Cover Image

Triadic-OCD: Asynchronous Online Change Detection with Provable Robustness, Optimality, and Convergence

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Huang, Yancheng, Yang, Kai, Zhu, Zelin, Chen, Leian
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

RoS-Guard: Robust and Scalable Online Change Detection with Delay-Optimal Guarantees
by: Zhu, Zelin, et al.
Published: (2025)

Scalable, Explainable and Provably Robust Anomaly Detection with One-Step Flow Matching
by: Li, Zhong, et al.
Published: (2025)

Provably Robust Bayesian Counterfactual Explanations under Model Changes
by: Duell, Jamie, et al.
Published: (2026)

Provable Robust Saliency-based Explanations
by: Chen, Chao, et al.
Published: (2022)

Provably Mitigating Corruption, Overoptimization, and Verbosity Simultaneously in Offline and Online RLHF/DPO Alignment
by: Chen, Ziyi, et al.
Published: (2025)

Provably Robust Adaptation for Language-Empowered Foundation Models
by: Lai, Yuni, et al.
Published: (2025)

Cellular Traffic Prediction via Byzantine-robust Asynchronous Federated Learning
by: Ma, Hui, et al.
Published: (2025)

Accelerating Convergence of Score-Based Diffusion Models, Provably
by: Li, Gen, et al.
Published: (2024)

Enhancing Convergence in Federated Learning: A Contribution-Aware Asynchronous Approach
by: Xu, Changxin, et al.
Published: (2024)

Accelerating Asynchronous Federated Learning Convergence via Opportunistic Mobile Relaying
by: Bian, Jieming, et al.
Published: (2022)

Compute-Optimal LLMs Provably Generalize Better With Scale
by: Finzi, Marc, et al.
Published: (2025)

Provable Robust Overfitting Mitigation in Wasserstein Distributionally Robust Optimization
by: Liu, Shuang, et al.
Published: (2025)

Online Neural Networks for Change-Point Detection
by: Hushchyn, Mikhail, et al.
Published: (2020)

Wide & Deep Learning for Node Classification
by: Chen, Yancheng, et al.
Published: (2025)

FedPSA: Modeling Behavioral Staleness in Asynchronous Federated Learning
by: Lu, Chaoyi, et al.
Published: (2026)

Provably Robust and Plausible Counterfactual Explanations for Neural Networks via Robust Optimisation
by: Jiang, Junqi, et al.
Published: (2023)

The Path Not Taken: RLVR Provably Learns Off the Principals
by: Zhu, Hanqing, et al.
Published: (2025)

Provable Last-Iterate Convergence for Multi-Objective Safe LLM Alignment via Optimistic Primal-Dual
by: Li, Yining, et al.
Published: (2026)

Multi-layer Cross-attention is Provably Optimal for Multi-modal In-context Learning
by: Barnfield, Nicholas, et al.
Published: (2026)

Provably Robust Pre-Trained Ensembles for Biomarker-Based Cancer Classification
by: Lee, Chongmin, et al.
Published: (2024)

Scalable Valuation of Human Feedback through Provably Robust Model Alignment
by: Fujisawa, Masahiro, et al.
Published: (2025)

Provable Zero-Shot Generalization in Offline Reinforcement Learning
by: Wang, Zhiyong, et al.
Published: (2025)

UrbanMind: Towards Urban General Intelligence via Tool-Enhanced Retrieval-Augmented Generation and Multilevel Optimization
by: Yang, Kai, et al.
Published: (2025)

Adaptive Self-supervised Robust Clustering for Unstructured Data with Unknown Cluster Number
by: Ding, Chen-Lu, et al.
Published: (2024)

Provably Efficient Algorithm for Best Scoring Rule Identification in Online Principal-Agent Information Acquisition
by: Wang, Zichen, et al.
Published: (2025)

A Triadic Suffix Tokenization Scheme for Numerical Reasoning
by: Chetverina, Olga
Published: (2026)

Stagnation in Evolutionary Algorithms: Convergence $\neq$ Optimality
by: Zhou, Xiaojun
Published: (2025)

Change Detection in Multivariate data streams: Online Analysis with Kernel-QuantTree
by: Notarianni, Michelangelo Olmo Nogara, et al.
Published: (2024)

Dyn-D$^2$P: Dynamic Differentially Private Decentralized Learning with Provable Utility Guarantee
by: Zhu, Zehan, et al.
Published: (2025)

Policy Gradient Methods for Risk-Sensitive Distributional Reinforcement Learning with Provable Convergence
by: Xiao, Minheng, et al.
Published: (2024)

Provable Training Data Identification for Large Language Models
by: Liu, Zhenlong, et al.
Published: (2025)

CoPS: Empowering LLM Agents with Provable Cross-Task Experience Sharing
by: Yang, Chen, et al.
Published: (2024)

Federated Contextual Cascading Bandits with Asynchronous Communication and Heterogeneous Users
by: Yang, Hantao, et al.
Published: (2024)

Model-agnostic Selective Labeling with Provable Statistical Guarantees
by: Huang, Huipeng, et al.
Published: (2025)

Learning Cell-Aware Hierarchical Multi-Modal Representations for Robust Molecular Modeling
by: Li, Mengran, et al.
Published: (2025)

Asynchronous Graph Generator
by: Ley, Christopher P., et al.
Published: (2023)

Asynchronous and Segmented Bidirectional Encoding for NMT
by: Yang, Jingpu, et al.
Published: (2024)

Deciphering Raw Data in Neuro-Symbolic Learning with Provable Guarantees
by: Tao, Lue, et al.
Published: (2023)

$Q\sharp$: Provably Optimal Distributional RL for LLM Post-Training
by: Zhou, Jin Peng, et al.
Published: (2025)

AsyncFlow: An Asynchronous Streaming RL Framework for Efficient LLM Post-Training
by: Han, Zhenyu, et al.
Published: (2025)