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Learning outside the Black-Box: The pursuit of interpretable models
JonathanCrabbé, YaoZhang, WilliamZame....
Published date-11/17/2020
Machine Learning has proved its ability to produce accurate models but the deployment of these models outside the machine learning community has been hindered by the difficulties of interpreting these …
EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network
NeerajWagh, YogatheesanVaratharajah....
Published date-11/17/2020
EEG
This paper presents a novel graph convolutional neural network (GCNN)-based approach for improving the diagnosis of neurological diseases using scalp-electroencephalograms (EEGs). Although EEG is one of the main tests used …
Dual-stream Multiple Instance Learning Network for Whole Slide Image Classification with Self-supervised Contrastive Learning
BinLi, YinLi, KevinW.Eliceiri....
Published date-11/17/2020
ContrastiveLearning, ImageClassification, MultipleInstanceLearning, wholeslideimages
Whole slide images (WSIs) have large resolutions and usually lack localized annotations. WSI classification can be cast as a multiple instance learning (MIL) problem when only slide-level labels are available. …
Confounding Feature Acquisition for Causal Effect Estimation
ShirlyWang, SeungEunYi, ShalmaliJoshi....
Published date-11/17/2020
CausalInference
Reliable treatment effect estimation from observational data depends on the availability of all confounding information. While much work has targeted treatment effect estimation from observational data, there is relatively little …
SRF-GAN: Super-Resolved Feature GAN for Multi-Scale Representation
Seong-HoLee, Seung-HwanBae....
Published date-11/17/2020
Recent convolutional object detectors exploit multi-scale feature representations added with top-down pathway in order to detect objects at different scales and learn stronger semantic feature responses. In general, during the …
ZORB: A Derivative-Free Backpropagation Algorithm for Neural Networks
VarunRanganathan, AlexLewandowski....
Published date-11/17/2020
Gradient descent and backpropagation have enabled neural networks to achieve remarkable results in many real-world applications. Despite ongoing success, training a neural network with gradient descent can be a slow …