Given a set P of n points and a set S of m disks in the plane, the
disk ...
Rate-splitting multiple access (RSMA) uplink requires optimization of
de...
The federated learning (FL) paradigm emerges to preserve data privacy du...
Data imbalance is easily found in annotated data when the observations o...
Given a set P of n weighted points and a set S of m disks in the
plane, ...
Graph property prediction tasks are important and numerous. While each t...
Recently, Transformer-based architectures have been explored for speaker...
Unlike traditional distributed machine learning, federated learning stor...
Semantic segmentation of UAV aerial remote sensing images provides a mor...
In this report, we describe our submitted system for track 2 of the VoxC...
3D human pose estimation from a monocular video has recently seen signif...
Recommender systems employ machine learning models to learn from histori...
GSM-R is predicted to be obsoleted by 2030, and a suitable successor is
...
Rationale is defined as a subset of input features that best explains or...
Recently, self-supervised learning (SSL) has demonstrated strong perform...
Data augmentation has recently seen increased interest in graph machine
...
Learning to predict missing links is important for many graph-based
appl...
Oblivious RAM (ORAM) protected access pattern is essential for secure NV...
This paper describes the Microsoft speaker diarization system for monaur...
How about converting Taylor series to a network to solve the black-box n...
There are two famous function decomposition methods in math: 1) Taylor S...
The knowledge of the intuitive link between muscle activity and the fing...
Although the success of artificial neural networks (ANNs), there is stil...
Nearest neighbor (NN) problem is an important scientific problem. The NN...
TSP (Traveling Salesman Problem), a classic NP-complete problem in
combi...
Non-orthogonal multiple access (NOMA) is a promising radio access techno...
As an indicator of human attention gaze is a subtle behavioral cue which...
Non-invasive gaze estimation methods usually regress gaze directions dir...
Inertial navigation and attitude initialization in polar areas become a ...
Attention-based end-to-end (E2E) speech recognition models such as Liste...
Employing voice-based emotion recognition function in artificial intelli...
Long short-term memory (LSTM) is normally used in recurrent neural netwo...
Besides the text content, documents and their associated words usually c...
The segmentation of synthetic aperture radar (SAR) images is a longstand...
The least-square regression problems or inverse problems have been widel...
The total variation (TV) regularization method is an effective method fo...