Chen Wang

Feature Learning With a Divergence-Encouraging Autoencoder for Imbalanced Data Classification

2018 · IEEE Access

Imbalanced data exists commonly in machine learning classification applications. Popular classification algorithms are based on the assumption that data in different classes are roughly equally distributed; however, extremely skewed data, with instances from one class …

ML-Stealer: Stealing Prediction Functionality of Machine Learning Models with Mere Black-Box Access

2021 · 2021 IEEE 20th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

Machine Learning (ML) models are progressively deployed in many real-world applications to perform a wide range of tasks, but are exposed to the security and privacy threats which aim to infer the details and even …

A Lexicon Enhanced Chinese Long Named Entity Recognition Using Word-Aware Attention

2023

In recent years, due to the rapid growth of space science and utilization research of China Manned Space Engineering, a considerable amount of technical documents and web data have been produced. Named entity recognition (NER) …

Trustworthy Diagnostics With Out-of-Distribution Detection: A Novel Max-Consistency and Min-Similarity Guided Deep Ensembles for Uncertainty Estimation

2024 · IEEE Internet of Things Journal

The unknow fault diagnosis technology in industrial systems implies significant engineering application value and opportunities. The difficulty stems from the fact that the unknown fault samples frequently originate from the diagnostic model’s unknow distribution, leading …

Efficient Logical Reasoning in Large Language Models through Program-Guided Learning

2024

Language models have achieved remarkable success in generating coherent and contextually appropriate text, but they continue to face significant challenges when applied to tasks that require formal logical reasoning. Introducing structured guidance into the training …

Feature-distance-based Online Anomaly Detection for Dynamic Systems

2024

Traditional statistical anomaly detection methods struggle with the high-dimensional and highly dynamic characteristics. With the advancement in computing and monitoring capabilities, machine learning-based anomaly detection methods for dynamic system equipment have become a major research …

Verifiable, Access-Controllable, and Privacy-Preserving Multidimensional Data Aggregation based on Blockchain in Smart Grids

2024

With the development of the smart grids, terminal devices collect fine-grained sensitive data from users and achieve personalized functions. A large amount of data is sent to the control center to meet the needs of …

Graph-Sequential Alignment and Uniformity: Toward Enhanced Recommendation Systems

2025

Graph-based and sequential methods are two popular recommendation paradigms, each excelling in its domain but lacking the ability to leverage signals from the other. To address this, we propose a novel method that integrates both …