Biography
个人简介
山东大学博士后,研究兴趣主要包括时间序列分析与决策、多模态信息融合、计算机视觉、大模型高效迁移等。
Research Areas
研究方向
时间序列分析与决策多模态信息融合计算机视觉大模型高效迁移等
Personal Publications
已发表论文
2026ReCast: Reliability-aware Codebook-assisted Lightweight Time Series Forecasting
AAAI Conference on Artificial Intelligence · AAAI · CCF-A
2026Aligning the True Semantics: Constrained Decoupling and Distribution Sampling for Cross-Modal Alignment
AAAI Conference on Artificial Intelligence · AAAI · CCF-A
2025Reliable Cross-modal Alignment via Prototype Iterative Construction
ACM International Conference on Multimedia · ACM MM · CCF-A
2025Minding Fuzzy Regions: A Data-driven Alternating Learning Paradigm for Stable Lesion Segmentation
IEEE/CVF Conference on Computer Vision and Pattern Recognition · CVPR · CCF-A
2024Bridging the Modality Gap: Dimension Information Alignment and Sparse Spatial Constraint for Image-Text Matching
ACM International Conference on Multimedia · ACM MM · CCF-A
2024U-Mixer: An Unet-Mixer Architecture with Stationarity Correction for Time Series Forecasting
AAAI Conference on Artificial Intelligence · AAAI · CCF-A
2023Dynamic graph construction via motif detection for stock prediction
Information Processing & Management · IPM · CCF-B
2023A representation learning framework for stock movement prediction
Applied Soft Computing · ASOC · 二区
2023COVID19-MLSF: A multi-task learning-based stock market forecasting framework during the COVID-19 pandemic
Expert Systems with Applications · ESWA · 一区
2023Asset correlation based deep reinforcement learning for the portfolio selection
Expert Systems with Applications · ESWA · 一区
2022Fuzzy Hypergraph Network for Recommending Top-K Profitable Stocks
Information Sciences · IS · CCF-B
2022A hierarchical attention network for stock prediction based on attentive multi-view news learning
Neurocomputing · Neurocomputing · CCF-C
2022A stock price prediction method based on meta-learning and variational mode decomposition
Knowledge-Based Systems · KBS · 一区
2021Image smoothing based on global sparsity decomposition and a variable parameter
Computational Visual Media · CVM · 二区
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