Speaker: Yang Zheng, UC San Diego Abstract: Direct policy search has achieved great empirical success in reinforcement learning. Many recent studies have revisited its theoretical foundation for continuous control, which revealsContinue reading "Optimization for ML and AI Seminar: Extended Convex Lifting for Policy Optimization in Control"
Speaker: Sung-Kyu Lim, University of Southern California Abstract: Multi-chip integration has become a standard approach in AI training and is rapidly gaining traction in edge learning applications. Leveraging 2.5D and 3DContinue reading "TILOS-MICS Seminar: AI-Driven Design Automation for Multi-Chip Integration in AI Chips"
Speaker: Maarten de Hoop, Rice University Abstract: We present a kinetic theory perspective of foundation models for physics. We begin with providing a mathematical framework for analyzing transformers. To uniformly addressContinue reading "TILOS Seminar: Kinetic Theory Perspective of Foundation Models for Physics"
Speaker: Jason Eshraghian, UC Santa Cruz Abstract: This talk will show you what neuromorphic computing can do when an academic lab accidentally pulls $2-million of GPU-hours. We will showcase a seriesContinue reading "TILOS Seminar: Neuromorphic LLMs"
Speaker: Bharath Sriperumbudur, Pennsylvania State University Abstract: Wasserstein gradient flows have become a popular tool in machine learning with applications in sampling, variational inference, generative modeling, and reinforcement learning, among others.Continue reading "Optimization for ML and AI Seminar: (De)regularized Wasserstein Gradient Flows via Reproducing Kernels"