Naram Mhaisen
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  • News & Updates
    • Paper Accepted at NeurIPS 2026
    • Successfully Defended My Ph.D. Dissertation
  • Publications
    • Dynamic Regret in Online Convex Optimization with Indicator Switching Costs
    • Partially Lazy Gradient Descent for Smoothed Online Learning
    • DRONE-RL: Dynamic Reinforcement Learning for Online Navigation of UAVs in Evolving Environments
    • Optimistic Learning with Applications to Caching Networks
    • On the Dynamic Regret of Following the Regularized Leader: Optimism with History Pruning
    • Multi-Target Path Planning with Probabilistic Detection in Cluttered Environments
    • Slicing for AI: An Online Learning Framework for Network Slicing Supporting AI Services
    • An Online Learning Framework for UAV Search Mission in Adversarial Environments
    • Optimistic Learning for Communication Networks
    • An Online Learning Framework for UAV Target Search Missions in Non-stationary Environments
    • Adaptive Online Non-stochastic Control
    • Online Caching with no Regret: Optimistic Learning via Recommendations
    • Optimistic Online Non-stochastic Control via FTRL
    • Reinforcement Learning for Intelligent Healthcare Systems: A Review
    • Data Storage Methods and Systems
    • Federated Learning for Online Resource Allocation in Mobile Edge Computing: A Deep Reinforcement Learning Approach
    • Data Storage Methods and Systems
    • Optimistic No-regret Algorithms for Discrete Caching
    • Exploring Deep Reinforcement Learning-Assisted Federated Learning for Online Resource Allocation in Privacy-Preserving EdgeIoT
    • Pervasive AI for IoT Applications: A Survey on Resource-Efficient Distributed Artificial Intelligence
    • Online Caching with Optimistic Learning
    • Multi-Agent Reinforcement Learning for Network Selection and Resource Allocation in Heterogeneous Multi-RAT Networks
    • Communication-Efficient Hierarchical Federated Learning for IoT Heterogeneous Systems
    • On Designing Smart Agents for Service Provisioning in Blockchain-Powered Systems
    • Rational Contracts: Data-Driven Service Provisioning in Blockchain-Powered Systems
    • Optimal User-Edge Assignment in Hierarchical Federated Learning
    • To Chain or Not to Chain: A Reinforcement Learning Approach for Blockchain-Enabled IoT Monitoring
    • Data Consistency in Multi-Cloud Storage Systems with Passive Servers and Non-Communicating Clients
    • Novel Techniques for Blockchain-Enabled IoT Systems Leveraging Reinforcement Learning
    • Real-Time Scheduling for Electric Vehicles Charging/Discharging Using Reinforcement Learning
    • Secure Smart Contract-Enabled Control of Battery Energy Storage Systems against Cyber-Attacks
    • A Reconfigurable Multipurpose System on Chip Platform for Metal Detection
    • Self-Powered IoT-Enabled Water Monitoring System
    • A Reconfigurable Multipurpose SoC Mobile Platform for Metal Detection
    • Almost BPXOR Coding Technique for Tolerating Three Disk Failures in RAID7 Architectures
  • Research Interests
  • Talks & Presentations
    • ELLIS Delft Talk: Optimistic Learning and Applications to Resource Management
    • Tutorial: Optimistic Learning for Resource Management in Communication Systems
    • Invited Seminar: Adversarial Online Learning
  • Curriculum Vitae

Invited Seminar: Adversarial Online Learning

Jun 1, 2023
Slides
Abstract
An invited seminar covering the foundations of adversarial online learning, regret minimization, and applications to resource management.
Date
Jun 1, 2023
Event
Qatar University — Department of Computer Science & Engineering Seminar
Location

Qatar University, Doha, Qatar

events
Last updated on Jun 1, 2023
Tutorial: Optimistic Learning for Resource Management in Communication Systems Jun 10, 2024 →

© 2026 Naram Mhaisen. This work is licensed under CC BY NC ND 4.0

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