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06/11/2019
Table-Based Neural Units: Fully Quantizing Networks for Multiply-Free Inference
In this work, we propose to quantize all parts of standard classificatio...
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12/06/2018
Neural Image Decompression: Learning to Render Better Image Previews
A rapidly increasing portion of Internet traffic is dominated by request...
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09/24/2018
No Multiplication? No Floating Point? No Problem! Training Networks for Efficient Inference
For successful deployment of deep neural networks on highly--resource-co...
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09/07/2018
Representing Images in 200 Bytes: Compression via Triangulation
A rapidly increasing portion of internet traffic is dominated by request...
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05/31/2018
Image-Dependent Local Entropy Models for Learned Image Compression
The leading approach for image compression with artificial neural networ...
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02/07/2018
Spatially adaptive image compression using a tiled deep network
Deep neural networks represent a powerful class of function approximator...
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05/18/2017
Target-Quality Image Compression with Recurrent, Convolutional Neural Networks
We introduce a stop-code tolerant (SCT) approach to training recurrent c...
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03/29/2017
Improved Lossy Image Compression with Priming and Spatially Adaptive Bit Rates for Recurrent Networks
We propose a method for lossy image compression based on recurrent, conv...
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02/03/2017
Traffic Lights with Auction-Based Controllers: Algorithms and Real-World Data
Real-time optimization of traffic flow addresses important practical pro...
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08/18/2016
Full Resolution Image Compression with Recurrent Neural Networks
This paper presents a set of full-resolution lossy image compression met...
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11/19/2015
