S. V. N. Vishwanathan

According to our database, S. V. N. Vishwanathan authored at least 115 papers between 2000 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Bi-CAT: Improving Robustness of LLM-based Text Rankers to Conditional Distribution Shifts.

Sriram Srinivasan, Stephen Sheng, Rishabh Deshmukh, Chen Luo, Yesh Dattatreya, Subhajit Sanyal, S. V. N. Vishwanathan

Proceedings of the Companion Proceedings of the ACM on Web Conference 2024, 2024

PEFA: Parameter-Free Adapters for Large-scale Embedding-based Retrieval Models.

Wei-Cheng Chang, Jyun-Yu Jiang, Jiong Zhang, Mutasem Al-Darabsah, Choon Hui Teo, Cho-Jui Hsieh, Hsiang-Fu Yu, S. V. N. Vishwanathan

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

2023

Web-Scale Semantic Product Search with Large Language Models.

Aashiq Muhamed, Sriram Srinivasan, Choon Hui Teo, Qingjun Cui, Belinda Zeng, Trishul Chilimbi, S. V. N. Vishwanathan

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

2022

On the Value of Behavioral Representations for Dense Retrieval.

Nan Jiang, Dhivya Eswaran, Choon Hui Teo, Yexiang Xue, Yesh Dattatreya, Sujay Sanghavi, Vishy Vishwanathan

CoRR, 2022

Toward Understanding Privileged Features Distillation in Learning-to-Rank.

Shuo Yang, Sujay Sanghavi, Holakou Rahmanian, Jan Bakus, S. V. N. Vishwanathan

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Augmenting Training Data for Massive Semantic Matching Models in Low-Traffic E-commerce Stores.

Ashutosh Joshi, Shankar Vishwanath, Choon Hui Teo, Vaclav Petricek, Vishy Vishwanathan, Rahul Bhagat, Jonathan May

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Industry Track, 2022

2021

Embracing Structure in Data for Billion-Scale Semantic Product Search.

Vihan Lakshman, Choon Hui Teo, Xiaowen Chu, Priyanka Nigam, Abhinandan Patni, Pooja Maknikar, S. V. N. Vishwanathan

CoRR, 2021

2020

DS-FACTO: Doubly Separable Factorization Machines.

Parameswaran Raman, S. V. N. Vishwanathan

CoRR, 2020

2019

Scaling Multinomial Logistic Regression via Hybrid Parallelism.

Parameswaran Raman, Sriram Srinivasan, Shin Matsushima, Xinhua Zhang, Hyokun Yun, S. V. N. Vishwanathan

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Whole Page Optimization with Global Constraints.

Weicong Ding, Dinesh Govindaraj, S. V. N. Vishwanathan

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

A Zero Attention Model for Personalized Product Search.

Qingyao Ai, Daniel N. Hill, S. V. N. Vishwanathan, W. Bruce Croft

Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Extreme Stochastic Variational Inference: Distributed Inference for Large Scale Mixture Models.

Jiong Zhang, Parameswaran Raman, Shihao Ji, Hsiang-Fu Yu, S. V. N. Vishwanathan, Inderjit S. Dhillon

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Diversifying Music Recommendations.

Houssam Nassif, Kemal Oral Cansizlar, Mitchell Goodman, S. V. N. Vishwanathan

CoRR, 2018

Online Learning of Combinatorial Objects via Extended Formulation.

Holakou Rahmanian, David P. Helmbold, S. V. N. Vishwanathan

Proceedings of the Algorithmic Learning Theory, 2018

Batch-Expansion Training: An Efficient Optimization Framework.

Michal Derezinski, Dhruv Mahajan, S. Sathiya Keerthi, S. V. N. Vishwanathan, Markus Weimer

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

2017

Colors - Messengers of Concepts: Visual Design Mining for Learning Color Semantics.

Ali Jahanian, Shaiyan Keshvari, S. V. N. Vishwanathan, Jan P. Allebach

ACM Trans. Comput. Hum. Interact., 2017

Online Dynamic Programming.

Holakou Rahmanian, S. V. N. Vishwanathan, Manfred K. Warmuth

CoRR, 2017

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

Michal Derezinski, Dhruv Mahajan, S. Sathiya Keerthi, S. V. N. Vishwanathan, Markus Weimer

CoRR, 2017

Distributed Stochastic Optimization of Regularized Risk via Saddle-Point Problem.

Shin Matsushima, Hyokun Yun, Xinhua Zhang, S. V. N. Vishwanathan

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

An Efficient Bandit Algorithm for Realtime Multivariate Optimization.

Daniel N. Hill, Houssam Nassif, Yi Liu, Anand Iyer, S. V. N. Vishwanathan

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

2016

DS-MLR: Exploiting Double Separability for Scaling up Distributed Multinomial Logistic Regression.

Parameswaran Raman, Shin Matsushima, Xinhua Zhang, Hyokun Yun, S. V. N. Vishwanathan

CoRR, 2016

Extended Formulation for Online Learning of Combinatorial Objects.

Holakou Rahmanian, S. V. N. Vishwanathan, David P. Helmbold

CoRR, 2016

BlackOut: Speeding up Recurrent Neural Network Language Models With Very Large Vocabularies.

Shihao Ji, S. V. N. Vishwanathan, Nadathur Satish, Michael J. Anderson, Pradeep Dubey

Proceedings of the 4th International Conference on Learning Representations, 2016

Nomadic Computing for Big Data Analytics.

Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, S. V. N. Vishwanathan, Inderjit S. Dhillon

Computer, 2016

Adaptive, Personalized Diversity for Visual Discovery.

Choon Hui Teo, Houssam Nassif, Daniel N. Hill, Sriram Srinivasan, Mitchell Goodman, Vijai Mohan, S. V. N. Vishwanathan

Proceedings of the 10th ACM Conference on Recommender Systems, 2016

WordRank: Learning Word Embeddings via Robust Ranking.

Shihao Ji, Hyokun Yun, Pinar Yanardag, Shin Matsushima, S. V. N. Vishwanathan

Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, 2016

2015

Totally Corrective Boosting with Cardinality Penalization.

Vasil S. Denchev, Nan Ding, Shin Matsushima, S. V. N. Vishwanathan, Hartmut Neven

CoRR, 2015

Colors $-$Messengers of Concepts: Visual Design Mining for Learning Color Semantics.

Ali Jahanian, S. V. N. Vishwanathan, Jan P. Allebach

CoRR, 2015

A Scalable Asynchronous Distributed Algorithm for Topic Modeling.

Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, S. V. N. Vishwanathan, Inderjit S. Dhillon

Proceedings of the 24th International Conference on World Wide Web, 2015

A Structural Smoothing Framework For Robust Graph Comparison.

Pinar Yanardag, S. V. N. Vishwanathan

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Deep Graph Kernels.

Pinar Yanardag, S. V. N. Vishwanathan

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

Learning visual balance from large-scale datasets of aesthetically highly rated images.

Ali Jahanian, S. V. N. Vishwanathan, Jan P. Allebach

Proceedings of the Human Vision and Electronic Imaging XX, 2015

Autonomous color theme extraction from images using saliency.

Ali Jahanian, S. V. N. Vishwanathan, Jan P. Allebach

Proceedings of the Imaging and Multimedia Analytics in a Web and Mobile World 2015, 2015

Preface.

Guy Lebanon, S. V. N. Vishwanathan

Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014

Accelerated training of max-margin Markov networks with kernels.

Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan

Theor. Comput. Sci., 2014

NOMAD: Nonlocking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion.

Hyokun Yun, Hsiang-Fu Yu, Cho-Jui Hsieh, S. V. N. Vishwanathan, Inderjit S. Dhillon

Proc. VLDB Endow., 2014

Ranking via Robust Binary Classification and Parallel Parameter Estimation in Large-Scale Data.

Hyokun Yun, Parameswaran Raman, S. V. N. Vishwanathan

CoRR, 2014

The Structurally Smoothed Graphlet Kernel.

Pinar Yanardag, S. V. N. Vishwanathan

CoRR, 2014

Distributed Stochastic Optimization of the Regularized Risk.

Shin Matsushima, Hyokun Yun, S. V. N. Vishwanathan

CoRR, 2014

Modeling Attractiveness and Multiple Clicks in Sponsored Search Results.

Dinesh Govindaraj, Tao Wang, S. V. N. Vishwanathan

CoRR, 2014

Ranking via Robust Binary Classification.

Hyokun Yun, Parameswaran Raman, S. V. N. Vishwanathan

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Juxtapoze: supporting serendipity and creative expression in clipart compositions.

William Benjamin, Senthil K. Chandrasegaran, Devarajan Ramanujan, Niklas Elmqvist, S. V. N. Vishwanathan, Karthik Ramani

Proceedings of the CHI Conference on Human Factors in Computing Systems, 2014

2013

Distributed Autonomous Online Learning: Regrets and Intrinsic Privacy-Preserving Properties.

Feng Yan, Shreyas Sundaram, S. V. N. Vishwanathan, Yuan (Alan) Qi

IEEE Trans. Knowl. Data Eng., 2013

NOMAD: Non-locking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion.

Hyokun Yun, Hsiang-Fu Yu, Cho-Jui Hsieh, S. V. N. Vishwanathan, Inderjit S. Dhillon

CoRR, 2013

Open Problem: Lower bounds for Boosting with Hadamard Matrices.

Jiazhong Nie, Manfred K. Warmuth, S. V. N. Vishwanathan, Xinhua Zhang

Proceedings of the COLT 2013, 2013

2012

Efficient max-margin multi-label classification with applications to zero-shot learning.

Bharath Hariharan, S. V. N. Vishwanathan, Manik Varma

Mach. Learn., 2012

Smoothing multivariate performance measures.

Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan

J. Mach. Learn. Res., 2012

Quilting Stochastic Kronecker Product Graphs to Generate Multiplicative Attribute Graphs.

Hyokun Yun, S. V. N. Vishwanathan

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

Efficiently Sampling Multiplicative Attribute Graphs Using a Ball-Dropping Process

Hyokun Yun, S. V. N. Vishwanathan

CoRR, 2012

Fair and balanced: learning to present news stories.

Amr Ahmed, Choon Hui Teo, S. V. N. Vishwanathan, Alexander J. Smola

Proceedings of the Fifth International Conference on Web Search and Web Data Mining, 2012

Linear support vector machines via dual cached loops.

Shin Matsushima, S. V. N. Vishwanathan, Alexander J. Smola

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

SPF-GMKL: generalized multiple kernel learning with a million kernels.

Ashesh Jain, S. V. N. Vishwanathan, Manik Varma

Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012

Robust Classification with Adiabatic Quantum Optimization.

Vasil S. Denchev, Nan Ding, S. V. N. Vishwanathan, Hartmut Neven

Proceedings of the 29th International Conference on Machine Learning, 2012

2011

Introduction to the special issue on mining and learning with graphs.

S. V. N. Vishwanathan, Samuel Kaski, Jennifer Neville, Stefan Wrobel

Mach. Learn., 2011

Heat Walk: Robust Salient Segmentation of Non-rigid Shapes.

William Benjamin, Andrew Wood Polk, S. V. N. Vishwanathan, Karthik Ramani

Comput. Graph. Forum, 2011

New Approximation Algorithms for Minimum Enclosing Convex Shapes.

Ankan Saha, S. V. N. Vishwanathan, Xinhua Zhang

Proceedings of the Twenty-Second Annual ACM-SIAM Symposium on Discrete Algorithms, 2011

t-divergence Based Approximate Inference.

Nan Ding, S. V. N. Vishwanathan, Yuan (Alan) Qi

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

sLLE: Spherical locally linear embedding with applications to tomography.

Yi Fang, Mengtian Sun, S. V. N. Vishwanathan, Karthik Ramani

Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition, 2011

2010

A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning.

Jin Yu, S. V. N. Vishwanathan, Simon Günter, Nicol N. Schraudolph

J. Mach. Learn. Res., 2010

Graph Kernels.

S. V. N. Vishwanathan, Nicol N. Schraudolph, Risi Kondor, Karsten M. Borgwardt

J. Mach. Learn. Res., 2010

Bundle Methods for Regularized Risk Minimization.

Choon Hui Teo, S. V. N. Vishwanathan, Alexander J. Smola, Quoc V. Le

J. Mach. Learn. Res., 2010

Regularized Risk Minimization by Nesterov's Accelerated Gradient Methods: Algorithmic Extensions and Empirical Studies

Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan

CoRR, 2010

Cooperative Autonomous Online Learning

Feng Yan, S. V. N. Vishwanathan, Yuan (Alan) Qi

CoRR, 2010

Faster Rates for training Max-Margin Markov Networks

Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan

CoRR, 2010

Lower Bounds on Rate of Convergence of Cutting Plane Methods.

Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Multiple Kernel Learning and the SMO Algorithm.

S. V. N. Vishwanathan, Zhaonan Sun, Nawanol Ampornpunt, Manik Varma

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Multitask Learning without Label Correspondences.

Novi Quadrianto, Alexander J. Smola, Tibério S. Caetano, S. V. N. Vishwanathan, James Petterson

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

t-logistic regression.

Nan Ding, S. V. N. Vishwanathan

Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Large Scale Max-Margin Multi-Label Classification with Priors.

Bharath Hariharan, Lihi Zelnik-Manor, S. V. N. Vishwanathan, Manik Varma

Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010

Tied Kronecker product graph models to capture variance in network populations.

Sebastián Moreno, Sergey Kirshner, Jennifer Neville, S. V. N. Vishwanathan

Proceedings of the 48th Annual Allerton Conference on Communication, 2010

2009

Variable Metric Stochastic Approximation Theory.

Peter Sunehag, Jochen Trumpf, S. V. N. Vishwanathan, Nicol N. Schraudolph

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Hash Kernels for Structured Data.

Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alexander J. Smola, S. V. N. Vishwanathan

J. Mach. Learn. Res., 2009

Hash Kernels.

Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alexander J. Smola, Alexander L. Strehl, Vishy Vishwanathan

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Efficient graphlet kernels for large graph comparison.

Nino Shervashidze, S. V. N. Vishwanathan, Tobias Petri, Kurt Mehlhorn, Karsten M. Borgwardt

Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Lower Bounds for BMRM and Faster Rates for Training SVMs

Ankan Saha, Xinhua Zhang, S. V. N. Vishwanathan

CoRR, 2009

Efficient Approximation Algorithms for Minimum Enclosing Convex Shapes

Ankan Saha, S. V. N. Vishwanathan

CoRR, 2009

The Entire Quantile Path of a Risk-Agnostic SVM Classifier.

Jin Yu, S. V. N. Vishwanathan, Jian Zhang

Proceedings of the UAI 2009, 2009

Tutorial summary: Survey of boosting from an optimization perspective.

Manfred K. Warmuth, S. V. N. Vishwanathan

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2008

A quasi-Newton approach to non-smooth convex optimization.

Jin Yu, S. V. N. Vishwanathan, Simon Günter, Nicol N. Schraudolph

Proceedings of the Machine Learning, 2008

Consistent image analogies using semi-supervised learning.

Li Cheng, S. V. N. Vishwanathan, Xinhua Zhang

Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008

Entropy Regularized LPBoost.

Manfred K. Warmuth, Karen A. Glocer, S. V. N. Vishwanathan

Proceedings of the Algorithmic Learning Theory, 19th International Conference, 2008

2007

Fast Iterative Kernel Principal Component Analysis.

Simon Günter, Nicol N. Schraudolph, S. V. N. Vishwanathan

J. Mach. Learn. Res., 2007

Binet-Cauchy Kernels on Dynamical Systems and its Application to the Analysis of Dynamic Scenes.

S. V. N. Vishwanathan, Alexander J. Smola, René Vidal

Int. J. Comput. Vis., 2007

Bundle Methods for Machine Learning.

Alexander J. Smola, S. V. N. Vishwanathan, Quoc V. Le

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

An Efficient Sampling Scheme For Comparison of Large Graphs.

Karsten M. Borgwardt, Tobias Petri, S. V. N. Vishwanathan, Hans-Peter Kriegel

Proceedings of the Mining and Learning with Graphs, 2007

A scalable modular convex solver for regularized risk minimization.

Choon Hui Teo, Alexander J. Smola, S. V. N. Vishwanathan, Quoc V. Le

Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2007

Conditional random fields for multi-agent reinforcement learning.

Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanathan

Proceedings of the Machine Learning, 2007

Learning to compress images and videos.

Li Cheng, S. V. N. Vishwanathan

Proceedings of the Machine Learning, 2007

Semi-Markov Models for Sequence Segmentation.

Qinfeng Shi, Yasemin Altun, Alexander J. Smola, S. V. N. Vishwanathan

Proceedings of the EMNLP-CoNLL 2007, 2007

2006

Step Size Adaptation in Reproducing Kernel Hilbert Space.

S. V. N. Vishwanathan, Nicol N. Schraudolph, Alexander J. Smola

J. Mach. Learn. Res., 2006

Kernel extrapolation.

S. V. N. Vishwanathan, Karsten M. Borgwardt, Omri Guttman, Alexander J. Smola

Neurocomputing, 2006

Class Prediction from Time Series Gene Expression Profiles Using Dynamical Systems Kernels.

Karsten M. Borgwardt, S. V. N. Vishwanathan, Hans-Peter Kriegel

Proceedings of the Biocomputing 2006, 2006

Fast Computation of Graph Kernels.

S. V. N. Vishwanathan, Karsten M. Borgwardt, Nicol N. Schraudolph

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

Fast Iterative Kernel PCA.

Nicol N. Schraudolph, Simon Günter, S. V. N. Vishwanathan

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

implicit Online Learning with Kernels.

Li Cheng, S. V. N. Vishwanathan, Dale Schuurmans, Shaojun Wang, Terry Caelli

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

Accelerated training of conditional random fields with stochastic gradient methods.

S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy

Proceedings of the Machine Learning, 2006

Fast and space efficient string kernels using suffix arrays.

Choon Hui Teo, S. V. N. Vishwanathan

Proceedings of the Machine Learning, 2006

An Online Discriminative Approach to Background Subtraction.

Li Cheng, Shaojun Wang, Dale Schuurmans, Terry Caelli, S. V. N. Vishwanathan

Proceedings of the Advanced Video and Signal Based Surveillance, 2006

2005

Boîte à outils SVM simple et rapide.

Gaëlle Loosli, Stéphane Canu, S. V. N. Vishwanathan, Alexander J. Smola, M. Chattopadhyay

Rev. d'Intelligence Artif., 2005

NICTA at TRECVID 2005 Shot Boundary Detection Task.

Zhenghua Yu, S. V. N. Vishwanathan, Alex Smola

Proceedings of the 2005 TREC Video Retrieval Evaluation, 2005

Large-Scale Multiclass Transduction.

Thomas Gärtner, Quoc V. Le, Simon Burton, Alexander J. Smola, S. V. N. Vishwanathan

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

Step size-adapted online support vector learning.

Alexandros Karatzoglou, S. V. N. Vishwanathan, Nicol N. Schraudolph, Alexander J. Smola

Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005

Protein function prediction via graph kernels.

Karsten M. Borgwardt, Cheng Soon Ong, Stefan Schönauer, S. V. N. Vishwanathan, Alexander J. Smola, Hans-Peter Kriegel

Proceedings of the Proceedings Thirteenth International Conference on Intelligent Systems for Molecular Biology 2005, 2005

Joint Regularization.

Karsten M. Borgwardt, Omri Guttman, S. V. N. Vishwanathan, Alexander J. Smola

Proceedings of the 13th European Symposium on Artificial Neural Networks, 2005

Leaving the Span.

Manfred K. Warmuth, S. V. N. Vishwanathan

Proceedings of the Learning Theory, 18th Annual Conference on Learning Theory, 2005

Learnability of Probabilistic Automata via Oracles.

Omri Guttman, S. V. N. Vishwanathan, Robert C. Williamson

Proceedings of the Algorithmic Learning Theory, 16th International Conference, 2005

Kernel Methods for Missing Variables.

Alexander J. Smola, S. V. N. Vishwanathan, Thomas Hofmann

Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, 2005

2004

Binet-Cauchy Kernels.

S. V. N. Vishwanathan, Alexander J. Smola

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

2003

Laplace Propagation.

Alexander J. Smola, Vishy Vishwanathan, Eleazar Eskin

Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

SimpleSVM.

S. V. N. Vishwanathan, Alexander J. Smola, M. Narasimha Murty

Proceedings of the Machine Learning, 2003

2002

Fast Kernels for String and Tree Matching.

S. V. N. Vishwanathan, Alexander J. Smola

Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

Geometric SVM: A Fast and Intuitive SVM Algorithm.

S. V. N. Vishwanathan, M. Narasimha Murty

Proceedings of the 16th International Conference on Pattern Recognition, 2002

Jigsawing : A Method to Create Virtual Examples in OCR data.

S. V. N. Vishwanathan, M. Narasimha Murty

Proceedings of the Soft Computing Systems - Design, Management and Applications, 2002

2001

Use of Multi-category Proximal SVM for Data Set Reduction.

S. V. N. Vishwanathan, M. Narasimha Murty

Proceedings of the Hybrid Information Systems, 2001

2000

Kohonen's SOM with cache.

S. V. N. Vishwanathan, M. Narasimha Murty

Pattern Recognit., 2000