Graph anomaly detection (GAD) has attracted increasing attention in mach...
Anchor-based multi-view graph clustering (AMVGC) has received abundant
a...
Large language models (LLMs) demonstrate remarkable ability to comprehen...
In this work, we consider the Fokker-Planck equation of the Nonlinear No...
Graph anomaly detection (GAD) is a vital task in graph-based machine lea...
Neural machine translation (NMT) is often criticized for failures that h...
Graph Convolutional Neural Network (GCNN) is a popular class of deep lea...
We introduce a multi-tasking graph convolutional neural network, HydraGN...
In the inter-domain network, a route leak occurs when a routing announce...
Quantum key distribution (QKD) gradually has become a crucial element of...
We propose a novel prediction interval method to learn prediction mean
v...
This paper presents GearV, a two-gear lightweight hypervisor architectur...
Multi-view clustering (MVC) has been extensively studied to collect mult...
Multi-view clustering is an important yet challenging task in machine
le...
Many document-level neural machine translation (NMT) systems have explor...
Inspired by the strong correlation between the Label Smoothing
Regulariz...
The resolution of GPS measurements, especially in urban areas, is
insuff...
Document-level machine translation incorporates inter-sentential depende...
Multi-modal machine translation aims at translating the source sentence ...
Active Learning methods create an optimized and labeled training set fro...
Recent advances in sequence modeling have highlighted the strengths of t...
Voxel-based analysis methods localize brain structural differences by
pe...