Skip to main content
King Abdullah University of Science and Technology
Bayesian Computational Statistics and Modeling
BAYESCOMP
Bayesian Computational Statistics and Modeling

Main navigation

  • Home
  • People
    • All Profiles
    • Principal Investigators
    • Research Scientists
    • Postdoctoral Fellows
    • Students
    • Alumni
    • Former Members
  • Events
    • All Events
    • Events Calendar
  • News
  • About
  • Research
  • Software
  • Contact Us

personalized learning

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.

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

Bayesian Computational Statistics and Modeling (BAYESCOMP)

Footer

  • A-Z Directory
    • All Content
    • Browse Related Sites
  • Site Management
    • Log in

© 2025 King Abdullah University of Science and Technology. All rights reserved. Privacy Notice