222 citations · 467 across the 10 of their papers we have counts for
4 papers · 1 filter
Quantized deep learning models on low-power edge devices for robotic systems
Anugraha Sinha, Naveen Kumar, Murukesh Mohanan +4
In this work, we present a quantized deep neural network deployed on a low-power edge device, inferring learned motor-movements of a suspended robot in a defined space. This serves…
Scale MLPerf-0.6 models on Google TPU-v3 Pods
Sameer Kumar, Victor Bitorff, Dehao Chen +9
The recent submission of Google TPU-v3 Pods to the industry wide MLPerf v0.6 training benchmark demonstrates the scalability of a suite of industry relevant ML models. MLPerf defin…
MLPerf Training Benchmark
Peter Mattson, Christine Cheng, Cody Coleman +34
Machine learning (ML) needs industry-standard performance benchmarks to support design and competitive evaluation of the many emerging software and hardware solutions for ML. But M…
Multimodal Representation Learning using Deep Multiset Canonical Correlation
Krishna Somandepalli, Naveen Kumar, Ruchir Travadi +1
We propose Deep Multiset Canonical Correlation Analysis (dMCCA) as an extension to representation learning using CCA when the underlying signal is observed across multiple (more th…