 | 2009 |
|---|
| 13 |       | Vikas Sindhwani,
Prem Melville,
Richard D. Lawrence:
Uncertainty sampling and transductive experimental design for active dual supervision.
ICML 2009: 120 |
| 12 | | Tao Li,
Vikas Sindhwani,
Chris H. Q. Ding,
Yi Zhang:
Knowledge transformation for cross-domain sentiment classification.
SIGIR 2009: 716-717 |
| 2008 |
|---|
| 11 | | Vikas Sindhwani,
Prem Melville:
Document-Word Co-regularization for Semi-supervised Sentiment Analysis.
ICDM 2008: 1025-1030 |
| 10 | | Vikas Sindhwani,
David S. Rosenberg:
An RKHS for multi-view learning and manifold co-regularization.
ICML 2008: 976-983 |
| 9 | | Vikas Sindhwani,
Jianying Hu,
Aleksandra Mojsilovic:
Regularized Co-Clustering with Dual Supervision.
NIPS 2008: 1505-1512 |
| 2007 |
|---|
| 8 | | Vikas Sindhwani,
Wei Chu,
S. Sathiya Keerthi:
Semi-Supervised Gaussian Process Classifiers.
IJCAI 2007: 1059-1064 |
| 2006 |
|---|
| 7 | | Vikas Sindhwani,
S. Sathiya Keerthi,
Olivier Chapelle:
Deterministic annealing for semi-supervised kernel machines.
ICML 2006: 841-848 |
| 6 | | Olivier Chapelle,
Vikas Sindhwani,
S. Sathiya Keerthi:
Branch and Bound for Semi-Supervised Support Vector Machines.
NIPS 2006: 217-224 |
| 5 | | Wei Chu,
Vikas Sindhwani,
Zoubin Ghahramani,
S. Sathiya Keerthi:
Relational Learning with Gaussian Processes.
NIPS 2006: 289-296 |
| 4 | | S. Sathiya Keerthi,
Vikas Sindhwani,
Olivier Chapelle:
An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models.
NIPS 2006: 673-680 |
| 3 | | Vikas Sindhwani,
S. Sathiya Keerthi:
Large scale semi-supervised linear SVMs.
SIGIR 2006: 477-484 |
| 2 | | Mikhail Belkin,
Partha Niyogi,
Vikas Sindhwani:
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples.
Journal of Machine Learning Research 7: 2399-2434 (2006) |
| 2005 |
|---|
| 1 | | Vikas Sindhwani,
Partha Niyogi,
Mikhail Belkin:
Beyond the point cloud: from transductive to semi-supervised learning.
ICML 2005: 824-831 |
