Feature attributions based on the Shapley value are popular for explaining machine
learning models. However, their estimation is complex from both theoretical and …

Objective This work aims to provide a review of the existing literature in the field of
automated machine learning (AutoML) to help healthcare professionals better utilize …

In this paper, we question if self-supervised learning provides new properties to Vision
Transformer (ViT) that stand out compared to convolutional networks (convnets). Beyond the …

Deep learning's recent history has been one of achievement: from triumphing over humans
in the game of Go to world-leading performance in image classification, voice recognition …

The vast majority of successful deep neural networks are trained using variants of stochastic
gradient descent (SGD) algorithms. Recent attempts to improve SGD can be broadly …

Over the recent years, the growth of online social media has greatly facilitated the way
people communicate with each other. Users of online social media share information …

The field of machine translation faces an under-recognized problem because of
inconsistency in the reporting of scores from its dominant metric. Although people refer to" …

We investigate the training of sparse layers that use different parameters for different inputs
based on hashing in large Transformer models. Specifically, we modify the feedforward …

The field of machine translation (MT), the automatic translation of written text from one
natural language into another, has experienced a major paradigm shift in recent years …

As a promising machine learning tool to handle the accurate pattern recognition from
complex raw data, deep learning (DL) is becoming a powerful method to add intelligence to …