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Events for April 28, 2015
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CS Colloquium: Ilias Diakonikolas (University of Edinburgh) - Algorithmic Approaches in Unsupervised Learning
Tue, Apr 28, 2015 @ 09:45 AM - 10:50 AM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Ilias Diakonikolas, University of Edinburgh
Talk Title: Algorithmic Approaches in Unsupervised Learning
Series: CS Colloquium
Abstract: The growing scale of modern data sets and our increasingly ambitious inferential goals have highlighted new algorithmic challenges. In this talk, I will discuss recent progress in this vein that lies at the interface of computer science and statistics. I will highlight how the algorithmic perspective brings novel insights and leads to computationally efficient methods for classical statistical problems.
In this talk, I will focus on a core problem in unsupervised learning: how to infer information about a distribution based on random samples. An important goal in this context is understanding the structure in the data without making strong assumptions on its form. I will describe a unified algorithmic framework that yields new, provably efficient estimators for several natural and well-studied statistical models, including mixtures of structured distribution families (e.g., gaussian, log-concave, etc.). This framework provides a fairly complete picture of the sample and computational complexities for fundamental inference tasks, including density estimation and hypothesis testing.
I will also briefly describe some of my other work on learning, including supervised learning with missing and noisy data, as well as connections between these questions and seemingly unrelated problems in game theory and complexity theory.
The event will be available to stream HERE
Biography: Ilias Diakonikolas is an Assistant Professor in the School of Informatics at the University of Edinburgh. He holds a diploma in electrical and computer engineering from the National Technical University of Athens, and a Ph.D. in computer science from Columbia University (2010) where he was advised by Mihalis Yannakakis. He received a best thesis award for his doctoral dissertation and an honorable mention in the 2009 George Nicholson competition from the INFORMS society. Before moving to Edinburgh he spent two years (2010-2012) as the Simons postdoctoral fellow in theoretical computer science at the University of California, Berkeley. Ilias has worked in several areas of algorithms, including optimization, computational learning, and computational economics. His research focus is on the algorithmic foundations of massive data sets, in particular on designing efficient algorithms for statistics and machine learning.
Host: Computer Science Department
Location: Olin Hall of Engineering (OHE) - 132
Audiences: Everyone Is Invited
Contact: Assistant to CS chair
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Epstein Institute / ISE 651 Seminar Series
Tue, Apr 28, 2015 @ 03:30 PM - 04:50 PM
Daniel J. Epstein Department of Industrial and Systems Engineering
Conferences, Lectures, & Seminars
Speaker: Uday V. Shanbhag, Associate Professor, Department of Industrial and Manufacturing Engineering (IME), Pennsylvania State University
Talk Title: On the Solution of Optimization and Variational Problems in Misspecified Regimes
Series: Epstein Institute Seminar Series
Abstract: We consider a class of optimization and variational problems that are misspecified in a parametric sense. Resolving this misspecification is assumed to require the solution of a distinct convex learning problem. Traditional sequential approaches that first solve the learning problem and then solve the correctly specified computational problem require that exact or accurate solutions are available in finite time. We consider an approach where both problems are solved simultaneously in optimization and variational regimes via standard first-order projected gradient, subgradient, and extra gradient methods. We provide global convergence results and rate analysis for the schemes where we quantify the degradation from learning. In the second part of the talk, we consider stochastic generalizations of the problem that require coupled stochastic approximation schemes. We will also mention related efforts to solve problems distributed stochastic optimization problems on time-varying graphs and misspecified MDPs. Finally, time permitting, we may discuss some ongoing research initiatives in the area of power systems and markets.
Biography: Since fall 2012, Uday V. Shanbhag has been an associate professor in the department of Industrial and Manufacturing Engineering (IME) at the Pennsylvania State University. Prior to arriving at Penn. State, from 2006-“2012, he was first an assistant professor, and subsequently a tenured associate professor, in the department of Industrial and Enterprise Systems engineering (ISE) at the University of Illinois at Urbana-Champaign. His research honors include the triennial A.W. Tucker Prize by the mathematical programming society (MPS) in 2006, the Computational Optimization and Applications (COAP) best paper award (with advisor Walter Murray) in 2007, and the best theoretical paper award in the Winter Simulation Conference (WSC) in 2013 (with Angelia Nedi'c and Farzad Yousefian). Additionally, he was a finalist for the Microsoft Faculty fellowship (2008) and was awarded the National Science Foundation (NSF) Faculty Early Career Development (CAREER) award in 2012 from the Operations Research program. Several of his doctoral students have been recognized by a range of honors including Uma Ravat (best student paper prize at the triennial International Conference on Stochastic Programming (2010)), Aswin Kannan (finalist for best student paper prize at the triennial International Conference on Stochastic Programming (2010)) and Huibing Yin (finalist for the best student paper prize at the IEEE Conference on Decision and Control (2009)). Uday V. Shanbhag has a Ph.D. from Stanford University's department of Management Science and Engineering (2006), with a concentration in operations research and was associated with the Systems Optimization Laboratory when at Stanford. He also holds masters and undergraduate degrees from the Massachusetts Institute of Technology (MIT), Cambridge (in Operations Research) and the Indian Institute of Technology (IIT), Bombay, respectively.
Host: Daniel J. Epstein Department of Industrial and Systems Engineering
More Information: Seminar-Shanbhag.docx
Location: Ethel Percy Andrus Gerontology Center (GER) - 206
Audiences: Everyone Is Invited
Contact: Georgia Lum
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Society of Women Engineers 8th General Meeting
Tue, Apr 28, 2015 @ 06:30 PM - 08:00 PM
Viterbi School of Engineering Student Organizations
Student Activity
Please check out the SWE USC facebook page for more event details!
Audiences: Everyone Is Invited
Contact: Society of Women Engineers Society of Women Engineers
