Ai4opt Seminar Series Accelerated First

Abstract: Semidefinite programs (SDPs) have been used as a tractable relaxation for many NP-hard problems that naturally arise ... Abstract: Graph Neural Networks (GNNs) have become a popular tool for learning algorithmic tasks, related to combinatorial ... Full Title: Using Machine Learning for Combinatorial Optimization (ML4CO): Case Studies and Research Directions Abstract: ... Abstract: Markov decision processes (MDPs) constitute one of the predominant modeling and solution paradigms for dynamic ... Abstract: Optimization problems constrained by neural network surrogates arise in design, control, and verification problems ... Abstract: Neural network driven applications suffer from hallucination and calibration issues where they confidently provide ...

Controlling Learned Inverter Dynamics of Distributed Energy Resources and Long-term Planning for Long-duration Energy ... Bridging Learning and Reasoning: From Solvers to LLMs Abstract: From its inception, AI has had two broad sub-fields, namely, ... Title: On the Foundations of Interactive Decision Making and Reinforcement Learning Abstract: In this talk, we will present a new ... Full Title: A Model-Free Approach for Solving Choice-Based Competitive Facility Location Problems Using Simulation and ... Abstract: We discuss our recent research aimed at solving truly huge-scale convex optimization problems, at the scale where ... Parametric Optimization Beyond Discretization Abstract: Many applications require solving a family of optimization problems, ...

Abstract: Data-driven learning and decision-making in complex systems are often subject to a variety of operational constraints ...