Deep neural networks have been well-known for their superb performance i...
Model complexity is a fundamental problem in deep learning. In this pape...
Stock trend forecasting, aiming at predicting the stock future trends, i...
The US Food and Drug Administration (FDA) has been actively promoting th...
Multi-agent reinforcement learning (MARL) has been increasingly explored...
Stock trend forecasting has become a popular research direction that att...
Semantic code search, which aims to retrieve code snippets relevant to a...
Imbalanced learning (IL), i.e., learning unbiased models from
class-imba...
Quantitative investment aims to maximize the return and minimize the ris...
Simultaneous neural machine translation (briefly, NMT) has attracted muc...
Machine teaching uses a meta/teacher model to guide the training of a st...
Dietary supplements (DSs) are popular but not always safe. Consumers usu...
It is fundamental to measure model complexity of deep neural networks. T...
Pre-trained contextual representations (e.g., BERT) have become the
foun...
High-resolution digital images are usually downscaled to fit various dis...
Distributional Reinforcement Learning (RL) differs from traditional RL i...
Cardiotoxicity related to cancer therapies has become a serious issue,
d...
Many real-world applications reveal difficulties in learning classifiers...
Many real-world applications reveal difficulties in learning classifiers...
Multiclass decomposition splits a multiclass classification problem into...
Model compression has become necessary when applying neural networks (NN...
Objectives To test the feasibility of using Twitter data to assess
deter...
Existing trials had not taken enough consideration of their population
r...
Despite the high consumption of dietary supplements (DS), there are not ...
Among American women, the rate of breast cancer is only second to lung
c...
Predicting the risk of mortality for patients with acute myocardial
infa...
Most existing event extraction (EE) methods merely extract event argumen...
Resource balancing within complex transportation networks is one of the ...
Heart disease remains the leading cause of death in the United States.
C...
This paper comprehensively surveys the development of trajectory cluster...
Surveillance is essential for the safety of power substation. The detect...
Many supervised learning tasks are emerged in dual forms, e.g.,
English-...
Machine learning is essentially the sciences of playing with data. An
ad...
Parallelization framework has become a necessity to speed up the trainin...
Click prediction is one of the fundamental problems in sponsored search....
Automatic image annotation (AIA) raises tremendous challenges to machine...