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Oct 21, 2019
Computation and Language
Machine Learning

Building Dynamic Knowledge Graphs from Text-based Games

We are interested in learning how to update Knowledge Graphs (KG) from text. In this preliminary work, we propose a novel Sequence-to-Sequence (Seq2S…
Oct 21, 2019
Optimization and Control
Machine Learning
Numerical Analysis

Adaptive gradient descent without descent

We present a strikingly simple proof that two rules are sufficient to automate gradient descent: 1) don't increase the stepsize too fast and 2) don't…
Oct 21, 2019
Computer Vision

Cascaded Generation of High-quality Color Visible Face Images from …

Generating visible-like face images from thermal images is essential to perform manual and automatic cross-spectrum face recognition. We successfully…
Oct 21, 2019
Audio and Speech Processing
Machine Learning

Comparative Study between Adversarial Networks and Classical Techniqu…

Speech enhancement is a crucial task for several applications. Among the most explored techniques are the Wiener filter and the LogMMSE, but approach…
Oct 21, 2019
Multiagent Systems
Artificial Intelligence
Machine Learning

Multi-agent Hierarchical Reinforcement Learning with Dynamic Terminat…

In a multi-agent system, an agent's optimal policy will typically depend on the policies chosen by others. Therefore, a key issue in multi-agent syst…
Oct 21, 2019
Image and Video Processing
Computer Vision
Signal Processing

Spectral Characterization of functional MRI data on voxel-resolution …

The human cortical layer exhibits a convoluted morphology that is unique to each individual. Conventional volumetric fMRI processing schemes take for…
Oct 21, 2019
Machine Learning
Computer Vision

Multi-Resolution Weak Supervision for Sequential Data

Since manually labeling training data is slow and expensive, recent industrial and scientific research efforts have turned to weaker or noisier forms…
Oct 21, 2019
Statistical Finance
Machine Learning

CorrGAN: Sampling Realistic Financial Correlation Matrices Using Ge…

We propose a novel approach for sampling realistic financial correlation matrices. This approach is based on generative adversarial networks. Experim…
Oct 21, 2019
Methodology
Machine Learning
Statistics Theory

Generalized tensor regression with covariates on multiple modes

We consider the problem of tensor-response regression given covariates on multiple modes. Such data problems arise frequently in applications such as…
Oct 21, 2019
Neural and Evolutionary Computation
Computer Vision
Machine Learning
Neurons and Cognition

S4NN: temporal backpropagation for spiking neural networks with one …

We propose a new supervised learning rule for multilayer spiking neural networks (SNN) that use a form of temporal coding known as rank-order-coding.…
Oct 21, 2019
Optimization and Control
Computer Vision

Relative Interior Rule in Block-Coordinate Minimization

(Block-)coordinate minimization is an iterative optimization method which in every iteration finds a global minimum of the objective over a variable …
Oct 21, 2019
Probability
Machine Learning

Sampling random graph homomorphisms and applications to network data …

A graph homomorphism is a map between two graphs that preserves adjacency relations. We consider the problem of sampling a random graph homomorphism …
Oct 21, 2019
Human-Computer Interaction
Machine Learning

Toward automatic comparison of visualization techniques: Application …

Many end-user evaluations of data visualization techniques have been run during the last decades. Their results are cornerstones to build efficient v…
Oct 21, 2019
By 7D
Artificial Intelligence
Machine Learning
Logic in Computer Science

A Logic-Based Framework Leveraging Neural Networks for Studying the …

Deductive formalisms have been strongly developed in recent years; among them, Answer Set Programming (ASP) gained some momentum, and has been lately…
Oct 21, 2019
Robotics
Machine Learning

Modelling Generalized Forces with Reinforcement Learning for Sim-to-R…

Learning robotic control policies in the real world gives rise to challenges in data efficiency, safety, and controlling the initial condition of the…
Oct 21, 2019
Robotics
Computer Vision

Self-Supervised Sim-to-Real Adaptation for Visual Robotic Manipulation

Collecting and automatically obtaining reward signals from real robotic visual data for the purposes of training reinforcement learning algorithms ca…
Oct 21, 2019
Computer Vision
Machine Learning
Image and Video Processing

Object landmark discovery through unsupervised adaptation

This paper proposes a method to ease the unsupervised learning of object landmark detectors. Similarly to previous methods, our approach is fully uns…
Oct 21, 2019
Machine Learning

Learning to Learn by Zeroth-Order Oracle

In the learning to learn (L2L) framework, we cast the design of optimization algorithms as a machine learning problem and use deep neural networks to…
Oct 21, 2019
Computer Vision
Machine Learning

Improving Vehicle Re-Identification using CNN Latent Spaces: Metrics …

This paper addresses the problem of vehicle re-identification using distance comparison of images in CNN latent spaces. First, we study the impact of…
Oct 21, 2019
By eyke
Machine Learning

Aleatoric and Epistemic Uncertainty in Machine Learning: A Tutorial …

The notion of uncertainty is of major importance in machine learning and constitutes a key element of machine learning methodology. In line with the …
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