S. V. N. Vishwanathan

127 papers A* 26A 14B 6C 2Misc 1Journal 51Unranked 26

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Retrieval-augmented Encoders for Extreme Multi-label Text Classification. CoRR Yau-Shian Wang, Wei-Cheng Chang, Jyun-Yu Jiang, Jiong Zhang, Hsiang-Fu Yu, S. V. N. Vishwanathan
2024	—	`conf`	Bi-CAT: Improving Robustness of LLM-based Text Rankers to Conditional Distribution Shifts. WWW (Companion Volume) Sriram Srinivasan, Stephen Sheng, Rishabh Deshmukh, Chen Luo, Yesh Dattatreya, Subhajit Sanyal, S. V. N. Vishwanathan
2024	A	`conf`	PEFA: Parameter-Free Adapters for Large-scale Embedding-based Retrieval Models. WSDM Wei-Cheng Chang, Jyun-Yu Jiang, Jiong Zhang, Mutasem Al-Darabsah, Choon Hui Teo, Cho-Jui Hsieh, Hsiang-Fu Yu, S. V. N. Vishwanathan
2023	J	`jnl`	PEFA: Parameter-Free Adapters for Large-scale Embedding-based Retrieval Models. CoRR Wei-Cheng Chang, Jyun-Yu Jiang, Jiong Zhang, Mutasem Al-Darabsah, Choon Hui Teo, Cho-Jui Hsieh, Hsiang-Fu Yu, S. V. N. Vishwanathan
2023	—	`conf`	Web-Scale Semantic Product Search with Large Language Models. PAKDD (3) Aashiq Muhamed, Sriram Srinivasan, Choon Hui Teo, Qingjun Cui, Belinda Zeng, Trishul Chilimbi, S. V. N. Vishwanathan
2022	A*	`conf`	Toward Understanding Privileged Features Distillation in Learning-to-Rank. NeurIPS Shuo Yang, Sujay Sanghavi, Holakou Rahmanian, Jan Bakus, S. V. N. Vishwanathan
2022	J	`jnl`	Toward Understanding Privileged Features Distillation in Learning-to-Rank. CoRR Shuo Yang, Sujay Sanghavi, Holakou Rahmanian, Jan Bakus, S. V. N. Vishwanathan
2021	J	`jnl`	Embracing Structure in Data for Billion-Scale Semantic Product Search. CoRR Vihan Lakshman, Choon Hui Teo, Xiaowen Chu, Priyanka Nigam, Abhinandan Patni, Pooja Maknikar, S. V. N. Vishwanathan
2020	J	`jnl`	DS-FACTO: Doubly Separable Factorization Machines. CoRR Parameswaran Raman, S. V. N. Vishwanathan
2019	A	`conf`	A Zero Attention Model for Personalized Product Search. CIKM Qingyao Ai, Daniel N. Hill, S. V. N. Vishwanathan, W. Bruce Croft
2019	J	`jnl`	A Zero Attention Model for Personalized Product Search. CoRR Qingyao Ai, Daniel N. Hill, S. V. N. Vishwanathan, W. Bruce Croft
2019	A	`conf`	Extreme Stochastic Variational Inference: Distributed Inference for Large Scale Mixture Models. AISTATS Jiong Zhang, Parameswaran Raman, Shihao Ji, Hsiang-Fu Yu, S. V. N. Vishwanathan, Inderjit S. Dhillon
2019	A*	`conf`	Scaling Multinomial Logistic Regression via Hybrid Parallelism. KDD Parameswaran Raman, Sriram Srinivasan, Shin Matsushima, Xinhua Zhang, Hyokun Yun, S. V. N. Vishwanathan
2019	A*	`conf`	Whole Page Optimization with Global Constraints. KDD Weicong Ding, Dinesh Govindaraj, S. V. N. Vishwanathan
2018	J	`jnl`	Adaptive, Personalized Diversity for Visual Discovery. CoRR Choon Hui Teo, Houssam Nassif, Daniel N. Hill, Sriram Srinivasan, Mitchell Goodman, Vijai Mohan, S. V. N. Vishwanathan
2018	J	`jnl`	An Efficient Bandit Algorithm for Realtime Multivariate Optimization. CoRR Daniel N. Hill, Houssam Nassif, Yi Liu, Anand Iyer, S. V. N. Vishwanathan
2018	A	`conf`	Batch-Expansion Training: An Efficient Optimization Framework. AISTATS Michal Derezinski, Dhruv Mahajan, S. Sathiya Keerthi, S. V. N. Vishwanathan, Markus Weimer
2018	J	`jnl`	Diversifying Music Recommendations. CoRR Houssam Nassif, Kemal Oral Cansizlar, Mitchell Goodman, S. V. N. Vishwanathan
2018	B	`conf`	Online Learning of Combinatorial Objects via Extended Formulation. ALT Holakou Rahmanian, David P. Helmbold, S. V. N. Vishwanathan
2017	—	`ed.`	Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA Isabelle Guyon, Ulrike von Luxburg, Samy Bengio, Hanna M. Wallach, Rob Fergus, S. V. N. Vishwanathan, Roman Garnett
2017	A*	`conf`	An Efficient Bandit Algorithm for Realtime Multivariate Optimization. KDD Daniel N. Hill, Houssam Nassif, Yi Liu, Anand Iyer, S. V. N. Vishwanathan
2017	J	`jnl`	Batch-Expansion Training: An Efficient Optimization Paradigm for Machine Learning. CoRR Michal Derezinski, Dhruv Mahajan, S. Sathiya Keerthi, S. V. N. Vishwanathan, Markus Weimer
2017	J	`jnl`	Colors - Messengers of Concepts: Visual Design Mining for Learning Color Semantics. ACM Trans. Comput. Hum. Interact. Ali Jahanian, Shaiyan Keshvari, S. V. N. Vishwanathan, Jan P. Allebach
2017	—	`conf`	Distributed Stochastic Optimization of Regularized Risk via Saddle-Point Problem. ECML/PKDD (1) Shin Matsushima, Hyokun Yun, Xinhua Zhang, S. V. N. Vishwanathan
2017	J	`jnl`	Online Dynamic Programming. CoRR Holakou Rahmanian, S. V. N. Vishwanathan, Manfred K. Warmuth
2016	A	`conf`	Adaptive, Personalized Diversity for Visual Discovery. RecSys Choon Hui Teo, Houssam Nassif, Daniel N. Hill, Sriram Srinivasan, Mitchell Goodman, Vijai Mohan, S. V. N. Vishwanathan
2016	A*	`conf`	BlackOut: Speeding up Recurrent Neural Network Language Models With Very Large Vocabularies. ICLR Shihao Ji, S. V. N. Vishwanathan, Nadathur Satish, Michael J. Anderson, Pradeep Dubey
2016	J	`jnl`	DS-MLR: Exploiting Double Separability for Scaling up Distributed Multinomial Logistic Regression. CoRR Parameswaran Raman, Shin Matsushima, Xinhua Zhang, Hyokun Yun, S. V. N. Vishwanathan
2016	J	`jnl`	Extended Formulation for Online Learning of Combinatorial Objects. CoRR Holakou Rahmanian, S. V. N. Vishwanathan, David P. Helmbold
2016	J	`jnl`	Nomadic Computing for Big Data Analytics. Computer Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, S. V. N. Vishwanathan, Inderjit S. Dhillon
2016	A*	`conf`	WordRank: Learning Word Embeddings via Robust Ranking. EMNLP Shihao Ji, Hyokun Yun, Pinar Yanardag, Shin Matsushima, S. V. N. Vishwanathan
2015	A*	`conf`	A Scalable Asynchronous Distributed Algorithm for Topic Modeling. WWW Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, S. V. N. Vishwanathan, Inderjit S. Dhillon
2015	—	`conf`	A Structural Smoothing Framework For Robust Graph Comparison. NIPS Pinar Yanardag, S. V. N. Vishwanathan
2015	—	`conf`	Autonomous color theme extraction from images using saliency. IMAWM Ali Jahanian, S. V. N. Vishwanathan, Jan P. Allebach
2015	J	`jnl`	Colors $-$Messengers of Concepts: Visual Design Mining for Learning Color Semantics. CoRR Ali Jahanian, S. V. N. Vishwanathan, Jan P. Allebach
2015	A*	`conf`	Deep Graph Kernels. KDD Pinar Yanardag, S. V. N. Vishwanathan
2015	—	`conf`	Learning visual balance from large-scale datasets of aesthetically highly rated images. Human Vision and Electronic Imaging Ali Jahanian, S. V. N. Vishwanathan, Jan P. Allebach
2015	A	`conf`	Preface. AISTATS Guy Lebanon, S. V. N. Vishwanathan
2015	A	`ed.`	Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, AISTATS 2015, San Diego, California, USA, May 9-12, 2015 AISTATS Guy Lebanon, S. V. N. Vishwanathan
2015	J	`jnl`	Totally Corrective Boosting with Cardinality Penalization. CoRR Vasil S. Denchev, Nan Ding, Shin Matsushima, S. V. N. Vishwanathan, Hartmut Neven
2015	J	`jnl`	WordRank: Learning Word Embeddings via Robust Ranking. CoRR Shihao Ji, Hyokun Yun, Pinar Yanardag, Shin Matsushima, S. V. N. Vishwanathan
2014	J	`jnl`	A Scalable Asynchronous Distributed Algorithm for Topic Modeling. CoRR Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, S. V. N. Vishwanathan, Inderjit S. Dhillon
2014	J	`jnl`	Accelerated training of max-margin Markov networks with kernels. Theor. Comput. Sci. Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan
2014	J	`jnl`	Distributed Stochastic Optimization of the Regularized Risk. CoRR Shin Matsushima, Hyokun Yun, S. V. N. Vishwanathan
2014	A*	`conf`	Juxtapoze: supporting serendipity and creative expression in clipart compositions. CHI William Benjamin, Senthil K. Chandrasegaran, Devarajan Ramanujan, Niklas Elmqvist, S. V. N. Vishwanathan, Karthik Ramani
2014	J	`jnl`	Modeling Attractiveness and Multiple Clicks in Sponsored Search Results. CoRR Dinesh Govindaraj, Tao Wang, S. V. N. Vishwanathan
2014	J	`jnl`	NOMAD: Nonlocking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion. Proc. VLDB Endow. Hyokun Yun, Hsiang-Fu Yu, Cho-Jui Hsieh, S. V. N. Vishwanathan, Inderjit S. Dhillon
2014	J	`jnl`	Ranking via Robust Binary Classification and Parallel Parameter Estimation in Large-Scale Data. CoRR Hyokun Yun, Parameswaran Raman, S. V. N. Vishwanathan
2014	—	`conf`	Ranking via Robust Binary Classification. NIPS Hyokun Yun, Parameswaran Raman, S. V. N. Vishwanathan
2014	J	`jnl`	The Structurally Smoothed Graphlet Kernel. CoRR Pinar Yanardag, S. V. N. Vishwanathan
2013	J	`jnl`	Distributed Autonomous Online Learning: Regrets and Intrinsic Privacy-Preserving Properties. IEEE Trans. Knowl. Data Eng. Feng Yan, Shreyas Sundaram, S. V. N. Vishwanathan, Yuan (Alan) Qi
2013	J	`jnl`	NOMAD: Non-locking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion. CoRR Hyokun Yun, Hsiang-Fu Yu, Cho-Jui Hsieh, S. V. N. Vishwanathan, Inderjit S. Dhillon
2013	A*	`conf`	Open Problem: Lower bounds for Boosting with Hadamard Matrices. COLT Jiazhong Nie, Manfred K. Warmuth, S. V. N. Vishwanathan, Xinhua Zhang
2012	J	`jnl`	Efficient max-margin multi-label classification with applications to zero-shot learning. Mach. Learn. Bharath Hariharan, S. V. N. Vishwanathan, Manik Varma
2012	J	`jnl`	Efficiently Sampling Multiplicative Attribute Graphs Using a Ball-Dropping Process CoRR Hyokun Yun, S. V. N. Vishwanathan
2012	A	`conf`	Fair and balanced: learning to present news stories. WSDM Amr Ahmed, Choon Hui Teo, S. V. N. Vishwanathan, Alexander J. Smola
2012	A*	`conf`	Linear support vector machines via dual cached loops. KDD Shin Matsushima, S. V. N. Vishwanathan, Alexander J. Smola
2012	A	`conf`	Quilting Stochastic Kronecker Product Graphs to Generate Multiplicative Attribute Graphs. AISTATS Hyokun Yun, S. V. N. Vishwanathan
2012	A*	`conf`	Robust Classification with Adiabatic Quantum Optimization. ICML Vasil S. Denchev, Nan Ding, S. V. N. Vishwanathan, Hartmut Neven
2012	A*	`conf`	SPF-GMKL: generalized multiple kernel learning with a million kernels. KDD Ashesh Jain, S. V. N. Vishwanathan, Manik Varma
2012	J	`jnl`	Smoothing Multivariate Performance Measures CoRR Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan
2012	J	`jnl`	Smoothing multivariate performance measures. J. Mach. Learn. Res. Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan
2012	J	`jnl`	The Entire Quantile Path of a Risk-Agnostic SVM Classifier CoRR Jin Yu, S. V. N. Vishwanathan, Jian Zhang
2011	B	`conf`	Accelerated Training of Max-Margin Markov Networks with Kernels. ALT Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan
2011	J	`jnl`	Heat Walk: Robust Salient Segmentation of Non-rigid Shapes. Comput. Graph. Forum William Benjamin, Andrew Wood Polk, S. V. N. Vishwanathan, Karthik Ramani
2011	J	`jnl`	Introduction to the special issue on mining and learning with graphs. Mach. Learn. S. V. N. Vishwanathan, Samuel Kaski, Jennifer Neville, Stefan Wrobel
2011	A*	`conf`	New Approximation Algorithms for Minimum Enclosing Convex Shapes. SODA Ankan Saha, S. V. N. Vishwanathan, Xinhua Zhang
2011	J	`jnl`	Quilting Stochastic Kronecker Product Graphs to Generate Multiplicative Attribute Graphs CoRR Hyokun Yun, S. V. N. Vishwanathan
2011	A	`conf`	Smoothing Multivariate Performance Measures. UAI Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan
2011	A*	`conf`	sLLE: Spherical locally linear embedding with applications to tomography. CVPR Yi Fang, Mengtian Sun, S. V. N. Vishwanathan, Karthik Ramani
2011	—	`conf`	t-divergence Based Approximate Inference. NIPS Nan Ding, S. V. N. Vishwanathan, Yuan (Alan) Qi
2010	J	`jnl`	A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning. J. Mach. Learn. Res. Jin Yu, S. V. N. Vishwanathan, Simon Günter, Nicol N. Schraudolph
2010	J	`jnl`	Bundle Methods for Regularized Risk Minimization. J. Mach. Learn. Res. Choon Hui Teo, S. V. N. Vishwanathan, Alexander J. Smola, Quoc V. Le
2010	J	`jnl`	Cooperative Autonomous Online Learning CoRR Feng Yan, S. V. N. Vishwanathan, Yuan (Alan) Qi
2010	J	`jnl`	Faster Rates for training Max-Margin Markov Networks CoRR Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan
2010	J	`jnl`	Graph Kernels. J. Mach. Learn. Res. S. V. N. Vishwanathan, Nicol N. Schraudolph, Risi Kondor, Karsten M. Borgwardt
2010	A*	`conf`	Large Scale Max-Margin Multi-Label Classification with Priors. ICML Bharath Hariharan, Lihi Zelnik-Manor, S. V. N. Vishwanathan, Manik Varma
2010	—	`conf`	Lower Bounds on Rate of Convergence of Cutting Plane Methods. NIPS Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan
2010	—	`conf`	Multiple Kernel Learning and the SMO Algorithm. NIPS S. V. N. Vishwanathan, Zhaonan Sun, Nawanol Ampornpunt, Manik Varma
2010	—	`conf`	Multitask Learning without Label Correspondences. NIPS Novi Quadrianto, Alexander J. Smola, Tibério S. Caetano, S. V. N. Vishwanathan, James Petterson
2010	J	`jnl`	Regularized Risk Minimization by Nesterov's Accelerated Gradient Methods: Algorithmic Extensions and Empirical Studies CoRR Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan
2010	—	`conf`	Tied Kronecker product graph models to capture variance in network populations. Allerton Sebastián Moreno, Sergey Kirshner, Jennifer Neville, S. V. N. Vishwanathan
2010	—	`conf`	t-logistic regression. NIPS Nan Ding, S. V. N. Vishwanathan
2009	J	`jnl`	Efficient Approximation Algorithms for Minimum Enclosing Convex Shapes CoRR Ankan Saha, S. V. N. Vishwanathan
2009	A	`conf`	Efficient graphlet kernels for large graph comparison. AISTATS Nino Shervashidze, S. V. N. Vishwanathan, Tobias Petri, Kurt Mehlhorn, Karsten M. Borgwardt
2009	J	`jnl`	Hash Kernels for Structured Data. J. Mach. Learn. Res. Qinfeng Shi, James Petterson, Gideon Dror, John Langford, Alexander J. Smola, S. V. N. Vishwanathan
2009	J	`jnl`	Lower Bounds for BMRM and Faster Rates for Training SVMs CoRR Ankan Saha, Xinhua Zhang, S. V. N. Vishwanathan
2009	A	`conf`	The Entire Quantile Path of a Risk-Agnostic SVM Classifier. UAI Jin Yu, S. V. N. Vishwanathan, Jian Zhang
2009	A*	`conf`	Tutorial summary: Survey of boosting from an optimization perspective. ICML Manfred K. Warmuth, S. V. N. Vishwanathan
2009	A	`conf`	Variable Metric Stochastic Approximation Theory. AISTATS Peter Sunehag, Jochen Trumpf, S. V. N. Vishwanathan, Nicol N. Schraudolph
2008	A*	`conf`	A quasi-Newton approach to non-smooth convex optimization. ICML Jin Yu, S. V. N. Vishwanathan, Simon Günter, Nicol N. Schraudolph
2008	A*	`conf`	Consistent image analogies using semi-supervised learning. CVPR Li Cheng, S. V. N. Vishwanathan, Xinhua Zhang
2008	B	`conf`	Entropy Regularized LPBoost. ALT Manfred K. Warmuth, Karen A. Glocer, S. V. N. Vishwanathan
2008	J	`jnl`	Graph Kernels CoRR S. V. N. Vishwanathan, Karsten M. Borgwardt, Imre Risi Kondor, Nicol N. Schraudolph
2007	A*	`conf`	A scalable modular convex solver for regularized risk minimization. KDD Choon Hui Teo, Alexander J. Smola, S. V. N. Vishwanathan, Quoc V. Le
2007	—	`conf`	An Efficient Sampling Scheme For Comparison of Large Graphs. MLG Karsten M. Borgwardt, Tobias Petri, S. V. N. Vishwanathan, Hans-Peter Kriegel
2007	J	`jnl`	Binet-Cauchy Kernels on Dynamical Systems and its Application to the Analysis of Dynamic Scenes. Int. J. Comput. Vis. S. V. N. Vishwanathan, Alexander J. Smola, René Vidal
2007	—	`conf`	Bundle Methods for Machine Learning. NIPS Alexander J. Smola, S. V. N. Vishwanathan, Quoc V. Le
2007	A*	`conf`	Conditional random fields for multi-agent reinforcement learning. ICML Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanathan
2007	J	`jnl`	Fast Iterative Kernel Principal Component Analysis. J. Mach. Learn. Res. Simon Günter, Nicol N. Schraudolph, S. V. N. Vishwanathan
2007	A*	`conf`	Learning to compress images and videos. ICML Li Cheng, S. V. N. Vishwanathan
2007	—	`conf`	Semi-Markov Models for Sequence Segmentation. EMNLP-CoNLL Qinfeng Shi, Yasemin Altun, Alexander J. Smola, S. V. N. Vishwanathan
2006	A*	`conf`	Accelerated training of conditional random fields with stochastic gradient methods. ICML S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy
2006	B	`conf`	An Online Discriminative Approach to Background Subtraction. AVSS Li Cheng, Shaojun Wang, Dale Schuurmans, Terry Caelli, S. V. N. Vishwanathan
2006	Misc	`conf`	Class Prediction from Time Series Gene Expression Profiles Using Dynamical Systems Kernels. Pacific Symposium on Biocomputing Karsten M. Borgwardt, S. V. N. Vishwanathan, Hans-Peter Kriegel
2006	—	`conf`	Fast Computation of Graph Kernels. NIPS S. V. N. Vishwanathan, Karsten M. Borgwardt, Nicol N. Schraudolph
2006	—	`conf`	Fast Iterative Kernel PCA. NIPS Nicol N. Schraudolph, Simon Günter, S. V. N. Vishwanathan
2006	A*	`conf`	Fast and space efficient string kernels using suffix arrays. ICML Choon Hui Teo, S. V. N. Vishwanathan
2006	J	`jnl`	Kernel extrapolation. Neurocomputing S. V. N. Vishwanathan, Karsten M. Borgwardt, Omri Guttman, Alexander J. Smola
2006	J	`jnl`	Step Size Adaptation in Reproducing Kernel Hilbert Space. J. Mach. Learn. Res. S. V. N. Vishwanathan, Nicol N. Schraudolph, Alexander J. Smola
2006	—	`conf`	implicit Online Learning with Kernels. NIPS Li Cheng, S. V. N. Vishwanathan, Dale Schuurmans, Shaojun Wang, Terry Caelli
2005	J	`jnl`	Boîte à outils SVM simple et rapide. Rev. d'Intelligence Artif. Gaëlle Loosli, Stéphane Canu, S. V. N. Vishwanathan, Alexander J. Smola, M. Chattopadhyay
2005	B	`conf`	Joint Regularization. ESANN Karsten M. Borgwardt, Omri Guttman, S. V. N. Vishwanathan, Alexander J. Smola
2005	A	`conf`	Kernel Methods for Missing Variables. AISTATS Alexander J. Smola, S. V. N. Vishwanathan, Thomas Hofmann
2005	—	`conf`	Large-Scale Multiclass Transduction. NIPS Thomas Gärtner, Quoc V. Le, Simon Burton, Alexander J. Smola, S. V. N. Vishwanathan
2005	B	`conf`	Learnability of Probabilistic Automata via Oracles. ALT Omri Guttman, S. V. N. Vishwanathan, Robert C. Williamson
2005	A*	`conf`	Leaving the Span. COLT Manfred K. Warmuth, S. V. N. Vishwanathan
2005	—	`conf`	NICTA at TRECVID 2005 Shot Boundary Detection Task. TRECVID Zhenghua Yu, S. V. N. Vishwanathan, Alex Smola
2005	—	`conf`	Protein function prediction via graph kernels. ISMB (Supplement of Bioinformatics) Karsten M. Borgwardt, Cheng Soon Ong, Stefan Schönauer, S. V. N. Vishwanathan, Alexander J. Smola, Hans-Peter Kriegel
2005	—	`conf`	Step size-adapted online support vector learning. ISSPA Alexandros Karatzoglou, S. V. N. Vishwanathan, Nicol N. Schraudolph, Alexander J. Smola
2004	—	`conf`	Binet-Cauchy Kernels. NIPS S. V. N. Vishwanathan, Alexander J. Smola
2003	A*	`conf`	SimpleSVM. ICML S. V. N. Vishwanathan, Alexander J. Smola, M. Narasimha Murty
2002	—	`conf`	Fast Kernels for String and Tree Matching. NIPS S. V. N. Vishwanathan, Alexander J. Smola
2002	—	`conf`	Geometric SVM: A Fast and Intuitive SVM Algorithm. ICPR (2) S. V. N. Vishwanathan, M. Narasimha Murty
2002	C	`conf`	Jigsawing : A Method to Create Virtual Examples in OCR data. HIS S. V. N. Vishwanathan, M. Narasimha Murty
2001	C	`conf`	Use of Multi-category Proximal SVM for Data Set Reduction. HIS S. V. N. Vishwanathan, M. Narasimha Murty
2000	J	`jnl`	Kohonen's SOM with cache. Pattern Recognit. S. V. N. Vishwanathan, M. Narasimha Murty