Representation learning has been evolving from traditional supervised
tr...
Sequential recommendation requires understanding the dynamic patterns of...
Domain generalization is critical for real-world applications of machine...
Sequential recommendation aims to model dynamic user behavior from histo...
In our digital universe nowadays, enormous amount of data are produced i...
Understanding the customers' high level shopping intent, such as their d...
Multimodal magnetic resonance imaging (MRI) can reveal different pattern...
Numerical vector aggregation plays a crucial role in privacy-sensitive
a...
Local Differential Privacy (LDP) is now widely adopted in large-scale sy...
Automated Exploit Generation (AEG) is a well-known difficult task, espec...
Histopathology images are gigapixel-sized and include features and
infor...
Knowledge distillation has emerged as a scalable and effective way for
p...
Customized keyword spotting (KWS) has great potential to be deployed on ...
Directed greybox fuzzing (DGF) can quickly discover or reproduce bugs in...
Industrial recommender systems usually hold data from multiple business
...
Visual-based target tracking is easily influenced by multiple factors, s...
Sequential recommendation aims to model dynamic user behavior from histo...
This paper studies the item-to-item recommendation problem in recommende...
Electronic Health Records (EHRs) are a valuable asset to facilitate clin...
A critical step in virtual dental treatment planning is to accurately
de...
Geometrical structures and the internal local region relationship, such ...
With the continuous extension of the Industrial Internet, cyber incident...
We introduce ApolloRL, an open platform for research in reinforcement
le...
The recent availability of electronic health records (EHRs) have provide...
In this paper, we propose Neural Points, a novel point cloud
representat...
End-to-end learning robotic manipulation with high data efficiency is on...
General Continual Learning (GCL) aims at learning from non independent a...
In this paper, we develop a novel method for fast geodesic distance quer...
In this paper, we study endogeneity problems in algorithmic decision-mak...
Unsupervised deep learning has recently demonstrated the promise to prod...
Although significant progress in automatic learning of steganographic co...
Ethereum holds multiple billions of U.S. dollars in the form of Ether
cr...
Recently, the witness of the rapidly growing popularity of short videos ...
In the standard data analysis framework, data is first collected (once f...
Matching module plays a critical role in display advertising systems. Wi...
This paper proposes an iterative generative model for solving the automa...
Optical communication is developing rapidly in the directions of hardwar...
For e-commerce platforms such as Taobao and Amazon, advertisers play an
...
Bipartite b-matching is fundamental in algorithm design, and has been wi...
This letter presents a fast reinforcement learning algorithm for anti-ja...
Database platform-as-a-service (dbPaaS) is developing rapidly and a larg...
No-reference image quality assessment (NR-IQA) has received increasing
a...
The recurrent geometric network (RGN), the first end-to-end differentiab...
The conventional speaker recognition frameworks (e.g., the i-vector and
...
Adaptive moment methods have been remarkably successful in deep learning...
Adversarial machine learning is a fast growing research area, which cons...
Grasp is an essential skill for robots to interact with humans and the
e...
The Online Software, manager of the JUNO data acquisition (DAQ) system, ...
Coterm polynomials are introduced by Oztas et al. [a novel approach for
...
Zero-shot learning (ZSL) is a challenging task aiming at recognizing nov...