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Oct 18, 2019
Computation and Language
Computers and Society
Human-Computer Interaction
Machine Learning

Many Faces of Feature Importance: Comparing Built-in and Post-hoc F…

Feature importance is commonly used to explain machine predictions. While feature importance can be derived from a machine learning model with a vari…
Oct 18, 2019
Machine Learning
Methodology

Masked Gradient-Based Causal Structure Learning

Learning causal graphical models based on directed acyclic graphs is an important task in causal discovery and causal inference. We consider a genera…
Oct 18, 2019
Artificial Intelligence
Optimization and Control

A flexible integer linear programming formulation for scheduling cl…

Scheduling of personnel in a hospital environment is vital to improving the service provided to patients and balancing the workload assigned to clini…
Oct 18, 2019
By donini
Machine Learning

Scheduling the Learning Rate via Hypergradients: New Insights and a N…

We study the problem of fitting task-specific learning rate schedules from the perspective of hyperparameter optimization. This allows us to explicit…
Oct 18, 2019
Robotics
Computer Vision

Fast Local Planning and Mapping in Unknown Off-Road Terrain

In this paper, we present a fast, on-line mapping and planning solution for operation in unknown, off-road, environments. We combine obstacle detecti…
Oct 18, 2019
By samr
Machine Learning
Computer Vision

Texture Bias Of CNNs Limits Few-Shot Classification Performance

Accurate image classification given small amounts of labelled data (few-shot classification) remains an open problem in computer vision. In this work…
Oct 18, 2019
Machine Learning
Statistical Mechanics

Detecting multiple change-points in the time-varying Ising model

This work focuses on the estimation of change-points in a time-varying Ising graphical model (outputs $-1$ or $1$) evolving in a piecewise constant f…
Oct 18, 2019
Computational Geometry
Machine Learning

Adaptive Partitioning for Template Functions on Persistence Diagrams

As the field of Topological Data Analysis continues to show success in theory and in applications, there has been increasing interest in using tools …
Oct 18, 2019
By gyang
Computation and Language

Concept Pointer Network for Abstractive Summarization

A quality abstractive summary should not only copy salient source texts as summaries but should also tend to generate new conceptual words to express…
Oct 18, 2019
Computer Vision
Machine Learning

Understanding Deep Networks via Extremal Perturbations and Smooth Mas…

The problem of attribution is concerned with identifying the parts of an input that are responsible for a model's output. An important family of attr…
Oct 18, 2019
Machine Learning
Applications

Personalized Treatment for Coronary Artery Disease Patients: A Machin…

Current clinical practice guidelines for managing Coronary Artery Disease (CAD) account for general cardiovascular risk factors. However, they do not…
Oct 18, 2019
Machine Learning
Neural and Evolutionary Computation

On the Difficulty of Warm-Starting Neural Network Training

In many real-world deployments of machine learning systems, data arrive piecemeal. These learning scenarios may be passive, where data arrive increme…
Oct 18, 2019
Computer Vision
Graphics

Illumination-Based Data Augmentation for Robust Background Subtraction

A core challenge in background subtraction (BGS) is handling videos with sudden illumination changes in consecutive frames. In this paper, we tackle …
Oct 18, 2019
By ted
Machine Learning

First-Order Preconditioning via Hypergradient Descent

Standard gradient descent methods are susceptible to a range of issues that can impede training, such as high correlations and different scaling in p…
Oct 18, 2019
By zhanghw
Computer Vision

A novel centroid update approach for clustering-based superpixel meth…

Superpixel is widely used in image processing. And among the methods for superpixel generation, clustering-based methods have a high speed and a good…
Oct 18, 2019
By lorek
Machine Learning

Implicit Context-aware Learning and Discovery for Streaming Data An…

The performance of machine learning model can be further improved if contextual cues are provided as input along with base features that are directly…
Oct 18, 2019
By abordes
Computation and Language

Using Local Knowledge Graph Construction to Scale Seq2Seq Models to …

Query-based open-domain NLP tasks require information synthesis from long and diverse web results. Current approaches extractively select portions of…
Oct 18, 2019
By gally
Machine Learning
Optimization and Control
Applications

In this paper we have seen how model uncertainty can be identified by combining the optimal design of experiments approach with parameter identification. Optimal design of experiments can be used to choose sensors which allow the parameter identific…

Identification of Model Uncertainty via Optimal Design of Experiments…

In engineering applications almost all processes are described with the aid of models. Especially forming machines heavily rely on mathematical model…
Oct 18, 2019
Computation and Language
Audio and Speech Processing

In this paper, we experimentally showed that end-to-end approaches and different orthographic units were rather suitable to model the French language. RNN-transducer was found specially competitive with character units compared to other end-to-end a…

End-to-End Speech Recognition: A review for the French Language

Recently, end-to-end ASR based either on sequence-to-sequence networks or on the CTC objective function gained a lot of interest from the community, …
Oct 18, 2019
By hbilen
Computer Vision

Image Deconvolution with Deep Image and Kernel Priors

Image deconvolution is the process of recovering convolutional degraded images, which is always a hard inverse problem because of its mathematically …
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