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Author

C. P. Philip Chen

6 papers indexed here

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2026

Structured Multi-Evidence Learning for Hyperspectral Image Clustering

The hyperspectral images (HSIs) record subtle spectral responses of land-cover materials over a large number of contiguous bands, providing rich information for unsupervised land-cover analysis. However, local environmental variations, spectral ambiguity, and band redundancy often make the underlying clustering structu...

Hui-Lang Xu, Kai-Yu Lin, Pan Gao et al. · 0 citations
Oct 2026

Adaptive Progressive Optimization Ensemble Approach for High-Dimensional Imbalanced Data Classification

High-dimensional imbalanced data presents the problems of massive invalid features and class imbalance, making it arduous for classifiers to gain respectable outcomes. Compared to the individual classifier, classifier ensemble has great potential to elevate the performance. In this paper, an adaptive progressive optimi...

Yuyang Deng, Yu-Hong Xu, Pei-Jie Huang et al. · 0 citations
Oct 2026

G1Stack: A Learning-Assisted Scheduler Framework for Interactive and Batch Workload Co-Location With High Resource Efficiency

Interactive services typically over-provision CPU resources to meet Service Level Objectives (SLOs) for tail latency amidst workload fluctuations. This inefficiency motivates emerging research into workload co-location, where batch jobs are hosted alongside interactive services to harvest underutilized resources. Howev...

Di-Shi Xu, Fagui Liu, Bin Wang et al. · 0 citations
2026

Decision Boundary Drift: A Security, Privacy, and Trust Risk of Continual Learning for Agentic AI in Edge Networks

Continual learning (CL) is a key paradigm that enables intelligent agents to operate autonomously in edge networks over the long term. However, continuous model updates can lead to catastrophic forgetting and representation instability in edge deployment scenarios, which may further induce Decision Boundary Drift (DBD)...

Kaixiang Yang, Yue-Bin Xu, Zhi-Hao Li et al. · 0 citations
Review Aug 2026

Learning-Based Motion Planning for Dynamic Environments: From Foundational Algorithms to Emerging Paradigms

A role-of-learning taxonomy is proposed that categorizes existing methods according to how learning participates in the planning pipeline, including direct policy learning, learning-augmented classical planning, hybrid planning, and training enhancement methods.

Zong-Yuan Shen, Shalabh Gupta, Shan-Cheng Zhao et al. · 1 citation
Jul 2026

Large model-assisted video summarization via global entity unification and robust importance scoring

A summarization pipeline around Global Entity Unification and Robust Importance Scoring is built, but unlike earlier efforts, each object is traced across frames and attached consistent identifiers to it, and Fragmented, isolated descriptions become a single, object-aware text corpus that unifies the storyline.

Donglei Chen, Shaoyu Huang, Xuemiao Xu et al. · 0 citations

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