Recorded Talks Filter by - Any -Computational Complexity of Statistical Interference Boot CampFoundational Research SeminarIFML + DMS Joint EventIFML Diffusion Seminar SeriesIFML SeminarJoint IFML/CCSI SymposiumMLL Public LecturePublic LecturetinyML TalksUse-Inspired Research SeminarEthics/Fairness in AI SeminarWorkshopML+ X SeminarDistinguished Speaker SeminarPrivacy in AI Seminar IFML Seminar: 08/28/26 - Fast and Robust Diffusion Posterior Sampling for MR Image Reconstruction Using Preconditioned Langevin Sampling Moritz Blumenthal, postdoctoral researcher, Graz University of Technology and Boston Children’s Hospital IFML Seminar: 04/17/26 - Learning and guidance approaches for generative and physics-driven models in computational MRI Mehmet Akçakaya, Jim and Sara Anderson Chair Professor of Electrical Engineering, University of Minnesota IFML Seminar: 04/10/26 - High-Magnetization Sampling at Low Temperatures: Ising Models and Bayesian Sparse Linear Regression Kevin Tian, assistant professor of Computer Science, UT Austin IFML Seminar: 04/03/26 - Learning Mixture Models via Efficient High-dimensional Sparse Fourier Transforms Manolis Zampetakis, Assistant Professor of Computer Science, Yale University IFML Seminar: 03/13/26 - Foundations of Reliable Learning with Imperfect Data Arsen Vasilyan, postdoctoral fellow at the Institute for Foundations of Machine Learning (IFML) IFML Seminar: 02/27/26 - A survey of the mixing times of the Proximal Sampler algorithm Andre Wibisono, assistant professor in the Dept. of Computer Science, Yale University IFML Seminar: 02/13/26 - COWS and Their Hybrids: Customized Orthogonal Weights Larry Wasserman, University UPMC Professor of Statistics and Data Science, Carnegie Mellon University IFML Seminar: 02/06/26 - Are Diffusion and Autoregression Truly Different? Insights from Masked Diffusion Models Jiaxin Shi, former research scientist at Google DeepMind IFML Seminar: 11/21/25 - Learning Dynamics in Multiplayer Games Tatjana Chavdarova, visiting professor in the Department of Electronics, Information, and Bioengineering (DEIB), Politecnico di Milano (PoliMi) IFML Seminar: 11/14/25 - Faster Diffusion Language Models Sujay Sanghavi, Bettie Margaret Smith Professor, Chandra Family Department of Electrical and Computer Engineering, UT Austin IFML Seminar: 11/07/25 - Model Self-improvement via Optimal Retraining Adel Javanmard, Professor of Data Sciences and Operation, USC Marshall School of Business IFML Seminar: 10/24/25 - Learning from Many Trajectories Stephen Tu, Assistant Professor, Department of Electrical & Computer Engineering, University of Southern California IFML Seminar: 10/17/25 - Sample-Efficient Personalized Reward Models for Pluralistic Alignment Ramya Korlakai Vinayak, assistant professor, Dept. of ECE and affiliated faculty in the Dept. of Computer Science and Dept. of Statistics, UW-Madison IFML Seminar: 10/10/25 - Skill Learning from Video Kristen Grauman, Professor, Computer Science, UT Austin IFML Seminar: 10/03/25 - Successor Measures and Self-supervised Reinforcement Learning Amy Zhang, Assistant Professor, Electrical & Computer Engineering, UT Austin IFML Seminar: 09/19/25 - Speech Generation and Sound Understanding in the Era of Large Language Models David Harwath, Assistant Professor, Computer Science, UT Austin IFML Seminar: 09/12/25 - Accelerating Nonconvex Optimization via Online Learning Aryan Mokhtari, Associate Professor in ECE Department, UT Austin, and Visiting Faculty Researcher at Google Research IFML Seminar: 05/02/25 - Efficient Algorithms for Learning with Distribution Shift Adam Klivans, professor of computer science and director of IFML and Machine Learning Lab, UT-Austin IFML Seminar: 04/25/25 - On the Role of Gaussian Covariates in Minimum Norm Interpolation Gil Kur, postdoctoral fellow at ETH Zürich IFML Seminar: 04/18/25 - Learning to Solve Imaging Inverse Problems without Ground Truth Andrew Wang, PhD student, Institute for Imaging, Data and Communications in the School of Engineering, University of Edinburgh IFML Seminar: 04/11/25 - Beyond Benchmarks: Building a Science of AI Measurement Sanmi Koyejo, assistant professor in Computer Science, Stanford University and co-founder of Virtue AI IFML Seminar: 03/28/2025 - Simple Binary Hypothesis Testing: One-shot Bayes Error Bounds and Reverse Data-processing Inequalities Varun Jog, professor of Information Theory and Statistics, Department of Pure Mathematics and Mathematical Statistics (DPMMS), University of Cambridge IFML Seminar: 03/14/2025 - Training-free Approaches for Image Inversion and Editing Using Latent Generative Models Sanjay Shakkottai, Professor in the Chandra Family Department of Electrical and Computer Engineering, UT Austin IFML Seminar: 03/13/2025 - Near-Optimal Algorithms for Semirandom Planted Clique Pravesh K. Kothari, Assistant Professor in Computer Science, Princeton IFML Seminar: 03/07/2025 - Spectral Norm of Random Matrices and Tensors March Boedihardjo, assistant professor at Michigan State University IFML Seminar: 02/28/2025 - Bridging Generative and Discriminative Learning with Contrastive Mutual Information Machine Micha Livne, Senior Research Scientist at NVIDIA IFML Seminar: 02/14/2025 - Differentiable Weightless Neural Networks (DWNs) Alan T. L. Bacellar, Ph. D student in the Electrical and Computer Engineering Department, UT Austin IFML Seminar: 02/07/2025 - Preference Optimization in Large Language Model Alignment: Personalization, Common Pitfalls and Beyond Leqi Liu, Assistant Professor in use-inspired AI, Department of Information, Risk and Operations Management - UT Austin IFML Seminar: 01/31/2025 - Testing Noise Assumptions of Learning Algorithms Arsen Vasilyan, postdoctoral fellow at the Institute for Foundations of Machine Learning IFML Seminar: 12/13/2024 - Safe and Informative Imaging via Conformal Prediction and Generative Models Phil Schniter, Professor, Electrical and Computer Engineering The Ohio State University IFML Seminar: 12/06/24 - Unscripted Grounded Visual Learning Stella Yu, Professor of Electrical Engineering and Computer Science University of Michigan IFML Seminar: 11/15/24 Online Convex Optimization with a Separation Oracle Zak Mhammedi, Research Scientist at Google Research Tutorial on Diffusion Models for Image Generation -- Sanjay Shakkottai Sanjay Shakkottai IFML Seminar: 10/4/25 - Foundation Model for Sequential Decision-Making Furong Huang, Associate Professor, University of Maryland IFML Seminar: 9/27/24 - Computationally Efficient Reinforcement Learning with Linear Bellman Completeness Noah Golowich , PhD Student, MIT IFML Seminar: 9/13/24 - On the Computational Complexity of Private High-dimensional Model Selection Saptarshi Roy, Postdoc Research Fellow, The University of Texas at Austin IFML Seminar: 9/6/24 - Perceiving Humans in 4D Georogios Pavlakos, Assistant Professor, UT Austin IFML Seminar: 8/23/24 - Clued-in to Clueless: Navigating Distribution Shifts with Varying Levels of Target Distribution Information Olawale Salaudeen, Postdoctoral Associate, MIT CSAIL IFML Seminar: Generating a Video: Reflecting on a Two-Year Odyssey Atlas Wang, Associate Professor, UT Austin AIHealthTalk : 4/10/24 - Towards Digital Twins for Cardiovascular Health: From Clinical To Remote Bobak Mortazavi, Associate Professor, Texas A&M University IFML Seminar: 4/5/24 - Robustness in the Era of LLMs: Jailbreaking Attacks and Defenses Hamed Hassani, Associate Professor, The University of Pennsylvania AIHealthTalk : 4/3/24 - The Generalist Medical AI Will See You Now Pranav Rajpurkar, Assistant Professor, Harvard University AIHealthTalk : 3/27/24 - Shaping the Creation and Adoption of Large Language Models in Healthcare Nigam Shah, Professor, Stanford University AIHealthTalk: 3/20/24 - How LLMs Might Help Scale World Class Healthcare to Everyone Vivek Natarajan, Research Scientist, Google Health IFML Seminar: 3/8/2024 - An Lyapunov Analysis of the Lion Optimizer IFML Seminar: 2/23/2024 - Recent Advances in Parallel Stochastic Convex Optimization IFML Seminar: 3/1/2024 - On Solving Inverse Problems Using Latent Diffusion-based Generative Models Sanjay Shakkottai, Professor Cockrell Family Chair in Engineering # 1, UT Austin IFML SEMINAR: 2/16/24 - Long Context Foundational Models Srinadh Bhojanapalli, Research Scientist at Google Research IFML SEMINAR: 2/2/24 - Gromov-Wasserstein Alignment: Statistical and Computational Advancements via Duality IFML SEMINAR: Jan 26, 2024 - Meta Optimization Elad Hazan, Professor, Princeton and Director and co-founder, Google AI Princeton Pagination Page 1 Page 2 Next page Next Last page
