S. V. N. Vishwanathan
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
48
Venues
21
Active years
2001–2024
Best venue rank
A*
Where they publish
Papers
48 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2024 | WWW | 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 |
| 2024 | WSDM | 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 |
| 2023 | PAKDD | 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 |
| 2019 | AISTATS | 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 |
| 2019 | CIKM | A Zero Attention Model for Personalized Product Search. | Qingyao Ai, Daniel N. Hill, S. V. N. Vishwanathan, W. Bruce Croft |
| 2019 | KDD | Whole Page Optimization with Global Constraints. | Weicong Ding, Dinesh Govindaraj, S. V. N. Vishwanathan |
| 2019 | KDD | Scaling Multinomial Logistic Regression via Hybrid Parallelism. | Parameswaran Raman, Sriram Srinivasan, Shin Matsushima, Xinhua Zhang, Hyokun Yun, S. V. N. Vishwanathan |
| 2018 | AISTATS | Batch-Expansion Training: An Efficient Optimization Framework. | Michal Derezinski, Dhruv Mahajan, S. Sathiya Keerthi, S. V. N. Vishwanathan, Markus Weimer |
| 2018 | ALT | Online Learning of Combinatorial Objects via Extended Formulation. | Holakou Rahmanian, David P. Helmbold, S. V. N. Vishwanathan |
| 2017 | KDD | An Efficient Bandit Algorithm for Realtime Multivariate Optimization. | Daniel N. Hill, Houssam Nassif, Yi Liu, Anand Iyer, S. V. N. Vishwanathan |
| 2016 | EMNLP | WordRank: Learning Word Embeddings via Robust Ranking. | Shihao Ji, Hyokun Yun, Pinar Yanardag, Shin Matsushima, S. V. N. Vishwanathan |
| 2016 | RecSys | Adaptive, Personalized Diversity for Visual Discovery. | Choon Hui Teo, Houssam Nassif, Daniel N. Hill, Sriram Srinivasan, Mitchell Goodman, Vijai Mohan, S. V. N. Vishwanathan |
| 2015 | AISTATS | Preface. | Guy Lebanon, S. V. N. Vishwanathan |
| 2015 | KDD | Deep Graph Kernels. | Pinar Yanardag, S. V. N. Vishwanathan |
| 2015 | WWW | A Scalable Asynchronous Distributed Algorithm for Topic Modeling. | Hsiang-Fu Yu, Cho-Jui Hsieh, Hyokun Yun, S. V. N. Vishwanathan, Inderjit S. Dhillon |
| 2014 | CHI | Juxtapoze: supporting serendipity and creative expression in clipart compositions. | William Benjamin, Senthil K. Chandrasegaran, Devarajan Ramanujan, Niklas Elmqvist, S. V. N. Vishwanathan, Karthik Ramani |
| 2013 | COLT | Open Problem: Lower bounds for Boosting with Hadamard Matrices. | Jiazhong Nie, Manfred K. Warmuth, S. V. N. Vishwanathan, Xinhua Zhang |
| 2012 | ICML | Robust Classification with Adiabatic Quantum Optimization. | Vasil S. Denchev, Nan Ding, S. V. N. Vishwanathan, Hartmut Neven |
| 2012 | KDD | SPF-GMKL: generalized multiple kernel learning with a million kernels. | Ashesh Jain, S. V. N. Vishwanathan, Manik Varma |
| 2012 | KDD | Linear support vector machines via dual cached loops. | Shin Matsushima, S. V. N. Vishwanathan, Alexander J. Smola |
| 2012 | WSDM | Fair and balanced: learning to present news stories. | Amr Ahmed, Choon Hui Teo, S. V. N. Vishwanathan, Alexander J. Smola |
| 2011 | ALT | Accelerated Training of Max-Margin Markov Networks with Kernels. | Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan |
| 2011 | CVPR | sLLE: Spherical locally linear embedding with applications to tomography. | Yi Fang, Mengtian Sun, S. V. N. Vishwanathan, Karthik Ramani |
| 2011 | SODA | New Approximation Algorithms for Minimum Enclosing Convex Shapes. | Ankan Saha, S. V. N. Vishwanathan, Xinhua Zhang |
| 2011 | UAI | Smoothing Multivariate Performance Measures. | Xinhua Zhang, Ankan Saha, S. V. N. Vishwanathan |
| 2010 | ICML | Large Scale Max-Margin Multi-Label Classification with Priors. | Bharath Hariharan, Lihi Zelnik-Manor, S. V. N. Vishwanathan, Manik Varma |
| 2009 | ICML | Tutorial summary: Survey of boosting from an optimization perspective. | Manfred K. Warmuth, S. V. N. Vishwanathan |
| 2009 | UAI | The Entire Quantile Path of a Risk-Agnostic SVM Classifier. | Jin Yu, S. V. N. Vishwanathan, Jian Zhang |
| 2008 | ALT | Entropy Regularized LPBoost. | Manfred K. Warmuth, Karen A. Glocer, S. V. N. Vishwanathan |
| 2008 | CVPR | Consistent image analogies using semi-supervised learning. | Li Cheng, S. V. N. Vishwanathan, Xinhua Zhang |
| 2008 | ICML | A quasi-Newton approach to non-smooth convex optimization. | Jin Yu, S. V. N. Vishwanathan, Simon Gnter, Nicol N. Schraudolph |
| 2007 | EMNLP | Semi-Markov Models for Sequence Segmentation. | Qinfeng Shi, Yasemin Altun, Alexander J. Smola, S. V. N. Vishwanathan |
| 2007 | ICML | Learning to compress images and videos. | Li Cheng, S. V. N. Vishwanathan |
| 2007 | ICML | Conditional random fields for multi-agent reinforcement learning. | Xinhua Zhang, Douglas Aberdeen, S. V. N. Vishwanathan |
| 2007 | KDD | A scalable modular convex solver for regularized risk minimization. | Choon Hui Teo, Alexander J. Smola, S. V. N. Vishwanathan, Quoc V. Le |
| 2006 | AVSS | An Online Discriminative Approach to Background Subtraction. | Li Cheng, Shaojun Wang, Dale Schuurmans, Terry Caelli, S. V. N. Vishwanathan |
| 2006 | ICML | Fast and space efficient string kernels using suffix arrays. | Choon Hui Teo, S. V. N. Vishwanathan |
| 2006 | ICML | Accelerated training of conditional random fields with stochastic gradient methods. | S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark W. Schmidt, Kevin P. Murphy |
| 2006 | PSB | Class Prediction from Time Series Gene Expression Profiles Using Dynamical Systems Kernels. | Karsten M. Borgwardt, S. V. N. Vishwanathan, Hans-Peter Kriegel |
| 2005 | AISTATS | Kernel Methods for Missing Variables. | Alexander J. Smola, S. V. N. Vishwanathan, Thomas Hofmann |
| 2005 | ALT | Learnability of Probabilistic Automata via Oracles. | Omri Guttman, S. V. N. Vishwanathan, Robert C. Williamson |
| 2005 | COLT | Leaving the Span. | Manfred K. Warmuth, S. V. N. Vishwanathan |
| 2005 | ESANN | Joint Regularization. | Karsten M. Borgwardt, Omri Guttman, S. V. N. Vishwanathan, Alexander J. Smola |
| 2005 | ISMB | Protein function prediction via graph kernels. | Karsten M. Borgwardt, Cheng Soon Ong, Stefan Schnauer, S. V. N. Vishwanathan, Alexander J. Smola, Hans-Peter Kriegel |
| 2003 | ICML | SimpleSVM. | S. V. N. Vishwanathan, Alexander J. Smola, M. Narasimha Murty |
| 2002 | HIS | Jigsawing : A Method to Create Virtual Examples in OCR data. | S. V. N. Vishwanathan, M. Narasimha Murty |
| 2002 | ICPR | Geometric SVM: A Fast and Intuitive SVM Algorithm. | S. V. N. Vishwanathan, M. Narasimha Murty |
| 2001 | HIS | Use of Multi-category Proximal SVM for Data Set Reduction. | S. V. N. Vishwanathan, M. Narasimha Murty |