spectral learning

Deep Spectral Learning of Embedded Latent Transfer Operators for Stochastic Dynamical Systems UAI 2026 Any-Resolution AI-Generated Image Detection by Spectral Learning CVPR 2025 Spectral Learning of Shared Dynamics Between Generalized-Linear Processes NeurIPS 2024 Neural Networks as Kernel Learners: The Silent Alignment Effect ICLR 2022 Spectral Unsupervised Domain Adaptation for Visual Recognition CVPR 2022 Minimizing Annotation Effort via Max-Volume Spectral Sampling EMNLP 2021 Perturbing Eigenvalues with Residual Learning in Graph Convolutional Neural Networks ACML 2021 Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction NeurIPS 2021 Efficient Planning under Partial Observability with Unnormalized Q Functions and Spectral Learning AISTATS 2020 Connecting Weighted Automata and Recurrent Neural Networks through Spectral Learning AISTATS 2019 Interpolated Spectral NGram Language Models ACL 2019 On the Global Optima of Kernelized Adversarial Representation Learning ICCV 2019 Relating RNN Layers with the Spectral WFA Ranks in Sequence Modelling ACL 2019 Completing State Representations using Spectral Learning NeurIPS 2018 Nonlinear Weighted Finite Automata AISTATS 2018 Multitask Spectral Learning of Weighted Automata NeurIPS 2017 Spectral Learning from a Single Trajectory under Finite-State Policies ICML 2017 Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning JMLR 2016 Spectral Learning of Dynamic Systems from Nonequilibrium Data NeurIPS 2016 Low-Rank Spectral Learning with Weighted Loss Functions AISTATS 2015 Spectral Learning of Large Structured HMMs for Comparative Epigenomics NeurIPS 2015 Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning ICML 2014 Low-Rank Spectral Learning AISTATS 2014 Spectral Learning of Latent-Variable PCFGs: Algorithms and Sample Complexity JMLR 2014 Spectral Learning of Mixture of Hidden Markov Models NeurIPS 2014