Copertina

Continuous Optimization for Offline Change Point Detection and Estimation

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Reimann, Hans, Moka, Sarat, Sofronov, Georgy
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Methodology Computation Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Group COMBSS: Group Selection via Continuous Optimization
di: Mathur, Anant, et al.
Pubblicazione: (2024)

Best Subset Solution Path for Linear Dimension Reduction Models using Continuous Optimization
di: Liquet, Benoit, et al.
Pubblicazione: (2024)

Parsimonious Subset Selection for Generalized Linear Models with Biomedical Applications
di: Mathur, Anant, et al.
Pubblicazione: (2026)

Geometric-Based Pruning Rules For Change Point Detection in Multiple Independent Time Series
di: Pishchagina, Liudmila, et al.
Pubblicazione: (2023)

Neural Network-Based Change Point Detection for Large-Scale Time-Evolving Data
di: Geng, Jialiang, et al.
Pubblicazione: (2025)

Controlling Continuous Relaxation for Combinatorial Optimization
di: Ichikawa, Yuma
Pubblicazione: (2023)

Score-Based Change-Point Detection and Region Localization for Spatio-Temporal Point Processes
di: Zhou, Wenbin, et al.
Pubblicazione: (2026)

Bayesian Autoregressive Online Change-Point Detection with Time-Varying Parameters
di: Tsaknaki, Ioanna-Yvonni, et al.
Pubblicazione: (2024)

Change Point Detection with Copula Entropy based Two-Sample Test
di: Ma, Jian
Pubblicazione: (2024)

Automatic Change-Point Detection in Time Series via Deep Learning
di: Li, Jie, et al.
Pubblicazione: (2022)

Continuous Parallel Relaxation for Finding Diverse Solutions in Combinatorial Optimization Problems
di: Ichikawa, Yuma, et al.
Pubblicazione: (2024)

Online Kernel CUSUM for Change-Point Detection
di: Wei, Song, et al.
Pubblicazione: (2022)

Noise-contrastive Online Change Point Detection
di: Puchkin, Nikita, et al.
Pubblicazione: (2022)

Spatial Autoregressive Model on a Dirichlet Distribution
di: Nguyen, Teo, et al.
Pubblicazione: (2024)

Locally Private Parametric Methods for Change-Point Detection
di: Yadav, Anuj Kumar, et al.
Pubblicazione: (2026)

Pi-Change: A Prior-Informed Multiple Change Point Detection Algorithm
di: Jacobs, Jonathon, et al.
Pubblicazione: (2026)

High-Dimensional Change Point Detection using Graph Spanning Ratio
di: Sun, Yang-Wen, et al.
Pubblicazione: (2025)

Federated Offline Reinforcement Learning
di: Zhou, Doudou, et al.
Pubblicazione: (2022)

On Multi-entity, Multivariate Quickest Change Point Detection
di: Kor, Bahar, et al.
Pubblicazione: (2025)

Wavelet-SARIMA-Transformer: A Hybrid Model for Rainfall Forecasting
di: Saikia, Junmoni, et al.
Pubblicazione: (2025)

LITE: Efficiently Estimating Gaussian Probability of Maximality
di: Menet, Nicolas, et al.
Pubblicazione: (2025)

MOSAIC: Minimax-Optimal Sparsity-Adaptive Inference for Change Points in Dynamic Networks
di: Fan, Yingying, et al.
Pubblicazione: (2025)

Preconditioned Robust Neural Posterior Estimation for Misspecified Simulators
di: Kelly, Ryan P., et al.
Pubblicazione: (2026)

Semi-Parametric Inference for Doubly Stochastic Spatial Point Processes: An Approximate Penalized Poisson Likelihood Approach
di: Cheng, Si, et al.
Pubblicazione: (2023)

Estimate-Then-Optimize versus Integrated-Estimation-Optimization versus Sample Average Approximation: A Stochastic Dominance Perspective
di: Elmachtoub, Adam N., et al.
Pubblicazione: (2023)

Temperature Optimization for Bayesian Deep Learning
di: Ng, Kenyon, et al.
Pubblicazione: (2024)

LEARNER: A Transfer Learning Method for Low-Rank Matrix Estimation
di: McGrath, Sean, et al.
Pubblicazione: (2024)

Automated Efficient Estimation using Monte Carlo Efficient Influence Functions
di: Agrawal, Raj, et al.
Pubblicazione: (2024)

LARGE: A Locally Adaptive Regularization Approach for Estimating Gaussian Graphical Models
di: Nguyen, Ha, et al.
Pubblicazione: (2026)

Dimension-reduced Reconstruction Map Learning for Parameter Estimation in Likelihood-Free Inference Problems
di: Zhang, Rui, et al.
Pubblicazione: (2024)

Conditional Mean and Variance Estimation via \textit{k}-NN Algorithm with Automated Variance Selection
di: Matabuena, Marcos, et al.
Pubblicazione: (2024)

FAStEN: An Efficient Adaptive Method for Feature Selection and Estimation in High-Dimensional Functional Regressions
di: Boschi, Tobia, et al.
Pubblicazione: (2023)

Gradient Boosted Mixed Models: Flexible Joint Estimation of Mean and Variance Components for Clustered Data
di: Prevett, Mitchell L., et al.
Pubblicazione: (2025)

Optimization by Parallel Quasi-Quantum Annealing with Gradient-Based Sampling
di: Ichikawa, Yuma, et al.
Pubblicazione: (2024)

Bayesian Ensembling: Insights from Online Optimization and Empirical Bayes
di: Waxman, Daniel, et al.
Pubblicazione: (2025)

Learning Interpretable Point-Based Clinical Risk Scores via Direct Optimization
di: Cui, Ying, et al.
Pubblicazione: (2026)

Optimization-based Causal Estimation from Heterogenous Environments
di: Yin, Mingzhang, et al.
Pubblicazione: (2021)

Inferring Change Points in Regression via Sample Weighting
di: Arpino, Gabriel, et al.
Pubblicazione: (2026)

DAG DECORation: Continuous Optimization for Structure Learning under Hidden Confounding
di: Pal, Samhita, et al.
Pubblicazione: (2025)

A Log-Linear Non-Parametric Online Changepoint Detection Algorithm based on Functional Pruning
di: Romano, Gaetano, et al.
Pubblicazione: (2023)