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spectral decomposition

68 papers

Papers

HyperGOOD: Towards Out-of-Distribution Detection in Hypergraphs AAAI 2026 Sparse Topic Modeling via Spectral Decomposition and Thresholding JMLR 2026 SpecQuant: Spectral Decomposition and Adaptive Truncation for Ultra-Low-Bit LLMs Quantization AAAI 2026 Statistical guarantees for denoising reflected diffusion models JMLR 2026 A Theoretical Framework For Overfitting In Energy-based Modeling ICML 2025 Hyperspectral Pansharpening via Diffusion Models with Iteratively Zero-Shot Guidance CVPR 2025 Laplace Transform Based Low-Complexity Learning of Continuous Markov Semigroups ICML 2025 Learnable Frequency Decomposition for Image Forgery Detection and Localization IJCAI 2025 Primal-Dual Spectral Representation for Off-policy Evaluation AISTATS 2025 SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting ICML 2025 SODA: Spectral Orthogonal Decomposition Adaptation for Diffusion Models WACV 2025 Spectral State Space Model for Rotation-Invariant Visual Representation Learning CVPR 2025 Continuous Product Graph Neural Networks NeurIPS 2024 LaMDA: Large Model Fine-Tuning via Spectrally Decomposed Low-Dimensional Adaptation EMNLP 2024 Neural Feature Learning in Function Space JMLR 2024 Spectral Editing of Activations for Large Language Model Alignment NeurIPS 2024 The Galerkin method beats Graph-Based Approaches for Spectral Algorithms AISTATS 2024 When and How Does In-Distribution Label Help Out-of-Distribution Detection? ICML 2024 A Faster Sampler for Discrete Determinantal Point Processes AISTATS 2023 A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning NeurIPS 2023 Decompose, Adjust, Compose: Effective Normalization by Playing With Frequency for Domain Generalization CVPR 2023 Sharp Spectral Rates for Koopman Operator Learning NeurIPS 2023 Spectral Decomposition Representation for Reinforcement Learning ICLR 2023 Towards a better understanding of representation dynamics under TD-learning ICML 2023 Understanding Self-Predictive Learning for Reinforcement Learning ICML 2023