256 Result(s)
within
Yi**ang Chen
Algorithm Analysis and Problem Complexity
Artificial Intelligence
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Article
Open AccessFL-GUARD: A Holistic Framework for Run-Time Detection and Recovery of Negative Federated Learning
Federated learning (FL) is a promising approach for learning a model from data distributed on massive clients without exposing data privacy. It works effectively in the ideal federation where clients share hom...
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Chapter and Conference Paper
Analysis of Significant Cell Differences Between Cancer Patients and Healthy Individuals
At the end of 2019, a global outbreak of a new coronavirus ravaged the world, and to this day, many people’s bodies are still deeply affected by the virus. In order to find out if there is a correlation betwee...
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Chapter and Conference Paper
Ranking Enhanced Supervised Contrastive Learning for Regression
Supervised contrastive learning has shown promising results in image classification tasks where the representations are pulled together if they share same labels or otherwise pushed apart. Such dispersion proc...
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Chapter and Conference Paper
MHDF: Multi-source Heterogeneous Data Progressive Fusion for Fake News Detection
Social media platforms are inundated with an extensive volume of unverified information, most of which originates from heterogeneous data from a variety of diverse sources, spreading rapidly and widely, thereb...
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Article
Open AccessA Neural Inference of User Social Interest for Item Recommendation
User-generated content is daily produced in social media, as such user interest summarization is critical to distill salient information from massive information for recommendation tasks. While the interested ...
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Chapter and Conference Paper
AutoQ: An Automata-Based Quantum Circuit Verifier
We present a specification language and a fully automated tool named AutoQ for verifying quantum circuits symbolically. The tool implements the automata-based algorithm from [14] and extends it with the capabilit...
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Article
Open AccessDynamic Index Construction with Deep Reinforcement Learning
Thanks to the rapid advances in artificial intelligence, a brand new venue for database performance optimization is through deep neural networks and the reinforcement learning paradigm. Alongside the long lite...
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Chapter and Conference Paper
Interconnected Neural Linear Contextual Bandits with UCB Exploration
Contextual multi-armed bandit algorithms are widely used to solve online decision-making problems. However, traditional methods assume linear rewards and low dimensional contextual information, leading to high...
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Chapter and Conference Paper
Domain-Level Pairwise Semantic Interaction for Aspect-Based Sentiment Classification
Aspect-based sentiment classification (ABSC) is a very challenging subtask of sentiment analysis (SA) and suffers badly from the class-imbalance. Existing methods only process sentences independently, without ...
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Article
Open AccessSet-Based Adaptive Distributed Differential Evolution for Anonymity-Driven Database Fragmentation
By breaking sensitive associations between attributes, database fragmentation can protect the privacy of outsourced data storage. Database fragmentation algorithms need prior knowledge of sensitive association...
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Chapter and Conference Paper
A Multimodal Fusion Model Based on Hybrid Attention Mechanism for Gesture Recognition
Gesture recognition based on multimodal information plays a significant role in the field of human-computer interaction. In recent years, although many researchers devoted themselves to the related work in thi...
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Chapter and Conference Paper
Unsupervised Domain Adaptation for 3D Medical Image with High Efficiency
Domain adaptation is a fundamental problem in the 3D medical image process. The current methods mainly cut the 3D image into 2D slices and then use 2D CNN for processing, which may ignore the inter-slice infor...
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Chapter and Conference Paper
Towards Synthetic Multivariate Time Series Generation for Flare Forecasting
One of the limiting factors in training data-driven, rare-event prediction algorithms is the scarcity of the events of interest resulting in an extreme imbalance in the data. There have been many methods intro...
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Chapter and Conference Paper
Structure-Enhanced Graph Representation Learning for Link Prediction in Signed Networks
Link prediction in signed networks has attracted widespread attention from researchers recently. Existing studies usually learn a representation vector for each node, which is used for link prediction tasks, b...
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Chapter and Conference Paper
A Multi-task Kernel Learning Algorithm for Survival Analysis
Survival analysis aims to predict the occurring times of certain events of interest. Most existing methods for survival analysis either assume specific forms for the underlying stochastic processes or linear h...
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Chapter and Conference Paper
A Meta-path Based Graph Convolutional Network with Multi-scale Semantic Extractions for Heterogeneous Event Classification
Heterogeneous social events modeling in large and noisy data sources is an important task for applications such as international situation assessment and disaster relief. Accurate and interpretable classificat...
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Chapter and Conference Paper
Weak Supervision Network Embedding for Constrained Graph Learning
Constrained learning, a weakly supervised learning task, aims to incorporate domain constraints to learn models without requiring labels for each instance. Because weak supervision knowledge is useful and easy...
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Chapter and Conference Paper
An Editable k-Nearest Neighbor Classifier Based on Tissue-Like P Systems
In this paper, a new editable k-nearest neighbor classifier evolved by P systems is proposed, called Edit-kNN-P. A tissue-like P system consists of cell-membrance is designed as the computational framework. Th...
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Chapter and Conference Paper
Adaptive Graph Co-Attention Networks for Traffic Forecasting
Traffic forecasting has remained a challenging topic in the field of transportation, due to the time-varying traffic patterns and complicated spatial dependencies on road networks. To address such challenges, ...
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Chapter and Conference Paper
Path Planning of UAV-UGV Heterogeneous Robot System in Road Network
The previous research on path planning of the UAV-UGV heterogeneous robot system plan paths for both UAV and UGV without considering the UGV’s moving range or plan only the UAV’s path based on the given UGV’s ...
