382 citations · 1.6k across the 39 of their papers we have counts for
8 papers · 1 filter
Efficient Strong Scaling Through Burst Parallel Training
Seo Jin Park, Joshua Fried, Sunghyun Kim +2
As emerging deep neural network (DNN) models continue to grow in size, using large GPU clusters to train DNNs is becoming an essential requirement to achieving acceptable training…
Updating Street Maps using Changes Detected in Satellite Imagery
Favyen Bastani, Songtao He, Satvat Jagwani +5
Accurately maintaining digital street maps is labor-intensive. To address this challenge, much work has studied automatically processing geospatial data sources such as GPS traject…
Throughput-Fairness Tradeoffs in Mobility Platforms
Arjun Balasingam, Karthik Gopalakrishnan, Radhika Mittal +5
This paper studies the problem of allocating tasks from different customers to vehicles in mobility platforms, which are used for applications like food and package delivery, rides…
Efficient Video Compression via Content-Adaptive Super-Resolution
Mehrdad Khani, Vibhaalakshmi Sivaraman, Mohammad Alizadeh
Video compression is a critical component of Internet video delivery. Recent work has shown that deep learning techniques can rival or outperform human-designed algorithms, but the…
TagMe: GPS-Assisted Automatic Object Annotation in Videos
Songtao He, Favyen Bastani, Mohammad Alizadeh +4
Training high-accuracy object detection models requires large and diverse annotated datasets. However, creating these data-sets is time-consuming and expensive since it relies on h…
SWP: Microsecond Network SLOs Without Priorities
Kevin Zhao, Prateesh Goyal, Mohammad Alizadeh +1
The increasing use of cloud computing for latency-sensitive applications has sparked renewed interest in providing tight bounds on network tail latency. Achieving this in practice…
The Effect of Network Topology on Credit Network Throughput
Vibhaalakshmi Sivaraman, Weizhao Tang, Shaileshh Bojja Venkatakrishnan +2
Credit networks rely on decentralized, pairwise trust relationships (channels) to exchange money or goods. Credit networks arise naturally in many financial systems, including the…
Flow-Loss: Learning Cardinality Estimates That Matter
Parimarjan Negi, Ryan Marcus, Andreas Kipf +4
Previous approaches to learned cardinality estimation have focused on improving average estimation error, but not all estimates matter equally. Since learned models inevitably make…