Foundations of Data Science Seminars

Foundations of Data Science Seminars is a series of lectures on a variety of Machine Learning topics. Invited speakers for the series are leaders in their fields, hailing from respected research institutions worldwide. The ML Seminar Series is supported by the UT Austin Foundations of Data Science, an NSF Tripods Institute, and is administrated by WNCG. The series is curated for 2019-2020 by Prof. Aryan Mokhtari.

FDS Seminars was previously known as ML Seminars by UT Austin Foundations of Data Science.


20 Nov 2020	Virtual Seminar: Representation and Learning in Graph Neural Networks Stefanie Jegelka
30 Oct 2020	Virtual Seminar: Secure Frameworks for Outsourced Neural Network Inference Zahra Ghodsi
23 Oct 2020	Virtual Seminar: Finite Sample Convergence Bounds of Off-Policy Reinforcement Learning Algorithms Siva Theja Maguluri
16 Oct 2020	Virtual Seminar: The Role of Regularization in Overparameterized Neural Networks Rayadurgam Srikant
09 Oct 2020	Virtual Seminar: Reinforcement Learning using Generative Models for Continuous State and Action Space Systems Rahul Jain
02 Oct 2020	Virtual Seminar: Optimization algorithms for heterogeneous clients in Federated Learning Satyen Kale
25 Sep 2020	Virtual Seminar: On Heterogeneity in Federated Settings Virginia Smith
18 Sep 2020	Virtual Seminar: On the Convergence of Gradient Descent for Wide Two-Layer Neural Networks Francis Bach
11 Sep 2020	Virtual Seminar: Two Facets of Learning Robust Models: Fundamental Limits and Generalization to Natural Out-of-Distribution Inputs Hamed Hassani
15 May 2020	Virtual Seminar - Constant Regret Algorithms for Online Decision-Making Siddhartha Banerjee
08 May 2020	Virtual Seminar - Robust Distributed Training! But at What Cost? Prof. Dimitris Papailiopoulos
07 May 2020	Virtual Seminar - Modeling Uncertainty in Learning with Little Data Prof. Richard Zemel
06 Mar 2020	ML Seminar: Speeding up Distributed SGD via Communication-Efficient Model Aggregation Prof. Gauri Joshi
21 Feb 2020	ML Seminar: Toward the Jet Age of Machine Learning Prof. Ameet Talwalkar
03 Feb 2020	ML Seminar: Robust Reinforcement Learning with Langevin Dynamics Prof. Volkan Cevher
31 Jan 2020	ML Seminar: Distributed Stochastic Approximation: Reinforcement Learning and Optimization with Communication Constraints Prof. Justin Romberg
06 Dec 2019	ML Seminar: User Friendly Submodular Maximization Prof. Amin Karbasi
08 Nov 2019	ML Seminar: ReLU nets are powerful memorizers: a tight analysis of finite sample expressive power Suvrit Sra
03 May 2019	ML Seminar: Towards demystifying over-parameterization and early stopping in deep learning Prof. Mahdi Soltanolkotabi
05 Apr 2019	ML Seminar: Ant Navigation and When to Follow GPS Directions Prof. Steve Alpern
29 Mar 2019	ML Seminar: Hashing Algorithms for Extreme Scale Machine Learning Prof. Anshumali Shrivastava
15 Mar 2019	ML Seminar: Stein Variational Gradient Descent: Algorithm, Theory, Applications Prof. Qiang Liu
22 Feb 2019	ML Seminar: Uncertainty quantification and active sampling for low-rank matrices Prof. Yao Xie
01 Feb 2019	ML Seminar: Geometry and Regularization in Nonconvex Low-Rank Estimation Yuejie Chi
25 Jan 2019	ML Seminar: Statistical State Compression and Primal-Dual Pi Learning Mengdi Wang

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Foundations of Data Science Seminars