Sivaraman Balakrishnan
Sivaraman Balakrishnan
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TitleCited byYear
Statistical guarantees for the EM algorithm: From population to sample-based analysis
S Balakrishnan, MJ Wainwright, B Yu
The Annals of Statistics 45 (1), 77-120, 2017
Optimal kernel choice for large-scale two-sample tests
A Gretton, D Sejdinovic, H Strathmann, S Balakrishnan, M Pontil, ...
Advances in neural information processing systems, 1205-1213, 2012
Learning generative models for protein fold families
S Balakrishnan, H Kamisetty, JG Carbonell, SI Lee, CJ Langmead
Proteins: Structure, Function, and Bioinformatics 79 (4), 1061-1078, 2011
Confidence sets for persistence diagrams
BT Fasy, F Lecci, A Rinaldo, L Wasserman, S Balakrishnan, A Singh
The Annals of Statistics 42 (6), 2301-2339, 2014
Stochastically transitive models for pairwise comparisons: Statistical and computational issues
N Shah, S Balakrishnan, A Guntuboyina, M Wainwright
International Conference on Machine Learning, 11-20, 2016
Estimation from pairwise comparisons: Sharp minimax bounds with topology dependence
NB Shah, S Balakrishnan, J Bradley, A Parekh, K Ramchandran, ...
The Journal of Machine Learning Research 17 (1), 2049-2095, 2016
Efficient active algorithms for hierarchical clustering
A Krishnamurthy, S Balakrishnan, M Xu, A Singh
arXiv preprint arXiv:1206.4672, 2012
Noise thresholds for spectral clustering
S Balakrishnan, M Xu, A Krishnamurthy, A Singh
Advances in Neural Information Processing Systems, 954-962, 2011
Minimax localization of structural information in large noisy matrices
M Kolar, S Balakrishnan, A Rinaldo, A Singh
Advances in Neural Information Processing Systems, 909-917, 2011
Local maxima in the likelihood of gaussian mixture models: Structural results and algorithmic consequences
C Jin, Y Zhang, S Balakrishnan, MJ Wainwright, MI Jordan
Advances in neural information processing systems, 4116-4124, 2016
Robust estimation via robust gradient estimation
A Prasad, AS Suggala, S Balakrishnan, P Ravikumar
arXiv preprint arXiv:1802.06485, 2018
Computationally efficient robust sparse estimation in high dimensions
S Balakrishnan, SS Du, J Li, A Singh
Conference on Learning Theory, 169-212, 2017
A permutation-based model for crowd labeling: Optimal estimation and robustness
NB Shah, S Balakrishnan, MJ Wainwright
arXiv preprint arXiv:1606.09632, 2016
Cluster trees on manifolds
S Balakrishnan, S Narayanan, A Rinaldo, A Singh, L Wasserman
Advances in Neural Information Processing Systems, 2679-2687, 2013
Statistical and computational tradeoffs in biclustering
S Balakrishnan, M Kolar, A Rinaldo, A Singh, L Wasserman
NIPS 2011 workshop on computational trade-offs in statistical learning 4, 2011
Alternative paths in HIV-1 targeted human signal transduction pathways
S Balakrishnan, O Tastan, J Carbonell, J Klein-Seetharaman
BMC genomics 10 (3), S30, 2009
Feeling the Bern: Adaptive estimators for Bernoulli probabilities of pairwise comparisons
NB Shah, S Balakrishnan, MJ Wainwright
IEEE Transactions on Information Theory, 2019
Some scaling laws for MOOC assessments
NB Shah, J Bradley, S Balakrishnan, A Parekh, K Ramchandran, ...
KDD Workshop on Data Mining for Educational Assessment and Feedback (ASSESS …, 2014
Sparse additive functional and kernel CCA
S Balakrishnan, K Puniyani, J Lafferty
arXiv preprint arXiv:1206.4669, 2012
Minimax rates for homology inference
S Balakrishnan, A Rinaldo, D Sheehy, A Singh, L Wasserman
Artificial Intelligence and Statistics, 64-72, 2012
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