1.3k citations · 3.8k across the 222 of their papers we have counts for
6 papers · 2 filters
Lower Bounds on Active Learning for Graphical Model Selection
Jonathan Scarlett, Volkan Cevher
We consider the problem of estimating the underlying graph associated with a Markov random field, with the added twist that the decoding algorithm can iteratively choose which subs…
Convex block-sparse linear regression with expanders -- provably
Anastasios Kyrillidis, Bubacarr Bah, Rouzbeh Hasheminezhad +3
Sparse matrices are favorable objects in machine learning and optimization. When such matrices are used, in place of dense ones, the overall complexity requirements in optimization…
On the Difficulty of Selecting Ising Models with Approximate Recovery
Jonathan Scarlett, Volkan Cevher
In this paper, we consider the problem of estimating the underlying graph associated with an Ising model given a number of independent and identically distributed samples. We adopt…
Partial Recovery Bounds for the Sparse Stochastic Block Model
Jonathan Scarlett, Volkan Cevher
In this paper, we study the information-theoretic limits of community detection in the symmetric two-community stochastic block model, with intra-community and inter-community edge…
Converse Bounds for Noisy Group Testing with Arbitrary Measurement Matrices
Jonathan Scarlett, Volkan Cevher
We consider the group testing problem, in which one seeks to identify a subset of defective items within a larger set of items based on a number of noisy tests. While matching achi…
Learning Data Triage: Linear Decoding Works for Compressive MRI
Yen-Huan Li, Volkan Cevher
The standard approach to compressive sampling considers recovering an unknown deterministic signal with certain known structure, and designing the sub-sampling pattern and recovery…