The CORE Seminar is an interdepartmental talks series focused on optimization, machine learning, big data, statistics and numerics. This new cross campus activity aims to leverage the newly established critical mass of faculty and students in these areas at UW. Since 2014, CORE seminar has been funded by Pacific Institute of Mathematical Sciences (PIMS) and the UW Deans of Engineering and Arts and Sciences. In 2013-14, it was funded by the departments of Mathematics, Statistics, Electrical Engineering, and Computer Science Engineering, and the deans of Engineering and Arts and Sciences.

## Upcoming Talks

Zaid Harchaoui, *Department of Statistics, University of Washington
April 18, 2017, 4pm, Location: EEB 125
Catalyst, Generic Acceleration Scheme for Gradient-based Optimization
*

**Past Talks:**

Liza Levina, *Department of Statistics, University of Michigan
Interpretable Prediction Models for Network-Linked Data
April 11, 2017, 4pm, Location: EEB 125*

Jon Lee,* Department of Industrial and Operations Engineering, University of Michigan
Mixed-Integer Nonlinear Optimization: Let’s get crazy!
January 31, 2016, 4pm, Location: LOW 105*

David Shmoys, *Department of Computer Science, Cornell University
Models and Algorithms for the Operation and Design of Bike-Sharing Systems
*

*December 1, 2016, 11am, Location: CSE 403*

Nina Balcan, *Carnegie Mellon University
Distributed Machine Learning*

*May 31, 2016, 4 pm, Location: EEB 125*

Sébastien Bubeck,* Microsoft Research
New Results at the Crossroads of Convexity, Learning and Information Theory*

*April 19, 2016, 4 pm, Location: LOW 102*

Katya Scheinberg, *Lehigh University*

* Using randomized models in black-box, derivative free and stochastic optimization*

*March 8 , 2016, 4 pm, Location: SMI 304*

Pedro Domingos, *Department of Computer Science and Engineering, University of Washington*

* Recursive Decomposition for Nonconvex Optimization/em>*

*November 24 , 2015, Location: Gowen Hall, Room 201*

Michael Overton, *Courant Institute of Mathematical Sciences, New York University*

*Nonsmooth, Nonconvex Optimization: Algorithms and Examples*

*October 13, 2015, Location: Raitt Hall (RAI), Room 121*

Jonathan Kelner, *Department of Mathematics, MIT*

Bridging the Numerical and the Combinatorial: Emerging Tools, Techniques, and Design Principles for Graph Algorithms

*May 19, 2015, EEB 125*

Joel Tropp, *Department of Computing and Mathematical Sciences, Caltech*

Applied Random Matrix Theory

*April 28, 2015*

Andrew Fitzgibbon, *Microsoft Research, Cambridge*

Learning about Shape

*March 30, 2015*

Jeannette Wing, *Corporate Vice President of Microsoft Research*

Computational Thinking

*February 27, 2015*

Math Across Campus Seminar

*Jon Kleinberg, Departments of Computer Science and Information Science, Cornell*

Incentives for Collective Behavior: Badges, Procrastination, and Long-Range Goals

*January 15, 2015*

*CSE Distinguished Lecture Series, Data Science Seminar*

*James Renegar, School of Operations Research and Information Engineering, Cornell*

Extending the Applicability of Efficient First-Order Methods for Convex Optimization

*January 13, 2015*

Peter Bürgisser, *Institute for Mathematics, TU Berlin*

Condition of Convex Optimization and Spherical Intrinsic Volumes

*Dec 2, 2014*

**Past Talks 2013-2014:**

Dan Spielman, *Department of Computer Science, Yale University*

Spectral Sparsification of Graphs

*May 8, 2014*

Math Across Campus Seminar

Sanjeev Arora, *Department of Computer Science, Princeton University*

Overcoming Intractability in Unsupervised Learning

*April 15, 2014*

David Blei, *Department of Computer Science, Princeton University*

Probabilistic Topic Models of Text and Users

*March 31, 2014*

Maryam Fazel, *Department of Electrical Engineering, University of Washington*

Filling In the Gaps: Recovery from Incomplete Information

*February 21, 2014*

Math Across Campus Seminar

Pablo Parrilo, *Department of Electrical Engineering and Computer Science, MIT*

Flows and Decompositions of Games; Harmonic and Potential Games

*December 2, 2013*

Stephen P. Boyd, *Department of Electrical Engineering, Stanford University*

Convex Optimization: From Embedded Real-Time to Large-Scale Distributed

*October 29, 2013*