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Nov 13, 2019
Computer Vision

Momentum Contrast for Unsupervised Visual Representation Learning

We present Momentum Contrast (MoCo) for unsupervised visual representation learning. From a perspective on contrastive learning as dictionary look-up…
Nov 13, 2019
Machine Learning

A Convergent Off-Policy Temporal Difference Algorithm

Learning the value function of a given policy (target policy) from the data samples obtained from a different policy (behavior policy) is an importan…
Nov 13, 2019
Computer Vision

Extracting 2D weak labels from volume labels using multiple instance …

Multiple instance learning (MIL) is a supervised learning methodology that aims to allow models to learn instance class labels from bag class labels,…
Nov 13, 2019
Robotics
Computer Vision

Are We Ready for Service Robots? The OpenLORIS-Scene Datasets for L…

Service robots should be able to operate autonomously in dynamic and daily changing environments over an extended period of time. While Simultaneous …
Nov 13, 2019
Networking and Internet Architecture
Machine Learning

MOTH- Mobility-induced Outages in THz: A Beyond 5G (B5G) application

5G will enable the growing demand for Internet of Things (IoT), high-resolution video streaming, and low latency wireless services. Demand for such s…
Nov 13, 2019
Machine Learning
Computation and Language

Structured Sparsification of Gated Recurrent Neural Networks

Recently, a lot of techniques were developed to sparsify the weights of neural networks and to remove networks' structure units, e.g. neurons. We adj…
Nov 13, 2019
Quantitative Methods
Computer Vision
Image and Video Processing

DARTS: DenseUnet-based Automatic Rapid Tool for brain Segmentation

Quantitative, volumetric analysis of Magnetic Resonance Imaging (MRI) is a fundamental way researchers study the brain in a host of neurological cond…
Nov 13, 2019
Computer Vision

Cost-efficient segmentation of electron microscopy images using activ…

Over the last decade, electron microscopy has improved up to a point that generating high quality gigavoxel sized datasets only requires a few hours.…
Nov 13, 2019
Machine Learning

Learning Relationships between Text, Audio, and Video via Deep Canoni…

Multimodal language analysis often considers relationships between features based on text and those based on acoustical and visual properties. Text f…
Nov 13, 2019
Cryptography and Security
Computer Vision

IStego100K: Large-scale Image Steganalysis Dataset

In order to promote the rapid development of image steganalysis technology, in this paper, we construct and release a multivariable large-scale image…
Nov 13, 2019
Computer Vision

Multi-domain CT metal artifacts reduction using partial convolution …

Recent CT Metal Artifacts Reduction (MAR) methods are often based on image-to-image convolutional neural networks for adjustment of corrupted sinogra…
Nov 13, 2019
Signal Processing
Machine Learning
Neural and Evolutionary Computation

Real-time ultra-low power ECG anomaly detection using an event-driven…

Accurate detection of pathological conditions in human subjects can be achieved through off-line analysis of recorded biological signals such as elec…
Nov 13, 2019
Machine Learning

Compressive Transformers for Long-Range Sequence Modelling

We present the Compressive Transformer, an attentive sequence model which compresses past memories for long-range sequence learning. We find the Comp…
Nov 13, 2019
Audio and Speech Processing
Machine Learning
Sound

3-D Feature and Acoustic Modeling for Far-Field Speech Recognition

Automatic speech recognition in multi-channel reverberant conditions is a challenging task. The conventional way of suppressing the reverberation art…
Nov 13, 2019
Machine Learning

Uncertainty on Asynchronous Time Event Prediction

Asynchronous event sequences are the basis of many applications throughout different industries. In this work, we tackle the task of predicting the n…
Nov 13, 2019
Artificial Intelligence

HDDL -- A Language to Describe Hierarchical Planning Problems

The research in hierarchical planning has made considerable progress in the last few years. Many recent systems do not rely on hand-tailored advice a…
Nov 13, 2019
Robotics
Systems and Control

Deep Reinforcement Learning Attitude Control of Fixed-Wing UAVs Using…

Contemporary autopilot systems for unmanned aerial vehicles (UAVs) are far more limited in their flight envelope as compared to experienced human pil…
Nov 13, 2019
Machine Learning
Optimization and Control

Asynchronous Distributed Learning from Constraints

In this paper, the extension of the framework of Learning from Constraints (LfC) to a distributed setting where multiple parties, connected over the …
Nov 13, 2019
Fluid Dynamics
Statistical Mechanics
Artificial Intelligence
Machine Learning

In presence of limited statistics as in the case of relatively short signals, the estimation of the width of the inertial range or, similarly, the estimation of the viscosity, is enslaved to large scale energy fluctuations. On a time scale comparabl…

Deep learning velocity signals allows to quantify turbulence intensity

Turbulence, the ubiquitous and chaotic state of fluid motions, is characterized by strong and statistically non-trivial fluctuations of the velocity …
Nov 13, 2019
Computation and Language

We introduced an approach to generating word definitions that allows the model to access rich contextual information about the word token to be defined. Building on the distributional hypothesis, we naturally treat definition generation as a sequenc…

Mark my Word: A Sequence-to-Sequence Approach to Definition Modeling

Defining words in a textual context is a useful task both for practical purposes and for gaining insight into distributed word representations. Build…
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