singular value

Learning Continually by Spectral Regularization ICLR 2025 Learning dynamics in linear recurrent neural networks ICML 2025 Mind the Gap: a Spectral Analysis of Rank Collapse and Signal Propagation in Attention Layers ICML 2025 Singular Subspace Perturbation Bounds via Rectangular Random Matrix Diffusions ICLR 2025 Efficiency Calibration of Implicit Regularization in Deep Networks via Self-paced Curriculum-Driven Singular Value Selection IJCAI 2024 Estimation of the Order of Non-Parametric Hidden Markov Models using the Singular Values of an Integral Operator JMLR 2024 Local and Global Flatness for Federated Domain Generalization ECCV 2024 Weight Conditioning for Smooth Optimization of Neural Networks ECCV 2024 On the spectral bias of two-layer linear networks NeurIPS 2023 Towards Inadequately Pre-trained Models in Transfer Learning ICCV 2023 On the Faster Alternating Least-Squares for CCA AISTATS 2021 Controllable Orthogonalization in Training DNNs CVPR 2020 I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations IJCAI 2020 Revisiting the Landscape of Matrix Factorization AISTATS 2020 Spectrum Estimation from a Few Entries JMLR 2019 The emergence of spectral universality in deep networks AISTATS 2018 Diverse Neural Network Learns True Target Functions AISTATS 2017 Matrix Norm Estimation from a Few Entries NeurIPS 2017 Elastic-Net Regularization of Singular Values for Robust Subspace Learning CVPR 2015 Fast and Memory Optimal Low-Rank Matrix Approximation NeurIPS 2015 Low-Rank Spectral Learning with Weighted Loss Functions AISTATS 2015 Weighted Nuclear Norm Minimization with Application to Image Denoising CVPR 2014 Partial Sum Minimization of Singular Values in RPCA for Low-Level Vision ICCV 2013