Copertina

Tracking Dynamic Gaussian Density with a Theoretically Optimal Sliding Window Approach

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wang, Yinsong, Ding, Yu, Shahrampour, Shahin
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Theoretical Analysis of Measure Consistency Regularization for Partially Observed Data
di: Wang, Yinsong, et al.
Pubblicazione: (2026)

TAP: The Attention Patch for Cross-Modal Knowledge Transfer from Unlabeled Modality
di: Wang, Yinsong, et al.
Pubblicazione: (2023)

Online Optimization on Hadamard Manifolds: Curvature Independent Regret Bounds on Horospherically Convex Objectives
di: Sahinoglu, Emre, et al.
Pubblicazione: (2025)

Online Optimization Perspective on First-Order and Zero-Order Decentralized Nonsmooth Nonconvex Stochastic Optimization
di: Sahinoglu, Emre, et al.
Pubblicazione: (2024)

Decentralized Online Riemannian Optimization Beyond Hadamard Manifolds
di: Sahinoglu, Emre, et al.
Pubblicazione: (2025)

Regret Analysis of Policy Optimization over Submanifolds for Linearly Constrained Online LQG
di: Chang, Ting-Jui, et al.
Pubblicazione: (2024)

Finite-Time Analysis of Stochastic Nonconvex Nonsmooth Optimization on the Riemannian Manifolds
di: Sahinoglu, Emre, et al.
Pubblicazione: (2025)

Local Linear Convergence of Infeasible Optimization with Orthogonal Constraints
di: Sun, Youbang, et al.
Pubblicazione: (2024)

Retraction-Free Decentralized Non-convex Optimization with Orthogonal Constraints
di: Sun, Youbang, et al.
Pubblicazione: (2024)

Optimal Matrix Sketching over Sliding Windows
di: Yin, Hanyan, et al.
Pubblicazione: (2024)

Linear Convergence of Independent Natural Policy Gradient in Games with Entropy Regularization
di: Sun, Youbang, et al.
Pubblicazione: (2024)

Optimal Approximate Matrix Multiplication over Sliding Windows
di: Yao, Ziqi, et al.
Pubblicazione: (2025)

Sliding Window Recurrences for Sequence Models
di: Secrieru, Dragos, et al.
Pubblicazione: (2025)

Mutual Information Surprise: Rethinking Unexpectedness in Autonomous Systems
di: Wang, Yinsong, et al.
Pubblicazione: (2025)

ADARL: Adaptive Low-Rank Structures for Robust Policy Learning under Uncertainty
di: Li, Chenliang, et al.
Pubblicazione: (2025)

Sliding-Window Thompson Sampling for Non-Stationary Settings
di: Fiandri, Marco, et al.
Pubblicazione: (2024)

Online Learning with Limited Information in the Sliding Window Model
di: Braverman, Vladimir, et al.
Pubblicazione: (2026)

Learning-Augmented Frequency Estimation in Sliding Windows
di: Shahout, Rana, et al.
Pubblicazione: (2024)

A Bayesian Framework for Uncertainty-Aware Explanations in Power Quality Disturbance Classification
di: Chen, Yinsong, et al.
Pubblicazione: (2026)

A Posterior-Predictive Variance Decomposition for Epistemic and Aleatoric Uncertainty in Wind Power Forecasting
di: Chen, Yinsong, et al.
Pubblicazione: (2026)

Designing Adaptive Algorithms Based on Reinforcement Learning for Dynamic Optimization of Sliding Window Size in Multi-Dimensional Data Streams
di: Zarghani, Abolfazl, et al.
Pubblicazione: (2025)

Sliding-Window Signatures for Time Series: Application to Electricity Demand Forecasting
di: Drobac, Nina, et al.
Pubblicazione: (2025)

Enhancing Predictive Accuracy in Pharmaceutical Sales Through An Ensemble Kernel Gaussian Process Regression Approach
di: Mirshekari, Shahin, et al.
Pubblicazione: (2024)

Sliding Window Attention Training for Efficient Large Language Models
di: Fu, Zichuan, et al.
Pubblicazione: (2025)

SWIFT-FMQA: Enhancing Factorization Machine with Quadratic-Optimization Annealing via Sliding Window
di: Nakano, Mayumi, et al.
Pubblicazione: (2025)

Beyond Sliding Windows: Learning to Manage Memory in Non-Markovian Environments
di: Tasse, Geraud Nangue, et al.
Pubblicazione: (2025)

Optimal Robust Recourse with $L^p$-Bounded Model Change
di: Kyaw, Phone, et al.
Pubblicazione: (2025)

Sliding Window Training -- Utilizing Historical Recommender Systems Data for Foundation Models
di: Joshi, Swanand, et al.
Pubblicazione: (2024)

Addressing the Inconsistency in Bayesian Deep Learning via Generalized Laplace Approximation
di: Chen, Yinsong, et al.
Pubblicazione: (2024)

A Unified Framework for Uncertainty-Aware Explainable Artificial Intelligence: A Case Study in Power Quality Disturbance Classification
di: Chen, Yinsong, et al.
Pubblicazione: (2026)

Deep Learning-Based Financial Time Series Forecasting via Sliding Window and Variational Mode Decomposition
di: Li, Luke
Pubblicazione: (2025)

Optimal Control Theoretic Neural Optimizer: From Backpropagation to Dynamic Programming
di: Liu, Guan-Horng, et al.
Pubblicazione: (2025)

Tracking Temporal Dynamics of Vector Sets with Gaussian Process
di: Aida, Taichi, et al.
Pubblicazione: (2025)

A Dynamic, Ordinal Gaussian Process Item Response Theoretic Model
di: Chen, Yehu, et al.
Pubblicazione: (2025)

Mixture of Attention Spans: Optimizing LLM Inference Efficiency with Heterogeneous Sliding-Window Lengths
di: Fu, Tianyu, et al.
Pubblicazione: (2024)

Rethinking the Role of Positional Encoding: Sliding-Window Transformers without PE Remain Turing Complete
di: Li, Qian, et al.
Pubblicazione: (2026)

Shaping Initial State Prevents Modality Competition in Multi-modal Fusion: A Two-stage Scheduling Framework via Fast Partial Information Decomposition
di: Tang, Jiaqi, et al.
Pubblicazione: (2025)

Integrating Marketing Channels into Quantile Transformation and Bayesian Optimization of Ensemble Kernels for Sales Prediction with Gaussian Process Models
di: Mirshekari, Shahin, et al.
Pubblicazione: (2024)

Is Sliding Window All You Need? An Open Framework for Long-Sequence Recommendation
di: Chakrabarty, Sayak, et al.
Pubblicazione: (2026)

Model-Based Learning of Near-Optimal Finite-Window Policies in POMDPs
di: Jordan, Philip, et al.
Pubblicazione: (2026)