Online Learning for Network Resource Allocation

Explore network resource allocation challenges and solutions in this comprehensive seminar presented by Dr. Tareq Si Salem from Northeastern University. Dive into the complexities of managing network resources in an era of connected devices, where applications from autonomous driving to augmented reality demand precise latency and bandwidth requirements. Learn how network resource allocation optimizes service delivery and reduces network congestion while addressing real-world challenges like temporal variations in network parameters and unpredictable demand patterns. Examine specific cases including exact caching, similarity caching, and inference delivery networks, with special attention to fairness considerations. Discover how online learning and adversarial analysis techniques can provide robust performance guarantees in unpredictable environments. Benefit from Dr. Si Salem's expertise in machine learning, networking, and modeling, supported by his extensive research background at prestigious institutions and recognition through publications in top academic venues, including his Best Paper Award at the International Teletraffic Congress.