Machine-learning (ML) based discretization has been developed to simulat...
Counterfactual explanations (CFEs) exemplify how to minimally modify a
f...
In sequential recommendation, multi-modal information (e.g., text or ima...
Click-Through Rate (CTR) prediction, crucial in applications like recomm...
With the widespread application of personalized online services,
click-t...
Deep learning technology has made great achievements in the field of ima...
Malware detection models based on deep learning have been widely used, b...
User Behavior Modeling (UBM) plays a critical role in user interest lear...
Semi-Lagrangian (SL) schemes are known as a major numerical tool for sol...
Recently decades have witnessed the empirical success of framing Knowled...
In this paper, we propose a Universal Defence based on Clustering and
Ce...
Crowdsourcing is a favorable computing paradigm for processing computer-...
To offer accurate and diverse recommendation services, recent methods us...
Compared with model-based control and optimization methods, reinforcemen...
This paper reviews the adaptive sparse grid discontinuous Galerkin (aSG-...
Sequential recommendation (SR) plays an important role in personalized
r...
Scoring a large number of candidates precisely in several milliseconds i...
In this paper, we propose a novel Local Macroscopic Conservative (LoMaC)...
Multi-types of behaviors (e.g., clicking, adding to cart, purchasing, et...
In this paper, we propose a novel Local Macroscopic Conservative (LoMaC)...
We propose a stealthy clean-label video backdoor attack against Deep Lea...
Federated learning (FL) has been recognized as a promising distributed
l...
This paper studies the joint device selection and power control scheme f...
Remote sensing semantic segmentation aims to assign automatically each p...
Most recommender systems optimize the model on observed interaction data...
Rotated object detection in aerial images is a meaningful yet challengin...
In this paper, we propose a conservative low rank tensor method to
appro...
Machine learning systems deployed in the wild are often trained on a sou...
Together with impressive advances touching every aspect of our society, ...
We propose a low-rank tensor approach to approximate linear transport an...
CTR prediction, which aims to estimate the probability that a user will ...
Early-stage plant density is an essential trait that determines the fate...
The Global Wheat Head Detection (GWHD) dataset was created in 2020 and h...
Data competitions have become a popular approach to crowdsource new data...
The separation assurance task will be extremely challenging for air traf...
We introduce a new attack against face verification systems based on Dee...
Click-through rate (CTR) estimation plays as a core function module in
v...
Because of the superior feature representation ability of deep learning,...
Interactive response time is important in analytical pipelines for users...
RGB-Infrared person re-identification (RGB-IR Re-ID) aims to match perso...
Commonsense knowledge is critical in human reading comprehension. While
...
Given the convenience of collecting information through online services,...
This paper develops a high order adaptive scheme for solving nonlinear
S...
In light of growing challenges in agriculture with ever growing food dem...
With the starting point that implicit human biases are reflected in the
...
We are interested in numerically solving the Hamilton-Jacobi (HJ) equati...
Modeling the sequential correlation of users' historical interactions is...
The recent COVID-19 pandemic, which was first detected in Wuhan, China, ...
In this paper, we propose a class of adaptive multiresolution (also call...
The 3rd Generation Partnership Project (3GPP) has defined based on the L...