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All publications by Larry Wasserman
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Subsampling Methods for Persistent Homology
Frederic Chazal, Brittany Fasy, Fabrizio Lecci, Bertrand Michel, Alessandro Rinaldo and Larry Wasserman
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Optimal Ridge Detection using Coverage Risk
Yen-chi Chen, Christopher R. Genovese, Shirley Ho and Larry Wasserman
Advances in Neural Information Processing Systems 28, 2015


Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations
Kirthevasan Kandasamy, Akshay Krishnamurthy, Barnabas Poczos, Larry Wasserman and James M. Robins
Advances in Neural Information Processing Systems 28, 2015


Nonparametric Estimation of Renyi Divergence and Friends
Akshay Krishnamurthy, Kirthevasan Kandasamy, Barnabas Poczos and Larry Wasserman
Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014


Cluster Trees on Manifolds
Sivaraman Balakrishnan, Srivatsan Narayanan, Alessandro Rinaldo, Aarti Singh and Larry Wasserman
Advances in Neural Information Processing Systems 26, 2013


Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation
Martin Azizyan, Aarti Singh and Larry Wasserman
Advances in Neural Information Processing Systems 26, 2013


Exponential Concentration for Mutual Information Estimation with Application to Forests
Han Liu, Larry Wasserman and John D. Lafferty
Advances in Neural Information Processing Systems 25, 2012


The Nonparanormal SKEPTIC
Han Liu, Fang Han, Ming Yuan, Larry Wasserman and John D. Lafferty
Proceedings of the 29th International Conference on Machine Learning (ICML-12), 2012


Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models
Han Liu, Kathryn Roeder and Larry Wasserman
Advances in Neural Information Processing Systems 23, 2010


Graph-Valued Regression
Han Liu, Xi Chen, Larry Wasserman and John D. Lafferty
Advances in Neural Information Processing Systems 23, 2010


Nonparametric regression and classification with joint sparsity constraints
Han Liu, Larry Wasserman and John D. Lafferty
Advances in Neural Information Processing Systems 21, 2008


SpAM: Sparse Additive Models
Han Liu, Larry Wasserman, John D. Lafferty and Pradeep K. Ravikumar
Advances in Neural Information Processing Systems 20, 2007


Statistical Analysis of Semi-Supervised Regression
Larry Wasserman and John D. Lafferty
Advances in Neural Information Processing Systems 20, 2007


Compressed Regression
Shuheng Zhou, Larry Wasserman and John D. Lafferty
Advances in Neural Information Processing Systems 20, 2007


Rodeo: Sparse Nonparametric Regression in High Dimensions
Larry Wasserman and John D. Lafferty
Advances in Neural Information Processing Systems 18, 2005