Deep learning models have a risk of utilizing spurious clues to make
pre...
Machine learning (ML) based time series forecasting models often require...
In general-sum games, the interaction of self-interested learning agents...
Classical functional linear regression models the relationship between a...
This study investigates clustered federated learning (FL), one of the
fo...
NLP models are susceptible to learning spurious biases (i.e., bugs) that...
Benefiting from large-scale Pretrained Vision-Language Models (VL-PMs), ...
To automatically correct handwritten assignments, the traditional approa...
While various multi-agent reinforcement learning methods have been propo...
Neural language models' (NLMs') reasoning processes are notoriously hard...
Video Question Answering (VideoQA), aiming to correctly answer the given...
Background: Electronic Health Records (EHRs) contain rich information of...
Single-cell sequencing has a significant role to explore biological proc...
The Multi-Constraint Shortest Path (MCSP) problem aims to find the
short...
Deep convolutional neural networks (DCNN) aided high dynamic range (HDR)...
Weakly-supervised Temporal Action Localization (WS-TAL) methods learn to...
The object of Weakly-supervised Temporal Action Localization (WS-TAL) is...
Wide dynamic range (WDR) image tone mapping is in high demand in many
ap...
In this paper, we present a novel tone mapping algorithm that can be use...
Wide dynamic range (WDR) images contain more scene details and contrast ...
Currently, face detection approaches focus on facial information by vary...
The dynamic range of our normal life can exceeds 120 dB, however, the
sm...
Health departments have been deploying text classification systems for t...
Research in human action recognition has accelerated significantly since...