4 papers
Matrix Completion from General Deterministic Sampling Patterns
Hanbyul Lee, Rahul Mazumder, Qifan Song +1
Most of the existing works on provable guarantees for low-rank matrix completion algorithms rely on some unrealistic assumptions such that matrix entries are sampled randomly or th…
Support Recovery in Sparse PCA with Non-Random Missing Data
Hanbyul Lee, Qifan Song, Jean Honorio
We analyze a practical algorithm for sparse PCA on incomplete and noisy data under a general non-random sampling scheme. The algorithm is based on a semidefinite relaxation of the…
Support Recovery in Sparse PCA with Incomplete Data
Hanbyul Lee, Qifan Song, Jean Honorio
We study a practical algorithm for sparse principal component analysis (PCA) of incomplete and noisy data. Our algorithm is based on the semidefinite program (SDP) relaxation of th…
On the Fundamental Limits of Exact Inference in Structured Prediction
Hanbyul Lee, Kevin Bello, Jean Honorio
Inference is a main task in structured prediction and it is naturally modeled with a graph. In the context of Markov random fields, noisy observations corresponding to nodes and ed…