ARC Colloquium: Alina Ene (Boston University)

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Event Details
Contact

Dani Denton
denton at cc dot gatech dot edu

 

 

 

Summaries

Summary Sentence: Recent progress on minimizing decomposable submodular functions (Klaus 1116 E at 11am)

Full Summary: No summary paragraph submitted.

Video of this talk is available at: https://smartech.gatech.edu/handle/1853/55973

Full collection of talk videos are available at: https://smartech.gatech.edu/handle/1853/46836

Algorithms & Randomness Center (ARC)

Alina Ene - Boston University

Monday, October 17, 2016

Klaus 1116 East - 11am

Title:
From Minimum Cut to Submodular Minimization: Leveraging the Decomposable Structure

Abstract:
Submodular function minimization is a fundamental optimization problem that arises in several applications in machine learning and computer vision. The problem is known to be solvable in polynomial time, but general purpose algorithms have high running times and are unsuitable for large-scale problems. Recent work aims to obtain very practical algorithms for minimizing functions that are sums of "simple" functions. This class of functions provides an important bridge between functions with a rich combinatorial structure – notably, the cut function of a graph – and general submodular functions, and it brings along powerful combinatorial structure reminiscent of graphs as well as a fair bit of modeling power that greatly expands its applications. In this talk, we describe recent progress on designing very efficient algorithms for minimizing decomposable functions and understanding their combinatorial structure.

This talk is based on joint work with Huy Nguyen (Northeastern University) and Laszlo Vegh (London School of Economics).
 
Bio::
Alina Ene is an Assistant Professor in the Computer Science department at Boston University. Her research interests include the design and analysis of algorithms, the mathematical aspects of combinatorial optimization topics such as submodularity and graphs, and their applications to machine learning. Prior to joining BU, she was an Assistant Professor at the University of Warwick, a Faculty Fellow at the Alan Turing Institute for Data Science, and a postdoc in the Center for Computational Intractability at Princeton University. Alina obtained her PhD in Computer Science from the University of Illinois at Urbana-Champaign in 2013 under the supervision of Chandra Chekuri. She graduated with a BSE degree in Computer Science from Princeton University in 2008, with High Honors in Computer Science.

URL: http://cs-people.bu.edu/aene/

Seminar webpage

Fall 2016 ARC Seminar Schedule

Additional Information

In Campus Calendar
No
Groups

ARC, College of Computing, School of Computer Science

Invited Audience
Faculty/Staff, Public, Undergraduate students, Graduate students
Categories
Seminar/Lecture/Colloquium
Keywords
Algorithm and Randomness Center, ARC, Computational Complexity, Computational Learning Theory, Georgia Tech
Status
  • Created By: Dani Denton
  • Workflow Status: Published
  • Created On: Aug 17, 2016 - 2:07pm
  • Last Updated: Apr 13, 2017 - 5:15pm