Publications (28)
Estimating Networks With Jumps
Mladen Kolar, Eric P. Xing
Mean and variance estimation in high-dimensional heteroscedastic models with non-convex penalties
James Sharpnack, Mladen Kolar
Sparsistent Estimation of Time-Varying Discrete Markov Random Fields
Mladen Kolar, Eric P. Xing
Partially Linear Additive Gaussian Graphical Models
Sinong Geng, Minhao Yan, Mladen Kolar +1
Sketching Meets Random Projection in the Dual: A Provable Recovery Algorithm for Big and High-dimensional Data
Jialei Wang, Jason D. Lee, Mehrdad Mahdavi +2
Variance function estimation in high-dimensions
Mladen Kolar, James Sharpnack
Optimal Feature Selection in High-Dimensional Discriminant Analysis
Mladen Kolar, Han Liu
ROCKET: Robust Confidence Intervals via Kendall's Tau for Transelliptical Graphical Models
Rina Foygel Barber, Mladen Kolar
Ultra-high Dimensional Multiple Output Learning With Simultaneous Orthogonal Matching Pursuit: A Sure Screening Approach
Mladen Kolar, Eric P. Xing
Provable Gaussian Embedding with One Observation
Ming Yu, Zhuoran Yang, Tuo Zhao +2
Graph Estimation From Multi-attribute Data
Mladen Kolar, Han Liu, Eric P. Xing
Estimating time-varying networks
Mladen Kolar, Le Song, Amr Ahmed +1
Joint Nonparametric Precision Matrix Estimation with Confounding
Sinong Geng, Mladen Kolar, Oluwasanmi Koyejo
Learning Influence-Receptivity Network Structure with Guarantee
Ming Yu, Varun Gupta, Mladen Kolar
Inference for Sparse Conditional Precision Matrices
Jialei Wang, Mladen Kolar
Efficient Distributed Learning with Sparsity
Jialei Wang, Mladen Kolar, Nathan Srebro +1
Union Support Recovery in Multi-task Learning
Mladen Kolar, John Lafferty, Larry Wasserman
A General Framework for Robust Testing and Confidence Regions in High-Dimensional Quantile Regression
Tianqi Zhao, Mladen Kolar, Han Liu
Post-Regularization Inference for Time-Varying Nonparanormal Graphical Models
Junwei Lu, Mladen Kolar, Han Liu
Distributed Multitask Learning
Jialei Wang, Mladen Kolar, Nathan Srebro
Distributed Multi-Task Learning with Shared Representation
Jialei Wang, Mladen Kolar, Nathan Srebro
Distributed Stochastic Multi-Task Learning with Graph Regularization
Weiran Wang, Jialei Wang, Mladen Kolar +1
Estimating Undirected Graphs Under Weak Assumptions
Larry Wasserman, Mladen Kolar, Alessandro Rinaldo
Scalable Peaceman-Rachford Splitting Method with Proximal Terms
Sen Na, Mingyuan Ma, Mladen Kolar
Uniform Inference for High-dimensional Quantile Regression: Linear Functionals and Regression Rank Scores
Jelena Bradic, Mladen Kolar
Recovering Block-structured Activations Using Compressive Measurements
Sivaraman Balakrishnan, Mladen Kolar, Alessandro Rinaldo +1
Recovery of simultaneous low rank and two-way sparse coefficient matrices, a nonconvex approach
Ming Yu, Varun Gupta, Mladen Kolar
Kernel Meets Sieve: Post-Regularization Confidence Bands for Sparse Additive Model
Junwei Lu, Mladen Kolar, Han Liu