Recent Multimodal Large Language Models (MLLMs) are remarkable in
vision...
In this paper, we propose projected gradient descent (PGD) algorithms fo...
We are witnessing a heightened surge in remote privacy attacks on laptop...
Since 2016, we have witnessed the tremendous growth of artificial
intell...
In this paper, we study the problem of principal component analysis with...
Smartphone motion sensors provide a concealed mechanism for eavesdroppin...
In 1-bit compressive sensing, each measurement is quantized to a single ...
Rotating object detection has wide applications in aerial photographs, r...
A large labeled dataset is a key to the success of supervised deep learn...
With the advent of the Internet of Things (IoT), establishing a secure
c...
Learning disentangled representations leads to interpretable models and
...
Software behavioral models have proven useful for emulating and testing
...
This paper studies the issues about tensors. Three typical kinds of tens...
The resolution of GPS measurements, especially in urban areas, is
insuff...
Approximate inference in probability models is a fundamental task in mac...
Gradient-based approximate inference methods, such as Stein variational
...
With the Single-Instance Multi-Tenancy (SIMT) model for composite
Softwa...
In a multi-tenant service network, multiple virtual service networks (VS...
The electronic calendar is a valuable resource nowadays for managing our...
Robust and fast ego-motion estimation is a critical problem for autonomo...
The proliferation of surveillance cameras has greatly improved the physi...
In the era of Web of Things and Services, Context-aware Web Services (CA...
Mobile phones can record individual's daily behavioral data as a time-se...
We propose a variational inference approach to deep probabilistic video
...
Stein variational gradient decent (SVGD) has been shown to be a powerful...
With many large science equipment constructing and putting into use,
ast...
Mobile phone log data (e.g., phone call log) is not static as it is
prog...
The presence of noisy instances in mobile phone data is a fundamental is...
We propose a novel adaptive importance sampling algorithm which incorpor...
In distributed, or privacy-preserving learning, we are often given a set...