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A Progressive Batching L-BFGS Method for Machine Learning

See how an improvement to the L-BFGS algorithm takes advantage of progressive batching, line search, and quasi-Newton updating.

Authored by admin Last updated on 12/31/2018 - 14:00
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An Optimized Architecture for Unpaired Image-to-Image Translation

This paper introduces a new neural network architecture and shows how improvements to a Cycle-GAN significantly reduces training time for translating images across domains.

Authored by admin Last updated on 08/02/2018 - 10:43
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Boost Adversarial Attacks with Momentum

Learn more about an award-wining method that uses noise unnoticeable to humans to confuse neural networks into making enormous mistakes.

Authored by admin Last updated on 08/02/2018 - 10:41
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Break Natural Language Inference (NLI) Systems with Simple Lexical Interfaces

A new test shows that some of the best state-of-the-art natural language models fail by changing even just a few words.

Authored by admin Last updated on 08/02/2018 - 10:40
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DSOD: Deeply Supervised Object Detectors

This research paper introduces DSOD, a framework that outperforms modern variations of regional proposal and classification networks.

Authored by admin Last updated on 08/02/2018 - 10:41
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Explicit Loss-Error-Aware Quantization for Low-Bit Deep Neural Networks

This research shows how training low-bit deep neural networks has a much smaller memory footprint than full-precision models but with a small cost to accuracy.

Authored by admin Last updated on 08/02/2018 - 10:42
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Fast Weight Long Short-Term Memory

Read about a mechanism to improve the memory capacity and time-scale of recurrent neural networks that allows for higher accuracy and faster training.

Authored by admin Last updated on 08/02/2018 - 10:42
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Fruit Quantity and Quality Estimation Using a Robotic Vision System

This robotic vision innovation uses Intel® RealSense™ technology and a Faster R-CNN to track and harvest sweet peppers as a test for helping fruit farmers.

Authored by admin Last updated on 08/02/2018 - 10:42
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A Fully Convolutional Model for Variable Bit Length and Lossy High-Density Compression of Mammograms

Using a convolutional autoencoder, a compression algorithm rivals JPEG and JPEG 2000 to reduce the size of mammogram images.

Authored by admin Last updated on 08/02/2018 - 10:42
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HeNet: A Deep Learning Approach on Intel® Processor Trace for Effective Exploit Detection

This paper presents a novel technique for detecting malware through classifying hardware-generated control flow traces using a deep neural network.

Authored by admin Last updated on 08/02/2018 - 11:03