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Oct 17, 2019
By luiz.gh
Computer Vision

Meta-learning for fast classifier adaptation to new users of Signatur…

Offline Handwritten Signature verification presents a challenging Pattern Recognition problem, where only knowledge of the positive class is availabl…
Oct 17, 2019
Machine Learning

Graph Embedding VAE: A Permutation Invariant Model of Graph Structure

Generative models of graph structure have applications in biology and social sciences. The state of the art is GraphRNN, which decomposes the graph g…
Oct 17, 2019
By neermat
Computer Vision

Video Person Re-Identification using Learned Clip Similarity Aggregat…

We address the challenging task of video-based person re-identification. Recent works have shown that splitting the video sequences into clips and th…
Oct 17, 2019
By ajayj
Computer Vision
Machine Learning
Robotics

Discrete Residual Flow for Probabilistic Pedestrian Behavior Predicti…

Self-driving vehicles plan around both static and dynamic objects, applying predictive models of behavior to estimate future locations of the objects…
Oct 17, 2019
Machine Learning
Statistics Theory

A Unified Framework for Tuning Hyperparameters in Clustering Problems

Selecting hyperparameters for unsupervised learning problems is difficult in general due to the lack of ground truth for validation. However, this is…
Oct 17, 2019
Machine Learning

Why bigger is not always better: on finite and infinite neural networ…

Recent work has shown that the outputs of convolutional neural networks become Gaussian process (GP) distributed when we take the number of channels …
Oct 17, 2019
Robotics
Systems and Control
Optimization and Control

Robust Planning and Control For Polygonal Environments via Linear P…

In this paper, we are concerned with the design of a set of controllers, on a cell decomposition of a polygonal environment through Linear Programmin…
Oct 17, 2019
Computation and Language
Machine Learning

In this paper, we conducted an empirical investigation of BERT activations as universal text embeddings. We show that sentence embeddings from BERT perform strongly on SentEval tasks, and combining embeddings from the top and bottom layers of BERT f…

Universal Text Representation from BERT: An Empirical Study

We present a systematic investigation of layer-wise BERT activations for general-purpose text representations to understand what linguistic informati…
Oct 17, 2019
By argusm
Robotics
Computer Vision
Machine Learning

Adaptive Curriculum Generation from Demonstrations for Sim-to-Real …

We propose Adaptive Curriculum Generation from Demonstrations (ACGD) for reinforcement learning in the presence of sparse rewards. Rather than design…
Oct 17, 2019
Methodology
Machine Learning

Ranking variables and interactions using predictive uncertainty measu…

For complex nonlinear supervised learning models, assessing the relevance of input variables or their interactions is not straightforward due to the …
Oct 17, 2019
Machine Learning

A Stochastic Variance Reduced Nesterov's Accelerated Quasi-Newton Met…

Recently algorithms incorporating second order curvature information have become popular in training neural networks. The Nesterov's Accelerated Quas…
Oct 17, 2019
Computation and Language

Cross-lingual Parsing with Polyglot Training and Multi-treebank Lea…

Cross-lingual dependency parsing involves transferring syntactic knowledge from one language to another. It is a crucial component for inducing depen…
Oct 17, 2019
Computation and Language

PLATO: Pre-trained Dialogue Generation Model with Discrete Latent V…

Pre-training models have been proved effective for a wide range of natural language processing tasks. Inspired by this, we propose a novel dialogue g…
Oct 17, 2019
By YShi30
Computation and Language
Machine Learning
Sound
Audio and Speech Processing

H-VECTORS: Utterance-level Speaker Embedding Using A Hierarchical A…

In this paper, a hierarchical attention network to generate utterance-level embeddings (H-vectors) for speaker identification is proposed. Since diff…
Oct 17, 2019
Information Retrieval
Computation and Language
Machine Learning

Keyphrase Extraction from Disaster-related Tweets

While keyphrase extraction has received considerable attention in recent years, relatively few studies exist on extracting keyphrases from social med…
Oct 17, 2019
Machine Learning
Computers and Society
Information Theory

An Information-Theoretic Perspective on the Relationship Between Fa…

Our goal is to understand the so-called trade-off between fairness and accuracy. In this work, using a tool from information theory called Chernoff i…
Oct 17, 2019
Computer Vision
Machine Learning

Can I teach a robot to replicate a line art

Line art is arguably one of the fundamental and versatile modes of expression. We propose a pipeline for a robot to look at a grayscale line art and …
Oct 17, 2019
Machine Learning

Effect of Superpixel Aggregation on Explanations in LIME -- A Case St…

End-to-end learning with deep neural networks, such as convolutional neural networks (CNNs), has been demonstrated to be very successful for differen…
Oct 17, 2019
Machine Learning

In this section, we illustrate the power of our method by comparing the dropping forward-backward greedy algorithm to stepwise algorithm and the intuitive forward-backward scheme mentioned in the 2 section on artificial and real data. We use Mallow’…

Dropping forward-backward algorithms for feature selection

In this era of big data, feature selection techniques, which have long been proven to simplify the model, makes the model more comprehensible, speed …
Oct 17, 2019
Machine Learning
Computational Physics

From Dark Matter to Galaxies with Convolutional Neural Networks

Cosmological simulations play an important role in the interpretation of astronomical data, in particular in comparing observed data to our theoretic…
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