171 citations · 624 across the 37 of their papers we have counts for
11 papers · 1 filter
Convergence guarantee for the sparse monotone single index model
Ran Dai, Hyebin Song, Rina Foygel Barber +1
We consider a high-dimensional monotone single index model (hdSIM), which is a semiparametric extension of a high-dimensional generalize linear model (hdGLM), where the link functi…
A Sharp Blockwise Tensor Perturbation Bound for Orthogonal Iteration
Yuetian Luo, Garvesh Raskutti, Ming Yuan +1
In this paper, we develop novel perturbation bounds for the high-order orthogonal iteration (HOOI) [DLDMV00b]. Under mild regularity conditions, we establish blockwise tensor pertu…
The bias of isotonic regression
Ran Dai, Hyebin Song, Rina Foygel Barber +1
We study the bias of the isotonic regression estimator. While there is extensive work characterizing the mean squared error of the isotonic regression estimator, relatively little…
Testing for high-dimensional network parameters in auto-regressive models
Lili Zheng, Garvesh Raskutti
High-dimensional auto-regressive models provide a natural way to model influence between actors given multi-variate time series data for time intervals. While there has bee…
Minimax optimal convex methods for Poisson inverse problems under -ball sparsity
Yuan Li, Garvesh Raskutti
In this paper, we study the minimax rates and provide an implementable convex algorithm for Poisson inverse problems under weak sparsity and physical constraints. In particular we…
Convex Regularization for High-Dimensional Multi-Response Tensor Regression
Garvesh Raskutti, Ming Yuan, Han Chen
In this paper we present a general convex optimization approach for solving high-dimensional multiple response tensor regression problems under low-dimensional structural assumptio…