Class imbalance is prevalent in real-world node classification tasks and...
Robust constrained formation tracking control of underactuated underwate...
This paper addresses distributed robust learning-based control for conse...
Graph or network data are widely studied in both data mining and
visuali...
Chest X-ray (CXR) anatomical abnormality detection aims at localizing an...
We study a class of reinforcement learning (RL) tasks where the objectiv...
This paper addresses the problem of data-driven model discrimination for...
We investigate multi-agent reinforcement learning for stochastic games w...
This paper investigated the distributed leader follower formation contro...
Surgery is the only viable treatment for cataract patients with visual a...
Learning linear temporal logic (LTL) formulas from examples labeled as
p...
Recently, deep neural networks have greatly advanced histopathology imag...
We consider the problem of explaining the temporal behavior of black-box...
Tracking control has been a vital research topic in robotics. This paper...
Deep learning-based melanoma classification with dermoscopic images has
...
Recently, deep-learning-based approaches have been widely studied for
de...
In the past decades, considerable attention has been paid to bio-inspire...
Consensus formation tracking of multiple autonomous underwater vehicles
...
Recently, deep neural networks have greatly advanced undersampled Magnet...
Graph Neural Networks (GNNs) have achieved tremendous success in a varie...
We study the problem of autonomous racing amongst teams composed of
coop...
We develop a hierarchical controller for multi-agent autonomous racing. ...
To date few studies have comprehensively compared medical image registra...
We develop a learning-based algorithm for the distributed formation cont...
Deep learning-based Multi-Task Classification (MTC) is widely used in
ap...
In multi-agent reinforcement learning (MARL), it is challenging for a
co...
Semi-supervised learning has substantially advanced medical image
segmen...
Extracting spatial-temporal knowledge from data is useful in many
applic...
In order to tackle the difficulty associated with the ill-posed nature o...
We develop a probabilistic control algorithm, , for swarms
of agents wit...
We develop a learning-based algorithm for the control of robotic systems...
Recent works on ride-sharing order dispatching have highlighted the
impo...
Manually segmenting the hepatic vessels from Computer Tomography (CT) is...
Temporal logic inference is the process of extracting formal description...
The past decades have witnessed the prosperity of graph mining, with a
m...
We address the problem of inferring descriptions of system behavior usin...
In this paper, we present a provably correct controller synthesis approa...
Pandemics can bring a range of devastating consequences to public health...
Multimodal image registration (MIR) is a fundamental procedure in many
i...
The loss function of an unsupervised multimodal image registration frame...
Multimodal deformable image registration is essential for many image-gui...
Nowadays, autonomous taxis become a highly promising transportation mode...
Deformable image registration between Computed Tomography (CT) images an...
We study the distributed synthesis of policies for multi-agent systems t...
We present a novel network pruning algorithm called Dynamic Sparse Train...
With the increasing availability of new image registration approaches, a...
Machine teaching is an algorithmic framework for teaching a target hypot...
In inverse reinforcement learning (IRL), given a Markov decision process...
We study the synthesis of policies for multi-agent systems to implement
...
In this paper, we present a controller synthesis approach for wind turbi...