3,636 Result(s)
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Chapter and Conference Paper
Distributional Kernel: An Effective and Efficient Means for Trajectory Retrieval
In this paper, we propose a new and powerful way to represent trajectories and measure the distance between them using a distributional kernel. Our method has two unique properties: (i) the identity property w...
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Chapter and Conference Paper
Joint Video Transcoding and Representation Selection for Edge-Assisted Multi-party Video Conferencing
Current cloud-based multi-party video conferencing suffers from heavy workloads on media servers caused by video transcoding. Emerging edge computing can assist in offloading transcoding tasks to edge nodes. H...
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Chapter and Conference Paper
APFL: Active-Passive Forgery Localization for Medical Images
Medical image forgery has become an urgent issue in academia and medicine. Unlike natural images, images in the medical field are so sensitive that even minor manipulation can produce severe consequences. Exis...
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Chapter and Conference Paper
Absorb: Deadlock Resolution for 2.5D Modular Chiplet Based Systems
With Moore’s Law slowing down, the development of SoCs has encountered a bottleneck. Integrating more functional units and larger on-chip storage leads to a dramatic increase in chip area, resulting in lower c...
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Chapter and Conference Paper
A Weighted Cross-Modal Feature Aggregation Network for Rumor Detection
In this paper, we propose a Weighted Cross-modal Aggregation network (WCAN) for rumor detection in order to combine highly correlated features in different modalities and obtain a unified representation in the...
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Chapter and Conference Paper
Carbon Trading Based on Consortium Chain: Building, Modeling, and Analysis
Traditional carbon trading suffers from poor interoperability, low transparency and reliance on manual drawbacks. In this paper, we analyze the combination of carbon trading and blockchain technology to design...
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Chapter and Conference Paper
SAWTab: Smoothed Adaptive Weighting for Tabular Data in Semi-supervised Learning
Self-supervised and Semi-supervised learning (SSL) on tabular data is an understudied topic. Despite some attempts, there are two major challenges: 1. Imbalanced nature in the tabular dataset; 2. The one-hot e...
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Chapter and Conference Paper
Improving Knowledge Tracing via Considering Students’ Interaction Patterns
Knowledge Tracing (KT), which aims to accurately identify students’ evolving mastery of different concepts during their learning process, is a popular task for providing intelligent tutoring in online learning...
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Chapter and Conference Paper
Optimizing the Parallelism of Communication and Computation in Distributed Training Platform
With the development of deep learning, DNN models have become more complex. Large-scale model parameters enhance the level of AI by improving the accuracy of DNN models. However, they also present more severe ...
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Chapter and Conference Paper
An Updatable Key Management Scheme for Underwater Wireless Sensor Networks
In recent years, underwater wireless sensor networks (UWSNs) have emerged as promising network model for various marine exploration, detection, and protection applications. The problems of frequent node moveme...
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Chapter and Conference Paper
Improving Anti-money Laundering via Fourier-Based Contrastive Learning
Anti-money laundering (AML) aims to detect money laundering from daily transactions, which is the key frontier of combating financial crimes. Previous deep-learning AML methods are not robust enough. To addres...
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Chapter and Conference Paper
CFDM-IME: A Collaborative Fault Diagnosis Method for Intelligent Manufacturing Equipment
The stability of the intelligent manufacturing industry will directly affect the development of the social economy. The privacy of data among different smart factories (SF) leads to a lack of generalization of...
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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
Test-and-Decode: A Partial Recovery Scheme for Verifiable Coded Computing
Coded computing has proven its efficiency in tolerating stragglers in distributed computing. Workers return the sub-computation results to the master after computing, and the master recovers the final computat...
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Chapter and Conference Paper
A Data-Driven Approach for Building a Cardiovascular Disease Risk Prediction System
Cardiovascular disease is a leading cause of mortality worldwide. The disease can develop without showing apparent symptoms at an early stage, making it difficult for domain experts to provide intervention. Us...
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Chapter and Conference Paper
Rethinking Personalized Federated Learning with Clustering-Based Dynamic Graph Propagation
Most existing personalized federated learning approaches are based on intricate designs, which often require complex implementation and tuning. In order to address this limitation, we propose a simple yet effe...
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Chapter and Conference Paper
Interpreting Pretrained Language Models via Concept Bottlenecks
Pretrained language models (PLMs) have made significant strides in various natural language processing tasks. However, the lack of interpretability due to their “black-box” nature poses challenges for responsi...
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Chapter and Conference Paper
A Novel Network Topology Sensing Method for Network Security Situation Awareness
In Network Security Situation Awareness (NSSA), topology information of the monitored network constitutes the foundation of the whole NSSA process. This paper presents a novel method for network topology sensi...
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Chapter and Conference Paper
Separation in Distributionally Robust Monopolist Problem
We consider a monopoly pricing problem, where a seller has multiple items to sell to a single buyer, only knowing the distribution of the buyer’s value profile. The seller’s goal is to maximize her expected re...
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Chapter and Conference Paper
Kernel Representation Learning with Dynamic Regime Discovery for Time Series Forecasting
Correlations between variables in complex ecosystems such as weather and financial markets lead to a great amount of dynamic and co-evolving time series data, posing a significant challenge to the current fore...