In-process compartmentalization and access control have been actively
ex...
Interactive Recommender Systems (IRSs) have attracted a lot of attention...
In this paper, we introduce ST-RAP, a novel Spatio-Temporal framework fo...
In Reinforcement Learning (RL), enhancing sample efficiency is crucial,
...
Recently, unsupervised representation learning (URL) has improved the sa...
Recently, deep learning-based methods have drawn huge attention due to t...
This paper presents a personalized character recommendation system for
M...
Recently, Reinforcement Learning (RL) has been actively researched in bo...
As machine learning (ML) technologies and applications are rapidly chang...
Demand for data-intensive workloads and confidential computing are the
p...
Successful sequential recommendation systems rely on accurately capturin...
Heap layout randomization renders a good portion of heap vulnerabilities...
The adoption of randomness against heap layout has rendered a good porti...
Modern applications are increasingly advanced and complex, and inevitabl...