411 citations · 3k across the 39 of their papers we have counts for
6 papers · 1 filter
Truncated Power Method for Sparse Eigenvalue Problems
Xiao-Tong Yuan, Tong Zhang
This paper considers the sparse eigenvalue problem, which is to extract dominant (largest) sparse eigenvectors with at most non-zero components. We propose a simple yet effecti…
A tail inequality for quadratic forms of subgaussian random vectors
Daniel Hsu, Sham M. Kakade, Tong Zhang
We prove an exponential probability tail inequality for positive semidefinite quadratic forms in a subgaussian random vector. The bound is analogous to one that holds when the vect…
A General Theory of Concave Regularization for High Dimensional Sparse Estimation Problems
Cun-Hui Zhang, Tong Zhang
Concave regularization methods provide natural procedures for sparse recovery. However, they are difficult to analyze in the high dimensional setting. Only recently a few sparse re…
Spectral Methods for Learning Multivariate Latent Tree Structure
Animashree Anandkumar, Kamalika Chaudhuri, Daniel Hsu +3
This work considers the problem of learning the structure of multivariate linear tree models, which include a variety of directed tree graphical models with continuous, discrete, a…
Efficient Optimal Learning for Contextual Bandits
Miroslav Dudik, Daniel Hsu, Satyen Kale +4
We address the problem of learning in an online setting where the learner repeatedly observes features, selects among a set of actions, and receives reward for the action taken. We…
Dimension-free tail inequalities for sums of random matrices
Daniel Hsu, Sham M. Kakade, Tong Zhang
We derive exponential tail inequalities for sums of random matrices with no dependence on the explicit matrix dimensions. These are similar to the matrix versions of the Chernoff b…