A Neighbor-Searching Discrepancy-based Drift Detection Scheme for Learning Evolving Data
Fuente:
arXiv
Saved in:
| Main Authors: | Gu, Feng, Lu, Jie, Fang, Zhen, Wang, Kun, Zhang, Guangquan |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Generalized Incremental Learning under Concept Drift across Evolving Data Streams
by: Yu, En, et al.
Published: (2025)
by: Yu, En, et al.
Published: (2025)
Early Concept Drift Detection via Prediction Uncertainty
by: Lu, Pengqian, et al.
Published: (2024)
by: Lu, Pengqian, et al.
Published: (2024)
Drift-aware Collaborative Assistance Mixture of Experts for Heterogeneous Multistream Learning
by: Yu, En, et al.
Published: (2025)
by: Yu, En, et al.
Published: (2025)
Online Boosting Adaptive Learning under Concept Drift for Multistream Classification
by: Yu, En, et al.
Published: (2023)
by: Yu, En, et al.
Published: (2023)
Autonomous Concept Drift Threshold Determination
by: Lu, Pengqian, et al.
Published: (2025)
by: Lu, Pengqian, et al.
Published: (2025)
Debiased Negative Mining Improves Out-of-distribution Detection with Pre-trained Vision-Language Models
by: Peng, Bo, et al.
Published: (2026)
by: Peng, Bo, et al.
Published: (2026)
Learning Robust Spectral Dynamics for Temporal Domain Generalization
by: Yu, En, et al.
Published: (2025)
by: Yu, En, et al.
Published: (2025)
Online Drift Detection with Maximum Concept Discrepancy
by: Wan, Ke, et al.
Published: (2024)
by: Wan, Ke, et al.
Published: (2024)
A Behavior-Aware Approach for Deep Reinforcement Learning in Non-stationary Environments without Known Change Points
by: Liu, Zihe, et al.
Published: (2024)
by: Liu, Zihe, et al.
Published: (2024)
Privacy-Utility Trade-off in Data Publication: A Bilevel Optimization Framework with Curvature-Guided Perturbation
by: Yin, Yi, et al.
Published: (2025)
by: Yin, Yi, et al.
Published: (2025)
Autonomous Drift Learning in Data Streams: A Unified Perspective
by: Yang, Xiaoyu, et al.
Published: (2026)
by: Yang, Xiaoyu, et al.
Published: (2026)
Learning Unbiased Cluster Descriptors for Interpretable Imbalanced Concept Drift Detection
by: Zhang, Yiqun, et al.
Published: (2026)
by: Zhang, Yiqun, et al.
Published: (2026)
Autonomous Source Knowledge Selection in Multi-Domain Adaptation
by: Li, Keqiuyin, et al.
Published: (2025)
by: Li, Keqiuyin, et al.
Published: (2025)
Fair Bayesian Data Selection via Generalized Discrepancy Measures
by: Zhang, Yixuan, et al.
Published: (2025)
by: Zhang, Yixuan, et al.
Published: (2025)
Privacy Drift: Evolving Privacy Concerns in Incremental Learning
by: Ahamed, Sayyed Farid, et al.
Published: (2024)
by: Ahamed, Sayyed Farid, et al.
Published: (2024)
Comparative Study of Neighbor-based Methods for Local Outlier Detection
by: Qi, Zhuang, et al.
Published: (2024)
by: Qi, Zhuang, et al.
Published: (2024)
Evolving Machine Learning in Non-Stationary Environments: A Unified Survey of Drift, Forgetting, and Adaptation
by: Martin, Ignacio Cabrera, et al.
Published: (2025)
by: Martin, Ignacio Cabrera, et al.
Published: (2025)
DriftGuard: Mitigating Asynchronous Data Drift in Federated Learning
by: Han, Yizhou, et al.
Published: (2026)
by: Han, Yizhou, et al.
Published: (2026)
On the Learnability of Out-of-distribution Detection
by: Fang, Zhen, et al.
Published: (2024)
by: Fang, Zhen, et al.
Published: (2024)
Distributional Statistics Restore Training Data Auditability in One-step Distilled Diffusion Models
by: Li, Muxing, et al.
Published: (2025)
by: Li, Muxing, et al.
Published: (2025)
Anchor-based Maximum Discrepancy for Relative Similarity Testing
by: Zhou, Zhijian, et al.
Published: (2025)
by: Zhou, Zhijian, et al.
Published: (2025)
FedPall: Prototype-based Adversarial and Collaborative Learning for Federated Learning with Feature Drift
by: Zhang, Yong, et al.
Published: (2025)
by: Zhang, Yong, et al.
Published: (2025)
Overcoming Domain Drift in Online Continual Learning
by: Lyu, Fan, et al.
Published: (2024)
by: Lyu, Fan, et al.
Published: (2024)
Detecting Concept Drift in Evolving Malware Families Using Rule-Based Classifier Representations
by: Kalný, Tomáš, et al.
Published: (2026)
by: Kalný, Tomáš, et al.
Published: (2026)
Discovering Data Structures: Nearest Neighbor Search and Beyond
by: Salemohamed, Omar, et al.
Published: (2024)
by: Salemohamed, Omar, et al.
Published: (2024)
Fast Approximate Nearest Neighbor Search With The Navigating Spreading-out Graph
by: Fu, Cong, et al.
Published: (2017)
by: Fu, Cong, et al.
Published: (2017)
SOAR: Improved Indexing for Approximate Nearest Neighbor Search
by: Sun, Philip, et al.
Published: (2024)
by: Sun, Philip, et al.
Published: (2024)
Differentially Private In-Context Learning with Nearest Neighbor Search
by: Koskela, Antti, et al.
Published: (2025)
by: Koskela, Antti, et al.
Published: (2025)
CRINN: Contrastive Reinforcement Learning for Approximate Nearest Neighbor Search
by: Li, Xiaoya, et al.
Published: (2025)
by: Li, Xiaoya, et al.
Published: (2025)
Revisiting Deep Ensemble for Out-of-Distribution Detection: A Loss Landscape Perspective
by: Fang, Kun, et al.
Published: (2023)
by: Fang, Kun, et al.
Published: (2023)
Incremental Learning with Concept Drift Detection and Prototype-based Embeddings for Graph Stream Classification
by: Malialis, Kleanthis, et al.
Published: (2024)
by: Malialis, Kleanthis, et al.
Published: (2024)
Flow-based Policy With Distributional Reinforcement Learning in Trajectory Optimization
by: Hao, Ruijie, et al.
Published: (2026)
by: Hao, Ruijie, et al.
Published: (2026)
LLM-Enhanced Self-Evolving Reinforcement Learning for Multi-Step E-Commerce Payment Fraud Risk Detection
by: Qu, Bo, et al.
Published: (2025)
by: Qu, Bo, et al.
Published: (2025)
RoleMAG: Learning Neighbor Roles in Multimodal Graphs
by: Zuo, Yilong, et al.
Published: (2026)
by: Zuo, Yilong, et al.
Published: (2026)
From XAI to MLOps: Explainable Concept Drift Detection with Profile Drift Detection
by: Dar, Ugur, et al.
Published: (2024)
by: Dar, Ugur, et al.
Published: (2024)
LEAD-Drift: Real-time and Explainable Intent Drift Detection by Learning a Data-Driven Risk Score
by: Hossain, Md. Kamrul, et al.
Published: (2026)
by: Hossain, Md. Kamrul, et al.
Published: (2026)
Neighboring State-based Exploration for Reinforcement Learning
by: Li, Yu-Teng, et al.
Published: (2022)
by: Li, Yu-Teng, et al.
Published: (2022)
NK-GAD: Neighbor Knowledge-Enhanced Unsupervised Graph Anomaly Detection
by: Wang, Zehao, et al.
Published: (2026)
by: Wang, Zehao, et al.
Published: (2026)
Analytical Correction for Subsampling Bias in Drifting Models
by: Zhang, Jiaru, et al.
Published: (2026)
by: Zhang, Jiaru, et al.
Published: (2026)
Using Low-Discrepancy Points for Data Compression in Machine Learning: An Experimental Comparison
by: Göttlich, Simone, et al.
Published: (2024)
by: Göttlich, Simone, et al.
Published: (2024)
Similar Items
-
Generalized Incremental Learning under Concept Drift across Evolving Data Streams
by: Yu, En, et al.
Published: (2025) -
Early Concept Drift Detection via Prediction Uncertainty
by: Lu, Pengqian, et al.
Published: (2024) -
Drift-aware Collaborative Assistance Mixture of Experts for Heterogeneous Multistream Learning
by: Yu, En, et al.
Published: (2025) -
Online Boosting Adaptive Learning under Concept Drift for Multistream Classification
by: Yu, En, et al.
Published: (2023) -
Autonomous Concept Drift Threshold Determination
by: Lu, Pengqian, et al.
Published: (2025)