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  • Optimization for ML and AI Seminar with Courtney Paquette (McGill University): High-dimensional Optimization with Applications to Compute-Optimal Neural Scaling Laws

    CSE 1242 and Virtual 3235 Voigt Dr, La Jolla, CA, United States

    Courtney Paquette, McGill University Abstract: Given the massive scale of modern ML models, we now only get a single shot to train them effectively. This restricts our ability to test multiple architectures and hyper-parameter configurations. Instead, we need to understand how these models scale, allowing us to experiment with smaller problems and then apply those […]

  • TILOS-SDSU Seminar: Certifiably Correct Machine Perception

    Lamden Hall 341 (SDSU) and Virtual San Diego, CA, United States

    David Rosen, Northeastern University Abstract: Many fundamental machine perception and state estimation tasks require the solution of a high-dimensional nonconvex estimation problem; this class includes (for example) the fundamental problems of simultaneous localization and mapping (in robotics), 3D reconstruction (in computer vision), and sensor network localization (in distributed sensing). Such problems are known to be […]

  • Workshop on Topology, Algebra, and Geometry in Data Science (co-located with NeurIPS 2025)

    UC San Diego La Jolla, CA, United States

    We are thrilled to announce the first official TAG-DS Stand-Alone Event--TAG... We're it! This will be a two day event, December 1 & 2, 2025, featuring keynotes, poster sessions, spotlight talks, collaboration activities, and community development. The dates and location were selected to align with NeurIPS 2025--twice the fun! The event will be hosted on […]

  • TILOS-SDSU Seminar: 95 Percent: Bridging the Gap Between Prototype and Product

    Lamden Hall 341 (SDSU) and Virtual San Diego, CA, United States

    Jeremy Schwartz, Zoox Abstract: When transitioning from the academic world to the professional world of engineering, one of the most common pitfalls is failing to understand the difference between a compelling prototype and a successful product. This talk will focus on that distinction. We will discuss the differences between them, and the work required to […]

  • 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 […]