Keerthi, Aun Neow Poo, 2003, Multiple Classifier Systems.

Optimization Techniques for Semi-Supervised Support Vector Machines

S. Sathiya Keerthi, Vikas Sindhwani, Olivier Chapelle, 2008, J. Mach. Learn. Res..

A Fast Dual Algorithm for Kernel Logistic Regression

S. Sathiya Keerthi, Aun Neow Poo, Shirish K. Shevade, 2002, 2007 International Joint Conference on Neural Networks.

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

M. Narasimha Murty, S. Sathiya Keerthi, G. Phanendra Babu, 2000, IEEE Trans. Syst. Man Cybern. Part B.

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

Wei Chu, S. Sathiya Keerthi, Chong Jin Ong, 2005, IEEE Transactions on Neural Networks.

A web of concepts

Ravi Kumar, Andrew Tomkins, S. Sathiya Keerthi, 2009, PODS.

An efficient distributed learning algorithm based on effective local functional approximations

S. Sathiya Keerthi, Léon Bottou, Dhruv Kumar Mahajan, 2018, J. Mach. Learn. Res..

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

S. Sathiya Keerthi, Z. H. Zhang, Elmer G. Gilbert, 2004, Autom..

Bayesian Trigonometric Support Vector Classifier

Wei Chu, S. Sathiya Keerthi, Chong Jin Ong, 2003, Neural Computation.

Regional pole placement of multivariable systems under control structure constraints

S. Sathiya Keerthi, H. S. Phatak, M. Phatak, 1995, IEEE Trans. Autom. Control..

Algorithms for the optimal loading of recursive neural nets

V. Vinay, S. Sathiya Keerthi, Vijay Chandru, 1995, SODA '95.

A Quantitative Evaluation Framework for Missing Value Imputation Algorithms pdf

Johannes Gehrke, Vinod Nair, S. Sathiya Keerthi, 2013, ArXiv.

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

S. Sathiya Keerthi, N. K. Sancheti, 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

A Unified Loss Function in Bayesian Framework for Support Vector Regression

Wei Chu, S. Sathiya Keerthi, Chong Jin Ong, 2001, ICML.

Tractable Semi-supervised Learning of Complex Structured Prediction Models

Kai-Wei Chang, S. Sundararajan, S. Sathiya Keerthi, 2013, ECML/PKDD.

A Structured Prediction Approach for Missing Value Imputation pdf

Vinod Nair, S. Sathiya Keerthi, Sundararajan Sellamanickam, 2013, ArXiv.

Batch-Expansion Training: An Efficient Optimization Framework

S. V. N. Vishwanathan, S. Sathiya Keerthi, Markus Weimer, 2017, AISTATS.

Domain adaptation in display advertising: an application for partner cold-start

S. Sathiya Keerthi, Karan Aggarwal, Pranjul Yadav, 2019, RecSys.

On computing a distance measure for path planning

K. Sridharan, S. Sathiya Keerthi, Harry E. Stephanou, 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

A Machine Learning Approach for the Curation of Biomedical Literature

Han Tong Loh, S. Sathiya Keerthi, Min Shi, 2003, ECIR.

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

S. Sathiya Keerthi, N. K. Sancheti, H. Shashikala, 1992, Proceedings 1992 IEEE International Conference on Robotics and Automation.

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

S. Sathiya Keerthi, Shirish K. Shevade, S. Keerthi, 2003, Bioinform..

Distributed Newton Methods for Deep Neural Networks

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

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

S. Sathiya Keerthi, Elmer G. Gilbert, Daniel W. Johnson, 1988, IEEE J. Robotics Autom..

Evaluation of simple performance measures for tuning SVM hyperparameters

S. Sathiya Keerthi, Aun Neow Poo, Kaibo Duan, 2003, Neurocomputing.

Towards a Better Understanding of Predict and Count Models pdf

S. Sathiya Keerthi, Rajiv Khanna, Tobias Schnabel, 2015, ArXiv.

Deterministic annealing for semi-supervised kernel machines

S. Sathiya Keerthi, Vikas Sindhwani, Olivier Chapelle, 2006, ICML.

Predictive Approaches for Choosing Hyperparameters in Gaussian Processes

S. Sundararajan, S. Sathiya Keerthi, S. Keerthi, 1999, Neural Computation.

Numerical determination of optimal non-holonomic paths in the presence of obstacles

S. Sathiya Keerthi, Sudhaker Samuel, 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

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

K. Sridharan, S. Sathiya Keerthi, S. Keerthi, 2001, J. Field Robotics.

A Distributed Algorithm for Training Nonlinear Kernel Machines pdf

S. Sundararajan, S. Sathiya Keerthi, Dhruv Kumar Mahajan, 2014, ArXiv.

Automatic web-scale information extraction

S. Sathiya Keerthi, Nilesh N. Dalvi, Yuval Filmus, 2012, SIGMOD Conference.

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

S. Sathiya Keerthi, S. Keerthi, 2002, IEEE Trans. Neural Networks.

Special issue on support vector machines

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

Optimal control of a somersaulting platform diver: a numerical approach

S. Sathiya Keerthi, Nukala V. R. K. N. Murthy, 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

Bayesian Support Vector Machines for Feature Ranking and Selection

Wei Chu, Zoubin Ghahramani, S. Sathiya Keerthi, 2006, Feature Extraction.

Context filters for document-based information filtering

S. Sathiya Keerthi, K. R. K. Murthy, S. Keerthi, 1999, Proceedings of the Fifth International Conference on Document Analysis and Recognition. ICDAR '99 (Cat. No.PR00318).

Benchmarking Regression Methods: A comparison with CGAN

S. Sathiya Keerthi, Karan Aggarwal, Pranjul Yadav, 2019 .

Graph Based Classification Methods Using Inaccurate External Classifier Information pdf

S. Sathiya Keerthi, Sundararajan Sellamanickam, S. Keerthi, 2012, ArXiv.

Logit Attenuating Weight Normalization pdf

S. Sathiya Keerthi, Aman Gupta, Rohan Ramanath, 2021, ArXiv.

Asymptotic Behaviors of Support Vector Machines with

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

A new Bayesian design method for support vector classification

S. Sathiya Keerthi, Chong Jin Ong, Wei Chu, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..