decentralized systems

Learning under Limited Information across Federated, Multi-Agent, and LLM Settings

Salma Kharrat, Ph.D. Student, Computer Science

May 7, 15:00 - 16:45

B3 R5220

Federated learning personalized learning decentralized learning Reinforcement Learning black-box optimization prompt optimization decentralized systems combinatorial optimization observability inference Trustworthy AI trustworthy machine learning intelligent systems LLM

This dissertation studies learning under structural information constraints across three major paradigms: federated learning, cooperative multi-agent reinforcement learning, and black-box optimization of large language models.

Fully Decentralized Inference for Spatial Data Using Low-Rank Models

Jianwei Shi, Postdoctoral Research Fellow, Statistics

May 7, 12:00 - 13:00

B9 R2325

statistical inference decentralized systems Geospatial Data geospatial statistics optimization

This talk introduces a novel, fully decentralized optimization framework to enable scalable parameter inference in large spatial low-rank models, supported by both theoretical guarantees and empirical validation.

Jianwei Shi

Postdoctoral Research Fellow, Statistics

distributed computing decentralized systems Statistical Modelling geospatial statistics geospatial modeling

Salma Kharrat

Ph.D. Student, Computer Science

Federated learning Trustworthy AI trustworthy machine learning intelligent systems decentralized systems combinatorial optimization personalized learning decentralized learning Reinforcement Learning observability inference black-box optimization LLM prompt optimization