2 citations · 4 across the 4 of their papers we have counts for
4 papers
Optimizing High-Throughput Distributed Data Pipelines for Reproducible Deep Learning at Scale
Kashish Mittal, Di Yu, Roozbeh Ketabi +3
Training massive-scale deep learning models on datasets spanning tens of terabytes presents critical challenges in hardware utilization and training reproducibility. In this paper,…
Practical Prediction of Human Movements Across Device Types and Spatiotemporal Granularities
Babak Alipour, Leonardo Tonetto, Roozbeh Ketabi +3
Understanding and predicting mobility are essential for the design and evaluation of future mobile edge caching and networking. Consequently, research on prediction of human mobili…
Playing with Matches: Vehicular Mobility through Analysis of Trip Similarity and Matching
Roozbeh Ketabi, Babak Alipour, Ahmed Helmy
Understanding city-scale vehicular mobility and trip patterns is essential to addressing many problems, from transportation and pollution to public safety, among others. Using spat…
Analyzing Mobility-Traffic Correlations in Large WLAN Traces: Flutes vs. Cellos
Babak Alipour, Leonardo Tonetto, Aaron Ding +3
Two major factors affecting mobile network performance are mobility and traffic patterns. Simulations and analytical-based performance evaluations rely on models to approximate fac…