382 citations · 1.6k across the 39 of their papers we have counts for
5 papers · 1 filter
Real-Time Video Inference on Edge Devices via Adaptive Model Streaming
Mehrdad Khani, Pouya Hamadanian, Arash Nasr-Esfahany +1
Real-time video inference on edge devices like mobile phones and drones is challenging due to the high computation cost of Deep Neural Networks. We present Adaptive Model Streaming…
Placeto: Learning Generalizable Device Placement Algorithms for Distributed Machine Learning
Ravichandra Addanki, Shaileshh Bojja Venkatakrishnan, Shreyan Gupta +2
We present Placeto, a reinforcement learning (RL) approach to efficiently find device placements for distributed neural network training. Unlike prior approaches that only find a d…
Learning Scheduling Algorithms for Data Processing Clusters
Hongzi Mao, Malte Schwarzkopf, Shaileshh Bojja Venkatakrishnan +2
Efficiently scheduling data processing jobs on distributed compute clusters requires complex algorithms. Current systems, however, use simple generalized heuristics and ignore work…
Variance Reduction for Reinforcement Learning in Input-Driven Environments
Hongzi Mao, Shaileshh Bojja Venkatakrishnan, Malte Schwarzkopf +1
We consider reinforcement learning in input-driven environments, where an exogenous, stochastic input process affects the dynamics of the system. Input processes arise in many appl…
Graph2Seq: Scalable Learning Dynamics for Graphs
Shaileshh Bojja Venkatakrishnan, Mohammad Alizadeh, Pramod Viswanath
Neural networks have been shown to be an effective tool for learning algorithms over graph-structured data. However, graph representation techniques---that convert graphs to real-v…