Modern dataset search platforms employ ML task-based utility metrics ins...
Heatmap-based methods have become the mainstream method for pose estimat...
The volume-wise labeling of 3D medical images is expertise-demanded and
...
In generative modeling, numerous successful approaches leverage a
low-di...
Long-tailed recognition with imbalanced class distribution naturally eme...
Graph neural networks (GNNs) have pioneered advancements in graph
repres...
Ranking model plays an essential role in e-commerce search and
recommend...
Medical image data are often limited due to the expensive acquisition an...
Large vision and language models, such as Contrastive Language-Image
Pre...
We propose a stochastic volatility model for time series of curves. It i...
Effectively extracting inter-frame motion and appearance information is
...
The security of artificial intelligence (AI) is an important research ar...
Existing graph contrastive learning (GCL) typically requires two forward...
Pre-trained BERT models have achieved impressive accuracy on natural lan...
Current state-of-the-art document retrieval solutions mainly follow an
i...
Programmatic Weak Supervision (PWS) aggregates the source votes of multi...
Graph contrastive learning (GCL) is the most representative and prevalen...
In this paper, we focus on the pattern reconfigurable multiple-input
mul...
Multi-functional and reconfigurable multiple-input multiple-output (MR-M...
Most fair machine learning methods either highly rely on the sensitive
i...
With the prevalence of deep learning based embedding approaches, recomme...
Active learning theories and methods have been extensively studied in
cl...
Most recent semantic segmentation methods adopt a U-Net framework with a...
In this paper, we identify and study an important problem of gradient it...
Graph neural networks (GNNs) have been shown with superior performance i...
Many data mining and analytical tasks rely on the abstraction of network...
Deep 3-dimensional (3D) Convolutional Network (ConvNet) has shown promis...