Remote sensing images are essential for many earth science applications,...
The problem of phase retrieval (PR) involves recovering an unknown image...
Proximal gradient-based optimization is one of the most common strategie...
Breaking safety constraints in control systems can lead to potential ris...
Clustering continues to be a significant and challenging task. Recent st...
We present a robust and efficient method for simulating Lagrangian
solid...
Deep neural networks have strong capabilities of memorizing the underlyi...
Recent breakthroughs in Vision-Language (V L) joint research have achi...
Nowadays, differential privacy (DP) has become a well-accepted standard ...
CS is an efficient method to accelerate the acquisition of MR images fro...
The convergence of variable-step L1 scheme is studied for the time-fract...
Simulating stiff materials in applications where deformations are either...
The sparse representation of graphs has shown its great potential for
ac...
Performance of object detection models has been growing rapidly on two m...
Compressed sensing (CS) is an efficient method to reconstruct MR image f...
Deep neural networks (DNNs) could be very useful in blockchain applicati...
Given a graph G where each node is associated with a set of attributes, ...
This paper proposes a novel active boundary loss for semantic segmentati...
This paper proposes a novel location-aware deep learning-based single im...
Knowledge distillation has become an important technique for model
compr...
In this work, the performance of reconfigurable intelligent surface
(RIS...
While the superior performance of second-order optimization methods such...
In this letter, we consider a dual-hop cooperative network assisted by
m...
This paper presents LinSBFT, a Byzantine Fault Tolerance (BFT) protocol ...
We solve a challenging yet practically useful variant of 3D Bin Packing
...
Modern large-scale systems such as recommender system and online adverti...
Transformer-based models pre-trained on large-scale corpora achieve
stat...
Given a graph G and a node u in G, a single source SimRank query evaluat...
In recommender systems, the user-item interaction data is usually sparse...
Given a graph G, a source node s and a target node t, the personalized
P...
We present a computational design system that assists users to model,
op...
Local differential privacy (LDP) is a recently proposed privacy standard...
Given an input graph G and a node v in G, homogeneous network embedding ...
This paper presents LinBFT, a novel Byzantine fault tolerance (BFT) prot...
We present a novel spatial hashing based data structure to facilitate 3D...
DeepWarp is an efficient and highly re-usable deep neural network (DNN) ...
This article describes the development of a platform designed to visuali...
This article describes a contour-based 3D tongue deformation visualizati...
Differential privacy enables organizations to collect accurate aggregate...