Learning Evolving and Emerging Topics in Social Media:
A Dynamic NMF Approach with Temporal Regularization
A. Saha and V. Sindhwani
Fifth ACM International Conference on Web Search and Data Mining (WSDM), 2012
Non-parametric Group Orthogonal Matching Pursuit for Sparse Learning with Multiple Kernels
V. Sindhwani and A. C. Lozano
Neural Information Processing Systems (NIPS) , 2011
Vector-valued Manifold Regularization
H. Q. Minh and V. Sindhwani
International Conference on Machine Learning (ICML) , 2011
Emerging Topic Detection Using Dictionary Learning
S. Kasiviswanathan, P. Melville, A. Banerjee, and V. Sindhwani
ACM Conference on Information and Knowledge Management (CIKM) , 2011
SystemML: Declarative Machine Learning on MapReduce
A. Ghoting, R. Krishnamurthy, E. Pednault, B. Reinwald, V. Sindhwani, S. Tatikonda, Y. Tian, S. Vaithyanathan
IEEE International Conference on Data Engineering (ICDE) , 2011
Concept Labeling: Building Text Classifiers with Minimal Supervision.
V. Chenthamarakshan, P. Melville, V. Sindhwani and R. D. Lawrence
International Joint Conference on Artificial Intelligence (IJCAI) , 2011
Block Variable Selection in Multivariate Regression and High-dimensional Causal Inference
A.C. Lozano and V. Sindhwani
Neural Information Processing Systems (NIPS) , 2010
Dynamic NMFs with Temporal Regularization for Online Analysis of Streaming Text
A. Saha, V. Sindhwani
Machine Learning for Social Computing (NIPS Workshop) , 2010
Rank Selection in Low-Rank Matrix Approximations
B. Kanagal, V. Sindhwani
Low-Rank Methods for Large-scale Machine Learning (NIPS Workshop) , 2010
One-class Matrix Completion with Low-Density Factorizations
V. Sindhwani, S.S. Bucak, J. Hu, A. Mojsilovic
IEEE International Conference on Data Mining (ICDM) , 2010
Bridging Domains with Words: Opinion Analysis with Matrix Trifactorizations
T. Li, V. Sindhwani, C.Ding, Y.Zhang
SIAM International Conference on Data Mining (SDM) , 2010
Recommender Systems
P. Melville, V. Sindhwani
Encyclopedia of Machine Learning, Springer, 2010.
Social Media Analytics
R. Lawrence, P. Melville, C. Perlich, V.Sindhwani, E.Meliksetian, P.Hsueh, Y. Liu
Uncertainty Sampling and Transductive Experimental Design for Active Dual Supervision
V. Sindhwani, P. Melville, R. Lawrence
International Conference on Machine Learning (ICML), 2009
Sparse Least Squares Methods in the Parallel Machine Learning (PML) Framework
R. Natarajan, V.Sindhwani, S. Tatikonda
Large Scale Data Mining: Theory and Applications Workshop
IEEE International Conference on Data Mining (ICDM), 2009
A Kernel for Semi-supervised Learning with Multi-view Point Cloud Regularization
D. Rosenberg, V. Sindhwani, P. Bartlett, P. Niyogi
IEEE Signal Processing Magazine, 2009 (to appear)
A Non-negative Matrix Tri-factorization Approach to Sentiment Classification with Lexical Prior Knowledge
T. Li, Y. Zhang and V. Sindhwani
Association for Computational Linguistics (ACL), 2009
Winning the KDD Cup Orange Challenge with Ensemble Selection
A. Niculescu-Mizil, C. Perlich, G. Swirszcz, V. Sindhwani, Y. Liu, P. Melville, D. Wang, J. Xiao, J. Hu, M. Singh, W. X. Shang, Y.F. Zhu
Journal of Machine Learning Research (JMLR proceeding series), 2009
Social Media Analytics: Channeling the Power of the Blogosphere for Marketing Insight.
P. Melville, V. Sindhwani, R. Lawrence
Workshop on Information in Networks (WIN), 2009
Knowledge Transformation for Cross-domain Sentiment Classification
T. Li, V. Sindhwani, C. Ding, Y. Zhang
32nd Annual ACM SIGIR (Poster), 2009
Active Dual Supervision: Reducing the Cost of Annotating Examples and Features
P. Melville and V. Sindhwani
NAACL HLT 2009 Workshop on Active Learning for NLP, 2009
Data Quality from Crowdsourcing: A Study of Annotation Selection Criteria.
P. Hsueh, P. Melville, V. Sindhwani
NAACL HLT 2009 Workshop on Active Learning for NLP, 2009
Leveraging Social Networks for Corporate Staffing and Expert Recommendation
V. Chenthamarakshan, K. Dey, J. Hu, A. Mojsilovic, W. Riddle, V. Sindhwani
IBM Journal of Research and Development, 2009
Regularized Co-Clustering With Dual Supervision
V. Sindhwani, J. Hu, A. Mojsilovic
Neural Information Processing Systems (NIPS), 2008
Document-Word Co-Regularization for Semi-supervised Sentiment Analysis
V. Sindhwani, P. Melville
IEEE International Conference on Data Mining (ICDM), 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 9(Feb):203--233, 2008
On Semi-supervised Kernel Methods
V. Sindhwani
Doctoral Thesis , University of Chicago, 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
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
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
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
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
