Huan Li

Safe Deep Reinforcement Learning Based on Sample Value Evaluation

2022

In recent years, deep reinforcement learning has combined the advantages of reinforcement learning and deep learning, and has made great progress in decision-making tasks. However, the training of deep reinforcement learning requires frequent interactions between …

Point-Correlate Adversarial Transformer for Unsupervised Multivariate Time Series Anomaly Detection

2024

Multivariate time series anomaly detection plays a crucial role in industrial production. However, the inherent complexity and randomness of time series pose significant challenges. Furthermore, existing detection methods struggle to provide reliable explanations for outliers. …

BoKA: Bayesian Optimization based Knowledge Amalgamation for Multi-unknown-domain Text Classification

2024

With breakthroughs in pretrained language models, a large number of finetuned models specialized in distinct domains have surfaced online. Yet, when faced with a fresh dataset covering multiple (sub)domains, their performance might degrade. Reusing these …

CHASe: Client Heterogeneity-Aware Data Selection for Effective Federated Active Learning

2025 · IEEE Transactions on Knowledge and Data Engineering

Active learning (AL) reduces human annotation costs for machine learning systems by strategically selecting the most informative unlabeled data for annotation, but performing it individually may still be insufficient due to restricted data diversity and …

Complex-valued matrix-vector multiplication using a scalable coherent photonic processor

2025 · Science Advances

Matrix-vector multiplication is a fundamental operation in modern signal processing and artificial intelligence. Developing a chip-scale photonic matrix-vector multiplication processor (MVMP) offers the potential for notably enhanced computing speed and energy efficiency beyond microelectronics. Here, …