226 citations · 1.9k across the 128 of their papers we have counts for
16 papers · 1 filter
Tight Generalization Bounds for Noiseless Inverse Optimization
Pouria Fatemi, Hoomaan Maskan, Suvrit Sra +1
Inverse optimization (IO) seeks to infer the parameters of a decision-maker's objective from observed context--action data. We study noiseless IO, where demonstrations are generate…
Unsupervised robust nonparametric learning of hidden community properties
Mikhail A. Langovoy, Akhilesh Gotmare, Martin Jaggi
We consider learning of fundamental properties of communities in large noisy networks, in the prototypical situation where the nodes or users are split into two classes according t…
An Alternative to EM for Gaussian Mixture Models: Batch and Stochastic Riemannian Optimization
Reshad Hosseini, Suvrit Sra
We consider maximum likelihood estimation for Gaussian Mixture Models (Gmms). This task is almost invariably solved (in theory and practice) via the Expectation Maximization (EM) a…
Polynomial Time Algorithms for Dual Volume Sampling
Chengtao Li, Stefanie Jegelka, Suvrit Sra
We study dual volume sampling, a method for selecting k columns from an n x m short and wide matrix (n <= k <= m) such that the probability of selection is proportional to the volu…
Fast Mixing Markov Chains for Strongly Rayleigh Measures, DPPs, and Constrained Sampling
Chengtao Li, Stefanie Jegelka, Suvrit Sra
We study probability measures induced by set functions with constraints. Such measures arise in a variety of real-world settings, where prior knowledge, resource limitations, or ot…
Geometric Mean Metric Learning
Pourya Habib Zadeh, Reshad Hosseini, Suvrit Sra
We revisit the task of learning a Euclidean metric from data. We approach this problem from first principles and formulate it as a surprisingly simple optimization problem. Indeed,…