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06/11/2023
CARNA: Characterizing Advanced heart failure Risk and hemodyNAmic phenotypes using learned multi-valued decision diagrams
Early identification of high risk heart failure (HF) patients is key to ...
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12/05/2022
Dissimilar Nodes Improve Graph Active Learning
Training labels for graph embedding algorithms could be costly to obtain...
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05/17/2021
Rethinking "Batch" in BatchNorm
BatchNorm is a critical building block in modern convolutional neural ne...
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12/17/2019
PointRend: Image Segmentation as Rendering
We present a new method for efficient high-quality image segmentation of...
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11/13/2019
Momentum Contrast for Unsupervised Visual Representation Learning
We present Momentum Contrast (MoCo) for unsupervised visual representati...
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09/10/2019
Bayesian Relational Memory for Semantic Visual Navigation
We introduce a new memory architecture, Bayesian Relational Memory (BRM)...
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12/09/2018
Feature Denoising for Improving Adversarial Robustness
Adversarial attacks to image classification systems present challenges t...
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11/14/2018
Natural Environment Benchmarks for Reinforcement Learning
While current benchmark reinforcement learning (RL) tasks have been usef...
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09/28/2018
Learning and Planning with a Semantic Model
Building deep reinforcement learning agents that can generalize and adap...
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03/22/2018
Group Normalization
Batch Normalization (BN) is a milestone technique in the development of ...
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01/07/2018
Building Generalizable Agents with a Realistic and Rich 3D Environment
Towards bridging the gap between machine and human intelligence, it is o...
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07/04/2017
ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games
In this paper, we propose ELF, an Extensive, Lightweight and Flexible pl...
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11/30/2016
Effective Quantization Methods for Recurrent Neural Networks
Reducing bit-widths of weights, activations, and gradients of a Neural N...
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06/20/2016
DoReFa-Net: Training Low Bitwidth Convolutional Neural Networks with Low Bitwidth Gradients
We propose DoReFa-Net, a method to train convolutional neural networks t...
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12/31/2015
Exploiting Local Structures with the Kronecker Layer in Convolutional Networks
In this paper, we propose and study a technique to reduce the number of ...
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07/30/2015