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  • Optimization for AI and ML Seminar: Training Neural Networks at Any Scale

    HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States

    Volkan Cevher, École Polytechnique Fédérale de Lausanne Abstract: At the heart of deep learning’s transformative impact lies the concept of scale--encompassing both data and computational resources, as well as their interaction with neural network architectures. Scale, however, presents critical challenges, such as increased instability during training and prohibitively expensive model-specific tuning. Given the substantial resources […]

  • Networking Lunch Reception at NeurIPS 2025

    Mezé Greek Fusion San Diego, CA, United States

    TILOS will host a networking lunch reception during NeurIPS 2025 at Mezé Greek Fusion from 12:00-2:00pm on Thursday, December 4, 2025. This event is open to all NeurIPS attendees affiliated with any of the NSF AI Research Institutes, as well as invited industry partners. Join us to connect with colleagues across the network of NSF […]

  • Optimization for ML and AI Seminar: Stochastic-Gradient and Diagonal-Scaling Algorithms for Constrained Optimization and Learning

    HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States

    Frank E. Curtis, Lehigh University Abstract: I will motivate and provide an overview of recent efforts in my research group on the design and analysis of stochastic-gradient-based algorithms for solving constrained optimization problems. I will focus in particular on our motivation for informed supervised learning, where constraints in the training problem can be used to […]

  • Optimization for ML and AI Seminar with Joel Tropp (Caltech)

    HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States

    Title and abstract TBA... Joel A. Tropp is Steele Family Professor of Applied & Computational Mathematics at the California Institute of Technology. His research centers on applied mathematics, machine learning, data science, numerical algorithms, and random matrix theory. Some of his best-known contributions include matching pursuit algorithms, randomized SVD algorithms, matrix concentration inequalities, and statistical phase transitions. Prof. Tropp attained the […]

  • Optimization for ML and AI Seminar with Tengyu Ma (Stanford)

    HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States

    Title and abstract TBA... Tengyu Ma is an assistant professor of computer science at Stanford University. His research interests broadly include topics in machine learning, algorithms and their theory, such as deep learning, (deep) reinforcement learning, pre-training / foundation models, robustness, non-convex optimization, distributed optimization, and high-dimensional statistics. Zoom: https://bit.ly/Opt-AI-ML

  • Optimization for ML and AI Seminar with Yang Zheng (UC San Diego)

    HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States

    Title and abstract TBA... Yang Zheng is an Assistant Professor in Electrical and Computer Engineering at UC San Diego, and is affiliated with the department of Computer Science and Engineering and the Contextual Robotics Institute. From March 2019 to August 2020, Dr. Zheng was a postdoctoral scholar in SEAS and CGBC at Harvard University, working […]

  • Optimization for ML and AI Seminar with Bharath Sriperumbudur (Penn State)

    HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States

    Title and abstract TBA... Bharath Sriperumbudur is a professor in the Department of Statistics (with a courtesy appointment in the Department of Mathematics) at the Pennsylvania State University. His research interests include non-parametric statistics, machine learning, statistical learning theory, optimal transport and gradient flows, regularization and inverse problems, reproducing kernel spaces in probability and statistics, […]

  • Optimization for ML and AI Seminar with Yuejie Chi (Yale)

    HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States

    Title and abstract TBA... Yuejie Chi is the Charles C. and Dorothea S. Dilley Professor of Statistics and Data Science at Yale University, with a secondary appointment in Computer Science, and a member of the Yale Institute for Foundations of Data Science. Before joining Yale, Dr. Chi was the Sense of Wonder Group Endowed Professor […]

  • Optimization for ML and AI Seminar with Andre Wibisono (Yale)

    HDSI 123 and Virtual 3234 Matthews Ln, La Jolla, CA, United States

    Title and abstract TBA... Andre Wibisono is an assistant professor in the Department of Computer Science at Yale University, with a secondary appointment in the Department of Statistics & Data Science. His research interests are in the design and analysis of algorithms for machine learning, in particular for problems in optimization, sampling, and game theory. […]