The excellent text-to-image synthesis capability of diffusion models has...
In real-world scenarios, typical visual recognition systems could fail u...
In cluster randomized experiments, units are often recruited after the r...
Out-of-distribution (OOD) detection plays a vital role in enhancing the
...
In recent years, metaverse and digital humans have become important rese...
Accurate 3D cardiac reconstruction from cine magnetic resonance imaging
...
Reliability is extremely important for large-scale cloud systems like
Mi...
Position bias, the phenomenon whereby users tend to focus on higher-rank...
The whole slide image (WSI) classification is often formulated as a mult...
Recently, ”pre-training and fine-tuning” has been adopted as a standard
...
In this paper, we introduce AdaSelection, an adaptive sub-sampling metho...
With the emergence of privacy leaks in federated learning, secure aggreg...
With the availability of large-scale, comprehensive, and general-purpose...
One of the grand enduring goals of AI is to create generalist agents tha...
Lifelong learning offers a promising paradigm of building a generalist a...
Comparative effectiveness research with randomized trials or observation...
The ability to automatically detect and track surgical instruments in
en...
Commonsense question answering (QA) research requires machines to answer...
Differential privacy (DP), as a rigorous mathematical definition quantif...
Large language models (LLMs) have demonstrated remarkable zero-shot
gene...
In this paper, we study multiple problems from sponsored product optimiz...
Post-treatment confounding is a common problem in causal inference, incl...
Online Social Network (OSN) has become a hotbed of fake news due to the ...
Scene text detection is a challenging computer vision task due to the hi...
Video-and-language understanding has a variety of applications in the
in...
Post-randomization events, also known as intercurrent events, such as
tr...
In-memory key-value stores (IMKVSes) serve many online applications beca...
Modern sociology has profoundly uncovered many convincing social criteri...
Computing is a critical driving force in the development of human
civili...
Visual entailment (VE) is to recognize whether the semantics of a hypoth...
Graph neural networks (GNNs) have been successfully applied to early mil...
As a booming research area in the past decade, deep learning technologie...
Deep reinforcement learning (RL) has brought many successes for autonomo...
Bilevel optimization (BO) is useful for solving a variety of important
m...
Goal-conditioned reinforcement learning (GCRL) has a wide range of poten...
Multiple object tracking (MOT) is an important technology in the field o...
There has been significant progress in developing reinforcement learning...
Multi-Label Image Classification (MLIC) approaches usually exploit label...
With the rapid development of mobile Internet and big data, a huge amoun...
Evolutionary algorithms are sensitive to the mutation rate (MR); no sing...
In zero-shot learning (ZSL) community, it is generally recognized that
t...
As intelligent agents become autonomous over longer periods of time, the...
Zero-shot learning (ZSL) aims to recognize objects from unseen classes, ...
Machine learning models are vulnerable to data inference attacks, such a...
In a model inversion attack, an adversary attempts to reconstruct the da...
With the rapid development of smart manufacturing, data-driven machinery...
With the rapid development of smart manufacturing, data-driven machinery...
Anomalous sound detection (ASD) is one of the most significant tasks of
...
Valves are widely used in industrial and domestic pipeline systems. Howe...
Aspect-based sentiment classification (ABSC) is a very challenging subta...