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Dec 11, 2019
Image and Video Processing
Computer Vision

Variable Rate Deep Image Compression with Modulated Autoencoder

Variable rate is a requirement for flexible and adaptable image and video compression. However, deep image compression methods are optimized for a si…
Dec 11, 2019
Artificial Intelligence
Computation and Language
Machine Learning

Learning to Request Guidance in Emergent Communication

Previous research into agent communication has shown that a pre-trained guide can speed up the learning process of an imitation learning agent. The g…
Dec 11, 2019
Computer Vision

GLU-Net: Global-Local Universal Network for Dense Flow and Correspo…

Establishing dense correspondences between a pair of images is an important and general problem, covering geometric matching, optical flow and semant…
Dec 11, 2019
Computer Vision

SiamMan: Siamese Motion-aware Network for Visual Tracking

In this paper, we present a novel siamese motion-aware network (SiamMan) for visual tracking, which consists of the siamese feature extraction subnet…
Dec 11, 2019
Computers and Society
Machine Learning

Measurement and Fairness

We introduce the language of measurement modeling from the quantitative social sciences as a framework for understanding fairness in computational sy…
Dec 11, 2019
Machine Learning
Artificial Intelligence

SMiRL: Surprise Minimizing RL in Dynamic Environments

All living organisms struggle against the forces of nature to carve out niches where they can maintain homeostasis. We propose that such a search for…
Dec 11, 2019
Machine Learning
Signal Processing

The Wasserstein-Fourier Distance for Stationary Time Series

We introduce a novel framework for analysing stationary time series based on optimal transport distances and spectral embeddings. First, we represent…
Dec 11, 2019
Robotics

Zero-shot generalization using cascaded system-representations

This paper proposes a new framework named CASNET to learn control policies that generalize over similar robot types with different morphologies. The …
Dec 11, 2019
Artificial Intelligence
Machine Learning

What Can Learned Intrinsic Rewards Capture?

Reinforcement learning agents can include different components, such as policies, value functions, state representations, and environment models. Any…
Dec 11, 2019
Computation and Language

Quality of syntactic implication of RL-based sentence summarization

Work on summarization has explored both reinforcement learning (RL) optimization using ROUGE as a reward and syntax-aware models, such as models thos…
Dec 11, 2019
Artificial Intelligence
Machine Learning

Neural-Symbolic Descriptive Action Model from Images: The Search for …

Recent work on Neural-Symbolic systems that learn the discrete planning model from images has opened a promising direction for expanding the scope of…
Dec 11, 2019
Image and Video Processing
Computer Vision
Machine Learning

$Σ$-net: Ensembled Iterative Deep Neural Networks for Accelerated P…

We explore an ensembled $\Sigma$-net for fast parallel MR imaging, including parallel coil networks, which perform implicit coil weighting, and sensi…
Dec 11, 2019
Computation and Language
Machine Learning

MetaMT,a MetaLearning Method Leveraging Multiple Domain Data for Low …

Manipulating training data leads to robust neural models for MT.
Dec 11, 2019
Methodology
Machine Learning

Integrative Generalized Convex Clustering Optimization and Feature …

In mixed multi-view data, multiple sets of diverse features are measured on the same set of samples. By integrating all available data sources, we se…
Dec 11, 2019
Computer Vision
Machine Learning
Robotics

Self-Driving Car Steering Angle Prediction Based on Image Recognition

Self-driving vehicles have expanded dramatically over the last few years. Udacity has release a dataset containing, among other data, a set of images…
Dec 11, 2019
Machine Learning

Just Add Functions: A Neural-Symbolic Language Model

Neural network language models (NNLMs) have achieved ever-improving accuracy due to more sophisticated architectures and increasing amounts of traini…
Dec 11, 2019
Artificial Intelligence

UCT-ADP Progressive Bias Algorithm for Solving Gomoku

We combine Adaptive Dynamic Programming (ADP), a reinforcement learning method and UCB applied to trees (UCT) algorithm with a more powerful heuristi…
Dec 11, 2019
Computer Vision

Training Deep SLAM on Single Frames

Learning-based visual odometry and SLAM methods demonstrate a steady improvement over past years. However, collecting ground truth poses to train the…
Dec 11, 2019
Image and Video Processing
Computer Vision

U-Net with spatial pyramid pooling for drusen segmentation in optical…

The presence of drusen is the main hallmark of early/intermediate age-related macular degeneration (AMD). Therefore, automated drusen segmentation is…
Dec 11, 2019
Computer Vision
Machine Learning

Multimodal Self-Supervised Learning for Medical Image Analysis

In this paper, we propose a self-supervised learning approach that leverages multiple imaging modalities to increase data efficiency for medical imag…
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