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Algorithm Analysis and Problem Complexity
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Chapter and Conference Paper
Efficient Proactive Resource Allocation for Multi-stage Cloud-Native Microservices
Microservices deployment in the cloud often faces a prevalent challenge: how to maximize resource utilization while maintaining high quality-of-service (QoS). Existing automatic scaling tools frequently exhibi...
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Chapter and Conference Paper
Deep Learning for Journalism: The Bibliometric Analysis of Deep Learning for News Production in the Artificial Intelligence Era
This research aims to evaluate the articles published from 2018 to 2023. We focused on the deep learning issues that have risen in the last decade. Deep learning is the popular approach in news research, espec...
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Chapter and Conference Paper
Evidence of Increased Adaptation of Omicron SARS-CoV-2 Codons to Humans
Viruses are highly dependent on their hosts to carry out cellular mechanisms and cause productive infection. Thus, they undergo extensive adaptations to the host intracellular machinery, which occur over the e...
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Chapter and Conference Paper
Knowledge-Infused Optimization for Parameter Selection in Numerical Simulations
Many engineering applications rely on simulations based on partial differential equations. Different numerical schemes to approximate solutions exist. These schemes typically require setting parameters to appr...
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Chapter and Conference Paper
Approximating Spanning Tree Congestion on Graphs with Polylog Degree
Given a graph G and a spanning tree T of G, the congestion of an edge \(e\in E(T)\) e ...
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Chapter and Conference Paper
GraphSAGE-Based Spammer Detection Using Social Attribute Relationship
Spammers have existed since the birth of the Internet. They constantly pollute the social network environment, seriously degrade user experience and pose a threat to user account security. Finding spammers has...
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Chapter and Conference Paper
Beyond Universal Transformer: Block Reusing with Adaptor in Transformer for Automatic Speech Recognition
Recently, Transformer-based models have excelled in end-to-end (E2E) automatic speech recognition (ASR), enabling deployment on smart devices. However, their large parameter requirements pose challenges for AS...
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Chapter and Conference Paper
FCSO: Source Code Summarization by Fusing Multiple Code Features and Ensuring Self-consistency Output
Source code summarization is the process of generating a concise and generalized natural language summary from a given source code, which can facilitate software developers to comprehend and use the code bette...
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Chapter
Multimodal Optimization
This chapter will first introduce the definition of multimodal optimization. Next, most representative evolutionary multimodal optimization algorithms, which are also known as niching methods, will be introduc...
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Chapter and Conference Paper
SD-Attack: Targeted Spectral Attacks on Graphs
Graph learning (GL) models have been applied in various predictive tasks on graph data. But, similarly to other machine learning models, GL models are also vulnerable to adversarial attacks. As a powerful atta...
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Chapter and Conference Paper
Are Graph Embeddings the Panacea?
Graph representation learning has emerged as a machine learning go-to technique, outperforming traditional tabular view of data across many domains. Current surveys on graph representation learning predominant...
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Chapter and Conference Paper
False Negative Sample Aware Negative Sampling for Recommendation
Negative sampling plays a key role in implicit feedback collaborative filtering. It draws high-quality negative samples from a large number of uninteracted samples. Existing methods primarily focus on hard neg...
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Chapter and Conference Paper
SolGPT: A GPT-Based Static Vulnerability Detection Model for Enhancing Smart Contract Security
In this study, we present SolGPT, a novel approach to addressing the pivotal issue of detecting and mitigating vulnerabilities inherent in smart contracts, particularly those written in Solidity, the predomina...
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Chapter and Conference Paper
TripleS: A Subsidy-Supported Storage for Electricity with Self-financing Management System
In this paper, we propose a Subsidy-Supported Storage (also called TripleS) to assist grid management. Q-learning algorithms first determine the origin subsidies, and the proposed self-financing mechanism then...
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Chapter
Vehicular Indoor Localization and Tracking System
In this chapter, we implement a system prototype for vehicle localization and tracking in an indoor environment. First, we leverage ubiquitous wireless signals to realize fingerprinting localization. Then, we ...
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Chapter and Conference Paper
Abnormal Vibration Fault Diagnosis of Reducer Based on Bayesian Network
In order to recognize the fault type of reducer abnormal vibration and reduce the cost of inspection and maintenance, an intelligent diagnosis model is developed. In the case of insufficient historical abnorma...
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Chapter and Conference Paper
Text Extraction and Structuring of Standard Maintenance Documents for Metallurgical Continuous Casting Equipments
The large need of standard maintenance documents (SMD) for metallurgical continuous casting equipments brings a lot of repetitive, time-consuming and laborious work. Therefore through artificial intelligence a...
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Chapter and Conference Paper
DRL-Based Optimization Algorithm for Wireless Powered IoT Network
The extensive applications of Internet of Things (IoT) bring development and prosperity to multiple industries and greatly influent all aspects of human lives, which rely on the timely computation and communic...
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Chapter and Conference Paper
HAECN: Hierarchical Automatic ECN Tuning with Ultra-Low Overhead in Datacenter Networks
In modern datacenter networks (DCNs), mainstream congestion control (CC) mechanisms essentially rely on Explicit Congestion Notification (ECN) that is widely supported by commercial switches to reflect congest...
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Chapter and Conference Paper
Optimal Counterfactual Explanations for k-Nearest Neighbors Using Mathematical Optimization and Constraint Programming
Within the topic of explainable AI, counterfactual explanations to classifiers have received significant recent attention. We study counterfactual explanations that try to explain why a data point received an ...
