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Scaling down Deep Learning
SamGreydanus....
Published date-11/29/2020
Though deep learning models have taken on commercial and political relevance, many aspects of their training and operation remain poorly understood. This has sparked interest in "science of deep learning" …
Artificial Intelligence applied to chest X-Ray images for the automatic detection of COVID-19. A thoughtful evaluation approach
JulianD.Arias-Londoño, JorgeA.Gomez-Garcia, LaureanoMoro-Velazquez....
Published date-11/29/2020
COVID-19Diagnosis
Current standard protocols used in the clinic for diagnosing COVID-19 include molecular or antigen tests, generally complemented by a plain chest X-Ray. The combined analysis aims to reduce the significant …
A Targeted Universal Attack on Graph Convolutional Network
JiazhuDai, WeifengZhu, XiangfengLuo....
Published date-11/29/2020
AdversarialAttack
Graph-structured data exist in numerous applications in real life. As a state-of-the-art graph neural network, the graph convolutional network (GCN) plays an important role in processing graph-structured data. However, a …
Deeper or Wider Networks of Point Clouds with Self-attention?
HaoxiRan, LiLu....
Published date-11/29/2020
Prevalence of deeper networks driven by self-attention is in stark contrast to underexplored point-based methods. In this paper, we propose groupwise self-attention as the basic block to construct our network: …
Inflating Topic Relevance with Ideology: A Case Study of Political Ideology Bias in Social Topic Detection Models
MeiqiGuo, RebeccaHwa, Yu-RuLin....
Published date-11/29/2020
We investigate the impact of political ideology biases in training data. Through a set of comparison studies, we examine the propagation of biases in several widely-used NLP models and its …
Latent Template Induction with Gumbel-CRFs
YaoFu, ChuanqiTan, BinBi....
Published date-11/29/2020
Data-to-TextGeneration, ParaphraseGeneration, TextGeneration
Learning to control the structure of sentences is a challenging problem in text generation. Existing work either relies on simple deterministic approaches or RL-based hard structures. We explore the use …