Nonconvex Information Processing for Heterogeneous and Distributed Data
Abstract
The objective of this research program is to develop a comprehensive framework for nonconvex information processing with large-scale heterogeneous and distributed data. We aim to design efficient, robust and provably accurate algorithms for information processing using their natural nonconvex formulations without resorting to expensive convex relaxations. We will pursue a deeper understanding of geometric properties of nonconvex loss surfaces and optimization trajectories, with the emphasis on more realistic data models that can be heterogeneous and distributed. Novel combinations of insights and techniques from statistical signal processing, mathematical optimization, information theory, and high-dimensional statistics will be developed throughout the proposed research program to meet the research objectives
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 28, 2021
- Accession Number
- AD1197155
Entities
People
- Yuxin Chen
Organizations
- Princeton University