1.9k citations
- University of ChicagoUS60 papers
- Microsoft (United States)US23 papers
- Carnegie Mellon UniversityUS20 papers
- Massachusetts Institute of TechnologyUS18 papers
- Google (United States)US16 papers
- Technion – Israel Institute of TechnologyIL16 papers
- University of California, BerkeleyUS16 papers
- Princeton UniversityUS12 papers
- The University of Texas at AustinUS12 papers
- Toyota Technological InstituteJP10 papers
- University of TorontoCA10 papers
- University of WashingtonUS10 papers
4 papers · 2 filters
Provable Burer-Monteiro factorization for a class of norm-constrained matrix problems
Dohyung Park, Anastasios Kyrillidis, Srinadh Bhojanapalli +2
We study the projected gradient descent method on low-rank matrix problems with a strongly convex objective. We use the Burer-Monteiro factorization approach to implicitly enforce…
Global Optimality of Local Search for Low Rank Matrix Recovery
Srinadh Bhojanapalli, Behnam Neyshabur, Nathan Srebro
We show that there are no spurious local minima in the non-convex factorized parametrization of low-rank matrix recovery from incoherent linear measurements. With noisy measurement…
Efficient Distributed Learning with Sparsity
Jialei Wang, Mladen Kolar, Nathan Srebro +1
We propose a novel, efficient approach for distributed sparse learning in high-dimensions, where observations are randomly partitioned across machines. Computationally, at each rou…
Network Inference by Learned Node-Specific Degree Prior
Qingming Tang, Lifu Tu, Weiran Wang +1
We propose a novel method for network inference from partially observed edges using a node-specific degree prior. The degree prior is derived from observed edges in the network to…