Obtaining large pre-trained models that can be fine-tuned to new tasks w...
Correlation matrix visualization is essential for understanding the
rela...
Monotone missing data is a common problem in data analysis. However,
imp...
Orthogonal parameterization is a compelling solution to the vanishing
gr...
Transfer learning plays an essential role in Deep Learning, which can
re...
Missing data is common in datasets retrieved in various areas, such as
m...
Many models have been proposed for vision and language tasks, especially...
Diabetic Retinopathy (DR) is a leading cause of vision loss in the world...
Collecting large-scale medical datasets with fully annotated samples for...
Identifying the relevant variables for a classification model with corre...
Fisher Discriminant Analysis (FDA) is one of the essential tools for fea...
Many startups and companies worldwide have been using project management...
Recommender systems have been increasingly popular in entertainment and
...
The recommendation system plays a vital role in many areas, especially
a...
In recent years, the occurrence of falls has increased and has had
detri...
Stress is a complex issue with wide-ranging physical and psychological
i...
Generative Adversarial Networks (GANs) have emerged as useful generative...
There is a warning light for the loss of plant habitats worldwide that
e...
Accurate insect pest recognition is significant to protect the crop or t...
In this paper, we propose SPBERT, a transformer-based language model
pre...
The missing data problem has been broadly studied in the last few decade...
Conventional approaches to image-text retrieval mainly focus on indexing...
Existing skin attributes detection methods usually initialize with a
pre...
Until now, Coronavirus SARS-CoV-2 has caused more than 850,000 deaths an...
We develop an extension of the Knockoff Inference procedure, introduced ...
We study fast learning rates when the losses are not necessarily bounded...