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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 […]

  • 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 […]

  • Optimization for AI and ML Seminar with Volkan Cevher (EPFL)

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

    Title and abstract TBA... Volkan Cevher received the B.Sc. (valedictorian) in electrical engineering from Bilkent University in Ankara, Turkey, in 1999 and the Ph.D. in electrical and computer engineering from the Georgia Institute of Technology in Atlanta, GA in 2005. He was a Research Scientist with the University of Maryland, College Park from 2006-2007 and […]

  • Optimization for ML and AI Seminar with Frank E. Curtis (Lehigh University)

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

    Title and abstract TBA... Frank E. Curtis is a Professor in the Department of Industrial and Systems Engineering at Lehigh University, where he has been employed since 2009. He received a bachelor’s degree from the College of William and Mary in 2003 with a double major in Computer Science and Mathematics, received a master’s degree […]

  • NeurIPS 2025 Workshop on Differentiable Learning of Combinatorial Algorithms

    San Diego Convention Center San Diego, CA, United States

    Combinatorial algorithms are fundamental across a wide range of domains, owing to their ability to model optimization and decision-making tasks under complex constraints. These algorithms underpin practical applications such as vehicle routing, network and chip design, clustering and information retrieval. Combinatorial problems are also prominent in various areas of machine learning such as natural language […]

  • NeurIPS 2025 Workshop on Optimization for Machine Learning

    San Diego Convention Center San Diego, CA, United States

    Optimization lies at the heart of many machine learning algorithms and enjoys great interest in our community. Indeed, this intimate relation of optimization with ML is the key motivation for the OPT series of workshops. We aim to foster discussion, discovery, and dissemination of state-of-the-art research in optimization relevant to ML. The focus of OPT […]

  • NeurIPS 2025 Workhop on Imageomics: Discovering Biological Knowledge from Images Using AI

    San Diego Convention Center San Diego, CA, United States

    Imageomics is an emerging interdisciplinary field at the crossroads of machine learning (ML), computer vision (CV), and biological sciences. It leverages visual data—from microscopic images of single-cell species to videos of megafauna—to extract and analyze biological information, specifically traits. By grounding ML models in existing scientific knowledge, Imageomics aims to make traits computable from images, […]

  • NeurIPS 2025 Workshop on New Perspectives in Advancing Graph Machine Learning

    San Diego Convention Center San Diego, CA, United States

    Graphs serve as a powerful representational framework for machine learning, and their integration has substantially advanced the field. Indeed, extensive studies have pushed forward graph machine learning (GML) in both theory and applications. Recently, new perspectives have been emerging in the machine learning community, including algebraic–topological analyses, foundation models, generative models, and large models in […]

  • 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 […]