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May 16, 2018
By mroueh
Machine Learning

We define below the Empirical Regularized Kernel Sobolev Discrepancy ^\pazocalSH,λ(^νp,^νq) for empirical measures ^νp,^νq. We then give generalization bounds, i.e finite sample bounds on its convergence convergence to the Expected Kernelized Sobo...

Regularized Finite Dimensional Kernel Sobolev Discrepancy

We show in this note that the Sobolev Discrepancy introduced in Mroueh et al in the context of generative adversarial networks, is actually the wei...
May 16, 2018
By yzhao83
Computer Vision
Spatial Transformer Introspective Neural Network

Spatial Transformer Introspective Neural Network

Natural images contain many variations such as illumination differences, affine transformations, and shape distortions. Correctly classifying these...
May 16, 2018
Machine Learning
Regularization Learning Networks

Regularization Learning Networks

Despite their impressive performance, Deep Neural Networks (DNNs) typically underperform Gradient Boosting Trees (GBTs) on many tabular-dataset lea...
May 16, 2018
Machine Learning
ChoiceNet: Robust Learning by Revealing Output Correlations

ChoiceNet: Robust Learning by Revealing Output Correlations

In this paper, we focus on the supervised learning problem with corrupted training data. We assume that the training dataset is generated from a mi...
May 16, 2018
Human-Computer Interaction
MOABB: Trustworthy algorithm benchmarking for BCIs

MOABB: Trustworthy algorithm benchmarking for BCIs

BCI algorithm development has long been hampered by two major issues: small sample sets and a lack of reproducibility. We offer a solution to both ...
May 16, 2018
Computation and Language
CASCADE: Contextual Sarcasm Detection in Online Discussion Forums

CASCADE: Contextual Sarcasm Detection in Online Discussion Forums

The literature in automated sarcasm detection has mainly focused on lexical, syntactic and semantic-level analysis of text. However, a sarcastic se...
May 16, 2018
Computer Vision
Deep Segmentation and Registration in X-Ray Angiography Video

Deep Segmentation and Registration in X-Ray Angiography Video

In interventional radiology, short video sequences of vein structure in motion are captured in order to help medical personnel identify vascular is...
May 16, 2018
Computer Vision
When Regression Meets Manifold Learning for Object Recognition and ...

When Regression Meets Manifold Learning for Object Recognition and ...

In this work, we propose a method for object recognition and pose estimation from depth images using convolutional neural networks. Previous method...
May 16, 2018
Machine Learning
Computer Vision
Neural Multi-scale Image Compression

Neural Multi-scale Image Compression

This study presents a new lossy image compression method that utilizes the multi-scale features of natural images. Our model consists of two networ...
May 16, 2018
Machine Learning
Progress & Compress: A scalable framework for continual learning

Progress & Compress: A scalable framework for continual learning

We introduce a conceptually simple and scalable framework for continual learning domains where tasks are learned sequentially. Our method is consta...
May 16, 2018
Artificial Intelligence

This work proposed and experimentally investigated two versions of a new VFDT-based algorithm, SVFDT-I and SVFDT-II. The SVFDTs were created to reduce the size of the trees induced by VFDT, inducing a memory conservative decision tree for data str...

Strict Very Fast Decision Tree: a memory conservative algorithm for...

Dealing with memory and time constraints are current challenges when learning from data streams with a massive amount of data. Many algorithms have...
May 16, 2018
By mehtar1
Computer Vision
Object detection at 200 Frames Per Second

Object detection at 200 Frames Per Second

In this paper, we propose an efficient and fast object detector which can process hundreds of frames per second. To achieve this goal we investigat...
May 16, 2018
By toshea
Machine Learning
Approximating the Void: Learning Stochastic Channel Models from O...

Approximating the Void: Learning Stochastic Channel Models from O...

Channel modeling is a critical topic when considering designing, learning, or evaluating the performance of any communications system. Prior work i...
May 16, 2018
By cm1074
Computer Vision
Robust 6D Object Pose Estimation with Stochastic Congruent Sets

Robust 6D Object Pose Estimation with Stochastic Congruent Sets

Object pose estimation is frequently achieved by first segmenting an RGB image and then, given depth data, registering the corresponding point clou...
May 16, 2018
Social and Information Networks
Personalized Next Point-of-Interest Recommendation via Latent Behav...

Personalized Next Point-of-Interest Recommendation via Latent Behav...

In this paper, we address the problem of personalized next Point-of-interest (POI) recommendation which has become an important and very challengin...
May 16, 2018
Machine Learning
Learning Graph Embeddings on Constant-Curvature Manifolds for Chang...

Learning Graph Embeddings on Constant-Curvature Manifolds for Chang...

The space of graphs is characterized by a non-trivial geometry, which often complicates performing inference in practical applications. A common ap...
May 16, 2018
Computation and Language
Artificial Intelligence
Machine Learning
A robust self-learning method for fully unsupervised cross-lingual ...

A robust self-learning method for fully unsupervised cross-lingual ...

Recent work has managed to learn cross-lingual word embeddings without parallel data by mapping monolingual embeddings to a shared space through ad...
May 16, 2018
By bothe
Computation and Language
Artificial Intelligence
Human-Computer Interaction
Neural and Evolutionary Computation
A Context-based Approach for Dialogue Act Recognition using Simple ...

A Context-based Approach for Dialogue Act Recognition using Simple ...

Dialogue act recognition is an important part of natural language understanding. We investigate the way dialogue act corpora are annotated and the ...
May 16, 2018
Machine Learning
Structured nonlinear variable selection

Structured nonlinear variable selection

We investigate structured sparsity methods for variable selection in regression problems where the target depends nonlinearly on the inputs. We foc...
May 16, 2018
Robotics
Artificial Intelligence
Learning Representations of Spatial Displacement through Sensorimot...

Learning Representations of Spatial Displacement through Sensorimot...

Robots act in their environment through sequences of continuous motor commands. Because of the dimensionality of the motor space, as well as the in...
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