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  • TILOS Seminar: Foundational Methods for Foundation Models for Scientific Machine Learning

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

    Michael W. Mahoney, ICSI, LBNL, and Department of Statistics, UC Berkeley Abstract: The remarkable successes of ChatGPT in natural language processing (NLP) and related developments in computer vision (CV) motivate the question of what foundation models would look like and what new advances they would enable, when built on the rich, diverse, multimodal data that […]

  • TILOS Seminar: Amplifying human performance in combinatorial competitive programming

    Virtual

    Petar Veličković, Google DeepMind Abstract: Recent years have seen a significant surge in complex AI systems for competitive programming, capable of performing at admirable levels against human competitors. While steady progress has been made, the highest percentiles still remain out of reach for these methods on standard competition platforms such as Codeforces. In this talk, […]

  • TILOS Seminar: Optimal Quantization for LLMs and Matrix Multiplication

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

    Yury Polyanskiy, MIT Abstract: The main building block of large language models is matrix multiplication, which is often bottlenecked by the speed of loading these matrices from memory. A number of recent quantization algorithms (SmoothQuant, GPTQ, QuIP, SpinQuant etc) address this issue by storing matrices in lower precision. We derive optimal asymptotic information-theoretic tradeoff between […]

  • TILOS-HDSI Seminar with Adam Klivans (UT Austin): A New Paradigm for Learning with Distribution Shift

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

    Adam Klivans, The University of Texas at Austin Abstract: We revisit the fundamental problem of learning with distribution shift, where a learner is given labeled samples from training distribution D, unlabeled samples from test distribution D′ and is asked to output a classifier with low test error. The standard approach in this setting is to […]

  • 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 […]

  • Student and Postdoc Lunch at Zanzibar Cafe

    Zanzibar Cafe at UC San Diego

    Join fellow TILOS students and postdoctoral researchers for an informal lunch at Zanzibar Cafe, located on the second floor of Price Center.

  • 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 with Jeremy Schwartz (Zoox)

    SDSU and Virtual

    Title and abstract TBA... Jeremy Schwartz is a robotics engineer at Zoox with expertise in a wide variety of areas of mechanical and electrical engineering and computer science. His primary professional expertise is in autonomy and behavioral algorithms, and he has worked in the aerospace industry as well as ground robotics, specializing in autonomous systems […]