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Robust load-balanced backbone-based multicast routing in mobile opportunistic networks
Mobile opportunistic network (MON) is an efficient way of communication when there is no persistent connection between nodes. Multicast in MONs can be used to efficiently deliver messages to multiple destination nodes. However, because multiple ...
Universal tweakable Even-Mansour cipher and its applications
The construction of the tweakable Even-Mansour cipher is in fact the designs of permutations, mask operations, and masking functions. For information-theoretic security, permutations are usually taken as random permutations. This paper focuses on ...
Rumor detection with self-supervised learning on texts and social graph
Rumor detection has become an emerging and active research field in recent years. At the core is to model the rumor characteristics inherent in rich information, such as propagation patterns in social network and semantic patterns in post content, ...
Active label distribution learning via kernel maximum mean discrepancy
Label distribution learning (LDL) is a new learning paradigm to deal with label ambiguity and many researches have achieved the prominent performances. Compared with traditional supervised learning scenarios, the annotation with label distribution ...
Differential privacy histogram publishing method based on dynamic sliding window
Differential privacy has recently become a widely recognized strict privacy protection model of data release. Differential privacy histogram publishing can directly show the statistical data distribution under the premise of ensuring user privacy ...
swSpAMM: optimizing large-scale sparse approximate matrix multiplication on Sunway Taihulight
Although matrix multiplication plays an essential role in a wide range of applications, previous works only focus on optimizing dense or sparse matrix multiplications. The Sparse Approximate Matrix Multiply (SpAMM) is an algorithm to accelerate ...
An improved master-apprentice evolutionary algorithm for minimum independent dominating set problem
The minimum independent dominance set (MIDS) problem is an important version of the dominating set with some other applications. In this work, we present an improved master-apprentice evolutionary algorithm for solving the MIDS problem based on a ...
MAML2: meta reinforcement learning via meta-learning for task categories
Meta-learning has been widely applied to solving few-shot reinforcement learning problems, where we hope to obtain an agent that can learn quickly in a new task. However, these algorithms often ignore some isolated tasks in pursuit of the average ...
An efficient deep learning-assisted person re-identification solution for intelligent video surveillance in smart cities
Innovations on the Internet of Everything (IoE) enabled systems are driving a change in the settings where we interact in smart units, recognized globally as smart city environments. However, intelligent video-surveillance systems are critical to ...
ARCosmetics: a real-time augmented reality cosmetics try-on system
A virtual cosmetics try-on system provides a realistic try-on experience for consumers and helps them efficiently choose suitable cosmetics. In this article, we propose a real-time augmented reality virtual cosmetics try-on system for smartphones (...
A blockchain-based framework for data quality in edge-computing-enabled crowdsensing
With the rapid development of mobile technology and smart devices, crowdsensing has shown its large potential to collect massive data. Considering the limitation of calculation power, edge computing is introduced to release unnecessary data ...
Software approaches for resilience of high performance computing systems: a survey
With the scaling up of high-performance computing systems in recent years, their reliability has been descending continuously. Therefore, system resilience has been regarded as one of the critical challenges for large-scale HPC systems. Various ...
Domain-specific feature elimination: multi-source domain adaptation for image classification
Multi-source domain adaptation utilizes multiple source domains to learn the knowledge and transfers it to an unlabeled target domain. To address the problem, most of the existing methods aim to minimize the domain shift by auxiliary distribution ...
D-Cubicle: boosting data transfer dynamically for large-scale analytical queries in single-GPU systems
In analytical queries, a number of important operators like JOIN and GROUP BY are suitable for parallelization, and GPU is an ideal accelerator considering its power of parallel computing. However, when data size increases to hundreds of gigabytes,...
On the parameterized complexity of minimum/maximum degree vertex deletion on several special graphs
In the minimum degree vertex deletion problem, we are given a graph, a distinguished vertex in the graph, and an integer κ, and the question is whether we can delete at most κ vertices from the graph so that the distinguished vertex has the unique ...
Zero-correlation linear attack on reduced-round SKINNY
At ToSC 2019, Ankele et al. proposed a novel idea for constructing zero-correlation linear distinguishers in a related-tweakey model. This paper further clarifies this principle and gives a search model for zero-correlation distinguishers. As a ...