Sorting is fundamental and ubiquitous in modern computing systems. Hardw...
The recent work CLIPA presents an inverse scaling law for CLIP training ...
Graph contrastive learning (GCL), as a self-supervised learning method, ...
Recent advancements in text-to-image generation have enabled significant...
The high computational and memory requirements of generative large langu...
CLIP, the first foundation model that connects images and text, has enab...
Retrieving target information based on input query is of fundamental
imp...
Data series indexes are necessary for managing and analyzing the increas...
Scatterplots commonly use color to encode categorical data. However, as
...
Reliability updating refers to a problem that integrates Bayesian updati...
In recent years, camera-based 3D object detection has gained widespread
...
Image inpainting has achieved fundamental advances with deep learning.
H...
Adversarial training (AT) with samples generated by Fast Gradient Sign M...
This paper studies the potential of distilling knowledge from pre-traine...
For human children as well as machine learning systems, a key challenge ...
Nuclei Segmentation from histology images is a fundamental task in digit...
Sepsis is a leading cause of death in the ICU. It is a disease requiring...
The recent success of Vision Transformers is shaking the long dominance ...
We use deep distributional reinforcement learning (RL) to develop a hedg...
Language models increasingly rely on massive web dumps for diverse text ...
The maturity of structural health monitoring technology brings
ever-incr...
Retrieving target videos based on text descriptions is a task of great
p...
Softmax working with cross-entropy is widely used in classification, whi...
Plot-based Graphic API recommendation (Plot2API) is an unstudied but
mea...
Despite considerable progress, state of the art image captioning models
...
Large uncertainties in many phenomena of interest have challenged the
re...
As models in various fields are becoming more complex, associated
comput...
Computer vision models learn to perform a task by capturing relevant
sta...
Visual tracking problem demands to efficiently perform robust classifica...
In this paper, we present an end-to-end learning framework for detailed ...
Artificial neural networks (ANNs) have become the driving force behind r...
In today's blockchain system, designing a secure and high throughput on ...
Time-based media (videos, synthetic animations, and virtual reality
expe...