94 citations · 112 across the 18 of their papers we have counts for
4 papers · 1 filter
Inferring Causal Relationships to Improve Caching for Clients with Correlated Requests: Applications to VR
Agrim Bari, Gustavo de Veciana, Yuqi Zhou
Efficient edge caching reduces latency and alleviates backhaul congestion in modern networks. Traditional caching policies, such as Least Recently Used (LRU) and Least Frequently U…
Optimal Resource Allocation for ML Model Training and Deployment under Concept Drift
Hasan Burhan Beytur, Haris Vikalo, Kevin S Chan +1
We study how to allocate resources for training and deployment of machine learning (ML) models under concept drift and limited budgets. We consider a setting in which a model provi…
Optimal Scheduling Algorithms for LLM Inference: Theory and Practice
Agrim Bari, Parikshit Hegde, Gustavo de Veciana
With the growing use of Large Language Model (LLM)-based tools like ChatGPT, Perplexity, and Gemini across industries, there is a rising need for efficient LLM inference systems. T…
Efficient Weighted Sampling via Score-based Generative Models
Heasung Kim, Taekyun Lee, Hyeji Kim +1
Weighted sampling -- sampling from a probability density function (PDF) proportional to the product of a base PDF and a weight function -- is a fundamental technique with wide-rang…