:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Wang, Yinsong, Ding, Yu, Shahrampour, Shahin
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2403.07207
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Locating and Mitigating Gradient Conflicts in Point Cloud Domain Adaptation via Saliency Map Skewness
by: Tang, Jiaqi, et al.
Published: (2025)

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

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

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

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

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

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