80 Result(s)
within
Chapter
Zhigang **
Artificial Intelligence
Data Mining and Knowledge Discovery
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Chapter and Conference Paper
Lazy Machine Unlearning Strategy for Random Forests
Removing the impact of some revoked training data from the machine learning models, i.e., machine unlearning, is a non-trivial task, which plays a pivotal role in fortifying the privacy and security of ML-base...
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Chapter and Conference Paper
Logit Distillation via Student Diversity
Knowledge distillation (KD) is a technique of transferring the knowledge from a large teacher network to a small student network. Current KD methods either make a student mimic diverse teachers with knowledge ...
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Chapter and Conference Paper
AAT: Non-local Networks for Sim-to-Real Adversarial Augmentation Transfer
In sim-to-real task, domain adaptation is one of the basic challenge topic as it can reduce the huge performance variation caused by domain shift. Domain adaptation can effectively transfer knowledge from a la...
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Chapter and Conference Paper
A Study of Electricity Theft Detection Method Based on Anomaly Transformer
Electricity theft not only disrupts normal electricity consumption but also poses a significant security threat to the power system. The widespread deployment of smart meters has led to the collection of massi...
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Chapter and Conference Paper
Spatial Data Publication Under Local Differential Privacy
Local differential privacy (LDP), which has been applied in Google Chrome and Apple iOS, provides strong privacy assurance to users when collecting data from users. We focus on the sensitive spatial data colle...
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Chapter and Conference Paper
Aligning Internal Regularity and External Influence of Multi-granularity for Temporal Knowledge Graph Embedding
Representation learning for the Temporal Knowledge Graphs (TKGs) is an emerging topic in the knowledge reasoning community. Existing methods consider the internal and external influence at either element level...
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Chapter and Conference Paper
A Data Dimensionality Reduction Method Based on mRMR and Genetic Algorithm for High-Dimensional Small Sample Data
With the development of microarray sequencing technology, researchers can obtain expression data of a large number of genes or proteins from patients at one time for analysis of biomarkers that cause disease. ...
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Chapter and Conference Paper
Hierarchical Multi-granulation Sequential Three-Way Decisions
In granular computing, a single conditional attribute is usually used as a view to describe the target concept, and each view can choose a specific level of granularity to describe the object in the hierarchic...
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Chapter and Conference Paper
Towards Nested and Fine-Grained Open Information Extraction
Open Information Extraction is a crucial task in natural language processing with wide applications. Existing efforts only work on extracting simple flat triplets that are not minimized, which neglect triplets...
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Chapter and Conference Paper
Document-Level Relation Extraction with Entity Enhancement and Context Refinement
Document-level Relation Extraction (DocRE) is the task of extracting relational facts mentioned in the entire document. Despite its popularity, there are still two major difficulties with this task: (i) How to...
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Chapter and Conference Paper
Multimodal Named Entity Recognition with Image Attributes and Image Knowledge
Multimodal named entity extraction is an emerging task which uses both textual and visual information to detect named entities and identify their entity types. The existing efforts are often flawed in two aspe...
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Chapter and Conference Paper
Teaching Reform and Research of Data Structure Course Based on BOPPPS Model and Rain Classroom
Data structure is the core course for computer science majors. How to improve their ‘computational thinking’ ability is crucial and challenging in this course. To optimize the teaching effect, a classroom teac...
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Chapter and Conference Paper
Research and Application of Clustering Algorithm in Battlefield Scheduling Genetic Optimization
Combat mission system is an organic combination of scheduling command system and collaborative control system. The integrity and reliability of the system not only depend on the optimal control algorithm used ...
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Chapter and Conference Paper
Improving Entity Linking with Graph Networks
Entity linking aims to assign a unique identity to entities mentioned in text given a predefined Knowledge Base. Previous works address this task based on the local or global features or the combination of the...
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Chapter and Conference Paper
Design of Intelligent Water Purification Control System for Small Waterworks Based on LSTM
This paper studies the application of intelligent drug control automatic water purification in tap water supply in remote areas. On the basis of LSTM technology, the solutions of control system, human-computer...
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Chapter and Conference Paper
A Convergent Differentially Private k-Means Clustering Algorithm
Preserving differential privacy (DP) for the iterative clustering algorithms has been extensively studied in the interactive and the non-interactive settings. However, existing interactive differentially priva...
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Chapter and Conference Paper
WebEL: Improving Entity Linking with Extra Web Contexts
Entity Linking is the task of determining the identity of textual entity mentions given a predefined Knowledge Graph (KG). Plenty of existing efforts have been made on this task using either “local” informatio...
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Chapter and Conference Paper
Multiple Interaction Attention Model for Open-World Knowledge Graph Completion
Knowledge Graph Completion (KGC) aims at complementing missing relationships between entities in a Knowledge Graph (KG). While closed-world KGC approaches utilizing the knowledge within KG could only complemen...
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Chapter and Conference Paper
Unsupervised Entity Alignment Using Attribute Triples and Relation Triples
Entity alignment aims to find entities referring to the same real-world object across different knowledge graphs (KGs). Most existing works utilize the relations between entities contained in the relation trip...
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Chapter and Conference Paper
Multi Step Prediction of Landslide Displacement Time Series Based on Extended Kalman Filter and Back Propagation Trough Time
Landslide is a complex geological natural disaster that brings harm or damage to human beings and their living environment. By strengthening landslide monitoring and forecasting technology, people can avoid or...
