108 Result(s)
within
Zhigang **
Artificial Intelligence
Data Mining and Knowledge Discovery
-
Article
Masked self-supervised ECG representation learning via multiview information bottleneck
In recent years, self-supervised learning-based models have been widely used for electrocardiogram (ECG) representation learning. However, most of the models utilize contrastive learning that strongly depend o...
-
Article
Novel fixed-time stability criteria of nonlinear systems and applications in fuzzy competitive neural network and Chua’s oscillator
Since the fixed-time stability forms of nonlinear systems satisfy strict conditions, there are few general forms for nonlinear systems to achieve fixed-time stability. This work proposes a new class of more ge...
-
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...
-
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 ...
-
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...
-
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...
-
Article
Heterogeneous information network embedding for user behavior analysis on social media
User behavior prediction with low-dimensional vectors generated by user network embedding models has been verified to be efficient and reliable in real applications. However, existing graph representation lear...
-
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...
-
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...
-
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. ...
-
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...
-
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...
-
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...
-
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...
-
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...
-
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 ...
-
Article
Stock closing price prediction based on sentiment analysis and LSTM
Stock market prediction has been identified as a very important practical problem in the economic field. However, the timely prediction of the market is generally regarded as one of the most challenging proble...
-
Article
Hybridizing grey wolf optimization with neural network algorithm for global numerical optimization problems
This paper proposes a novel hybrid algorithm, called grey wolf optimization with neural network algorithm (GNNA), for solving global numerical optimization problems. The core idea of GNNA is to make full use o...
-
Article
Quasi-synchronization of stochastic memristor-based neural networks with mixed delays and parameter mismatches
This paper is concerned with quasi-synchronization of stochastic memristor-based neural networks with mixed delays and parameter mismatches. Due to the parameter mismatches, mean-square exponential synchroniza...
-
Article
Sentiment analysis via semi-supervised learning: a model based on dynamic threshold and multi-classifiers
Sentiment analysis has become a very popular research topic, especially for retrieving valuable information from various online environments. Most existing sentiment studies are based on supervised learning, w...
