Dynamic searchable symmetric encryption (DSSE) enables a server to
effic...
Recent years have witnessed the remarkable performance of diffusion mode...
Machine learning models may inadvertently memorize sensitive, unauthoriz...
We propose a novel method, LoLep, which regresses Locally-Learned planes...
Rendering photorealistic and dynamically moving human heads is crucial f...
Numerous studies have underscored the significant privacy risks associat...
A computational workflow, also known as workflow, consists of tasks that...
Diffusion models have emerged as state-of-the-art deep generative
archit...
Biological studies reveal that neural circuits located at the spinal cor...
Reinforcement learning (RL) agents are known to be vulnerable to evasion...
The vulnerability in the algorithm supply chain of deep learning has imp...
Synthetic Aperture Radar (SAR) to electro-optical (EO) image translation...
Serial crystallography at X-ray free electron laser (XFEL) sources has
e...
This work presents an effective depth-consistency self-prompt Transforme...
Artificial intelligence (AI) has brought tremendous impacts on biomedica...
For deep ordinal classification, learning a well-structured feature spac...
With X-ray free-electron lasers (XFELs), it is possible to determine the...
We apply Fourier neural operators (FNOs), a state-of-the-art operator
le...
Intrinsic motivation is a promising exploration technique for solving
re...
The hippocampus plays a vital role in the diagnosis and treatment of man...
Clone detection is widely exploited for software vulnerability search. T...
Scaling model parameters usually improves model quality, but at the pric...
The "Right to be Forgotten" rule in machine learning (ML) practice enabl...
The well-known benefits of cloud computing have spurred the popularity o...
In recent years there has been growing popularity of leveraging cloud
co...
Vision Transformers (ViTs) have recently dominated a range of computer v...
The spread of COVID-19 has brought a huge disaster to the world, and the...
We propose an effective Structural Prior guided Generative Adversarial
T...
Information Bottleneck (IB) based multi-view learning provides an inform...
Three-dimensional (3D) object recognition is crucial for intelligent
aut...
Energy is an essential, but often forgotten aspect in large-scale federa...
Open intent classification is a practical yet challenging task in dialog...
In Machine Learning, the emergence of the right to be forgotten gave
bir...
The essence of quadrupeds' movements is the movement of the center of
gr...
Due to their ability to adapt to different terrains, quadruped robots ha...
Companies build separate training and inference GPU clusters for deep
le...
Single image deraining is an important and challenging task for some
dow...
Federated learning has recently emerged as a paradigm promising the bene...
Many real-world networks are inherently decentralized. For example, in s...
This paper provides a complexity analysis for the game of dark Chinese c...
Model-based reinforcement learning methods achieve significant sample
ef...
The distributed convex optimization problem over the multi-agent system ...
Outsourcing decision tree inference services to the cloud is highly
bene...
Adversarial attacks against commercial black-box speech platforms, inclu...
In differential Evolution (DE) algorithms, a crossover operation filteri...
We present a novel self-supervised algorithm named MotionHint for monocu...
In recent years, single image dehazing models (SIDM) based on atmospheri...
Explanation of AI, as well as fairness of algorithms' decisions and the
...
Transfer learning has become a common solution to address training data
...
Face authentication usually utilizes deep learning models to verify user...