Subdeterminant Maximization via Nonconvex Relaxations and Anti-concentration

Channel:
United States Simons Institute for the Theory of Computing
Subscribers:
68,700
Published on ● Video Link: https://www.youtube.com/watch?v=eOpZUN-u60s


Duration: 34:27
405 views
3

Nisheeth Vishnoi, École Polytechnique Fédérale de Lausanne
https://simons.berkeley.edu/talks/subdeterminant-maximization-nonconvex-relaxations-and-anti-concentration
Discrete Optimization via Continuous Relaxation



Other Videos By Simons Institute for the Theory of Computing


2017-10-03The State of Contemporary Computing Substrates for Optimization Methods
2017-10-02On the Optimization Landscape of Matrix and Tensor Decomposition Problems
2017-10-02Chordal Graphs and Sparse Semidefinite Optimization
2017-10-02Michael Cohen and ell_p Regression
2017-10-02Slime Molds and Sparse Recovery
2017-10-02Width-independent Iterative Algorithms for Packing and Covering Programs
2017-10-02Continuous Methods for Discrete Optimization: From Convex Relaxations, to Iterative Schemes...
2017-09-19Across the Watershed: Unifying Perspectives on Optimization
2017-09-15Local Guarantees in Graph Cuts and Clustering
2017-09-15Approximating the Permanent of Positive Semidefinite Matrices
2017-09-15Subdeterminant Maximization via Nonconvex Relaxations and Anti-concentration
2017-09-15A Survey of Dependent Rounding
2017-09-15Finding Best LP Relaxations for Various Cut Problems
2017-09-14LP Relaxations for Reordering Buffer Management
2017-09-14A (1+epsilon)-approximation for Makespan Scheduling with Precedence Constraints Using LP Hierarchies
2017-09-14Scheduling on Related Machines
2017-09-14Low Diameter Graph Decompositions and Approximating Unique Games
2017-09-14Algorithms for Stable and Perturbation-resilient Problems
2017-09-14Beyond Worst Case Analysis in Approximation
2017-09-13The Non-Uniform k-Center Problem
2017-09-13Online Optimization, Smoothing, and Competitive Ratio


Tags:
Nisheeth Vishnoi
Simons Institute
Theory of Computing
Theory of Computation
Theoretical Computer Science
Computer Science
UC Berkeley
Discrete Optimization via Continuous Relaxation