Document-Word Co-Regularization for Semi-supervised Sentiment Analysis
V. Sindhwani, P. Melville
IEEE International Conference on Data Mining (ICDM), 2008
Regularized Co-Clustering with Dual Supervision
V. Sindhwani, J. Hu, A. Mojsilovic
Neural Information Processing Systems (NIPS), 2008
An RKHS for Multi-view Learning and Manifold Co-Regularization
V. Sindhwani, D. Rosenberg
International Conference on Machine Learning (ICML), 2008
Optimization Techniques for Semi-supervised Support Vector Machines
O. Chapelle, V. Sindhwani, S. S. Keerthi
Journal of Machine Learning Research (JMLR), 9(Feb):203--233, 2008
On Semi-supervised Kernel Methods
V. Sindhwani
Doctoral Thesis , 2007
Newton Methods for Fast Solution of Semi-supervised Linear SVMs
V. Sindhwani, S.S. Keerthi
Large Scale Kernel Machines MIT Press (Book Chapter), 2007
Semi-supervised Gaussian Processes
V. Sindhwani, W. Chu, S. S. Keerthi
International Joint Conference on Artificial Intelligence (IJCAI), 2007
Deterministic Annealing for Semi-supervised Kernel Machines
V. Sindhwani, S.S. Keerthi, O. Chapelle
International Conference on Machine Learning (ICML), 2006
Large Scale Semi-supervised Linear SVMs
V. Sindhwani, S.S. Keerthi
29th Annual International ACM SIGIR, 2006
Relational Learning with Gaussian Processes
W. Chu, V. Sindhwani, Z. Ghahramani, S. S. Keerthi
Neural Information Processing Systems (NIPS), 2006
Branch and Bound for Semi-supervised Support Vector Machines
O. Chapelle, V. Sindhwani, S. S. Keerthi
Neural Information Processing Systems (NIPS), 2006
An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models
S. S. Keerthi, V. Sindhwani, O. Chapelle
Neural Information Processing Systems (NIPS), 2006
The Geometric Basis of Semi-supervised Learning
V. Sindhwani, M. Belkin, P. Niyogi
Semi-supervised Learning MIT Press (Book Chapter), 2006
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
M. Belkin, P. Niyogi, V. Sindhwani
Journal of Machine Learning Research (JMLR), 2006
SVMlin: Fast Linear SVM Solvers for Supervised and Semi-supervised Learning
V. Sindhwani, P. Niyogi, M. Belkin
Workshop on Machine Learning Open Source Software, Neural Information Processing Systems (NIPS), 2006
Beyond the Point Cloud: from Transductive to Semi-supervised Learning
V. Sindhwani, P. Niyogi, M. Belkin
International Conference on Machine Learning (ICML), 2005
A Co-regularization Approach to Semi-supervised Learning with Multiple Views
V. Sindhwani, P. Niyogi, M. Belkin
Workshop on Learning with Multiple Views, International Conference on Machine Learning (ICML), 2005
On Manifold Regularization
M. Belkin, P. Niyogi, V. Sindhwani
Artificial Intelligence and Statistics (AISTATS), 2005
Linear Manifold Regularization for Large Scale Semi-supervised Learning
V. Sindhwani, P. Niyogi, M. Belkin
Workshop on Learning with Partially Classified Training Data, International Conference on Machine Learning (ICML), 2005
Kernel Machines for Semi-supervised Learning
V. Sindhwani
Masters Thesis , 2004
Feature Selection in MLPs and SVMs Based On Maximum Output Information
V. Sindhwani, S. Rakshit, D. Deodhare, D. Erdogmus, J.Principe, P.Niyogi
IEEE Trans. on Neural Networks,,V.15,N.4, 2004
Information Theoretic Performance Evaluation and Feature Selection in Machine Learning
V. Sindhwani
Bachelors Thesis , 2001
Information Theoretic Feature Crediting in Multiclass Support Vector Machines
V. Sindhwani, P. Bhattacharya, S. Rakshit
First Siam International Conference on Data Mining (SDM), 2001
