Seminars and Events

Machine Learning Seminar Series

Spring 2022: Wednesdays at 11:30

Wednesday, Jun. 1, 2022 in TTIC 530: Chenhao Tan, University of Chicago

Towards Human-Centered Explanations of AI Predictions


Wednesday, Apr. 27, 2022 in TTIC 530: Yuexi Wang, University of Chicago

Approximate Bayesian Computation via Classification


 Wednesday, Apr. 20, 2022 in TTIC 530: Rad Niazadeh, University of Chicago

Optimal Algorithms for Continuous Non-Monotone Submodular Maximization : Theory and Applications

Fall 2021: Wednesdays at 10:30

Wednesday, Dec. 01, 2021 in TTIC 530: Mladen Kolar, University of Chicago

Estimation Differential Networks from Functional Data


Wednesday, Nov. 17, 2021 in TTIC 530: Omar Montasser,TTIC

Transductive Robust Learning Guarantees 


Wednesday, Nov. 10, 2021 in TTIC 530: Frederic Koehler, UC Berkeley

Learning Ising Models with Latent Variables


Wednesday, Nov. 3, 2021 in TTIC 530: Zhimei Ren, University of Chicago

Policy Learning with Adaptively Collected Data


Wednesday, Oct. 20, 2021 in TTIC 530: Cong Ma, University of Chicago

Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism

Spring 2020: Fridays at 10:30

Friday, Apr. 3, 2020: No talk

Friday, Apr. 10, 2020: No talk

Friday, Apr. 17, 2020: Pritish Kamath, TTIC

Friday, Apr. 24, 2020: Dimitris Papailiopoulos, UW-Madison

Friday, May 1, 2020: Shirley Wu, UT-Austin

Friday, May 8, 2020: Vaishaal Shankar, UC-Berkeley

Friday, May 15, 2020: No talk

Friday, May 22, 2020: Cyrus Rashtchian, UCSD

Friday, May 29, 2020: Laurent Lessard, UW-Madison

Friday, Jun. 5, 2020: Yuanzhi Li, CMU


Winter 2020: Fridays at 10:30

Friday, Jan. 10, 2020 in TTIC 526: Mina Karzand, UW-Madison

Focused Learning in Tree-Structured Graphical Models


Friday, Jan. 17, 2020 in Crerar 390: Rina Foygel Barber, University of Chicago

Predictive inference with the jackknife+


Friday, Jan. 24, 2020 in TTIC 526: Steve Hanneke, TTIC

Learning Whenever Learning is Possible: Universal Learning under General Stochastic Processes


Friday, Jan. 31, 2020 in Crerar 390: Tengyu Ma, Stanford

Designing Explicit Regularizers for Deep Models


Friday, Feb. 7, 2020 in TTIC 526: Yixin Wang, Columbia

The Blessings of Multiple Causes


Friday, Feb. 14, 2020 in Crerar 390: Bryon Aragam, University of Chicago, Booth

A general framework for learning DAGs with NO TEARS

Friday, Feb. 21, 2020 in TTIC 526: TTIC Student Workshop

Friday, Feb. 28, 2020 in TTIC 526: Xiang Cheng, Berkeley

Sampling as Optimization and Optimization as Sampling


Friday, Mar. 6, 2020: No talk

Friday, Mar. 13, 2020 in Crerar 390: Samory Kpotufe, Columbia

Some Recent Insights on Transfer Learning

Friday, Mar. 20, 2020 in TTIC 526: Filip Hanzely, KAUST



Fall 2019: Fridays at 10:30

SPECIAL TIME: Wednesday, Oct. 2, 2019 at 1:30pm in TTIC room 526: Arthur Szlam, Facebook Research

Language and Interaction in Minecraft


Friday, Oct. 11, 2019 in TTIC room 526: Peter Bartlett, UC-Berkeley

Optimizing probability distributions for machine learning: sampling meets optimization


Friday, Oct. 18, 2019 in Crerar room 390: Madeleine Udell, Cornell

Big data is low rank


Friday, Oct. 25, 2019 in TTIC room 526: Shay Moran, Technion

Convex Set Disjointness, Distributed Learning of Halfspaces, and LP Feasibility

Friday, Nov. 1, 2019 in Crerar room 390: Ohad Shamir, Weizmann

Training Neural Networks: The Bigger the Better?

Special Talk: Distinguished Lecture at TTIC, Friday, Nov. 8, 2019 in TTIC room 526: Shafi Goldwasser, MIT

Friday, Nov. 15, 2019 in Crerar 390: Greg Ongie, University of Chicago; and Blake Woodworth, TTIC

Greg Ongie: A function space view of overparameterized neural networks

Blake Woodworth: The complexity of finding stationary points in convex and non-convex optimization


Friday, Nov. 22, 2019 in TTIC 526: Ramya Vinayak, University of Washington

Learning from Sparse Data


Friday, Nov. 29, 2019: Thanksgiving break

Friday, Dec. 6, 2019 in TTIC 526: Zhaoran Wang, Northwestern

On the Computational and Statistical Efficiency of Policy Optimization in (Deep) Reinforcement Learning

Friday, Dec. 13, 2019: NeurIPS




Academic year 2018-2019

Wednesdays, 1-2pm in the Harper Center (Booth) Room 219 Pizza provided by UChicago CS Department

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April 3, 2019 in Crerar room 390: Lorenzo Orecchia, Boston University

First-Order Methods Unleashed: Scalable Optimization in the Age of Big Data


April 10, 2019 in room C25: Mesrob Ohannessian, TTIC 

From Fair Decisions to Social Benefit


April 17, 2019 in room C04: Lin Yang, Princeton University

Learn Policy Optimally via Efficiently Utilizing Data


April 24, 2019: Avrim Blum, TTIC

Algorithmic fairness in online decision-making


April 29, 2019: (2:30pm in Crerar 390) Tong Zhang, Hong Kong University of Science and Technology.

Modern Techniques of Statistical Optimization for Machine Learning


May 1, 2019: Tengyuan Liang, University of Chicago Booth

New Thoughts on Adaptivity, Generalization and Interpolation Motivated from Neural Networks


May 8, 2019: Rosemary Braun, Northwestern University

Using Gene Expression to Tell Time


May 15, 2019: Yali Amit, UChicago Statistics

Optimization of latent variables in deep network applications


May 22, 2019: UChicago Geometric Data Analysis Workshop

May 29, 2019 in SHFE 203 (Saieh Hall For Economics): Dan McDonald

Trend filtering in exponential families



Past Quarters:

Jan. 16, 2019: Sumeet Katariya, UW-Madison

Adaptive Sampling for Ranking and Clustering

Jan. 23, 2019: Karl Stratos, TTIC

Challenges and Hopes of Unsupervised Learning by Mutual Information Maximization

Feb. 6, 2019: Chao Gao, University of Chicago Statistics

Convergence Rates of Variational Posterior Distributions

Feb. 13, 2019: Veronika Rockova, Univeristy of Chicago, Booth 

On Theory for BART

Feb. 20, 2019: Ruey Tsay, University of Chicago, Booth 

Analysis of Big Dependent Data

Feb. 27, 2019: No Seminar


March 5, 2019 (TUESDAY), Harper Center 3B from 12:10 to 1:10 p.m.: Jorge Nocedal, Northwestern University

Zero-Order Methods for the Optimization of Noisy Functions


March 6, 2019: Bryan Pardo, Northwestern University 

Audio source separation models that learn without ground truth and are open to user correction


March 13, 2019: Sebastian Stitch, EPFL

Error Feedback for Communication Efficient SGD


March 20, 2019: Spring Break, No Seminar

March 27, 2019: Spring Break, No Seminar

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