frobenius norm

On Purely Private Covariance Estimation ALT 2026 Elastic Representation: Mitigating Spurious Correlations for Group Robustness AISTATS 2025 FroM: Frobenius Norm-Based Data-Free Adaptive Model Merging EMNLP 2025 Robust Consensus Anchor Learning for Efficient Multi-view Subspace Clustering ICML 2025 Dimension-free Structured Covariance Estimation COLT 2024 Optimal Sketching for Residual Error Estimation for Matrix and Vector Norms ICLR 2024 Scalable Multiple Kernel Clustering: Learning Clustering Structure from Expectation ICML 2024 Fast (1+ε)-Approximation Algorithms for Binary Matrix Factorization ICML 2023 RegBN: Batch Normalization of Multimodal Data with Regularization NeurIPS 2023 The Sample Complexity of One-Hidden-Layer Neural Networks NeurIPS 2022 Additive Error Guarantees for Weighted Low Rank Approximation ICML 2021 Minimax Estimation of Laplacian Constrained Precision Matrices AISTATS 2021 Rate-Optimal Subspace Estimation on Random Graphs NeurIPS 2021 The Sample Complexity of Robust Covariance Testing COLT 2021 Goodness-of-Fit Tests for Inhomogeneous Random Graphs ICML 2020 Faster Algorithms for Binary Matrix Factorization ICML 2019 Fine-grained Optimization of Deep Neural Networks NeurIPS 2019 A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks ICLR 2018 Matrix Completion from $O(n)$ Samples in Linear Time COLT 2017 On the Power of Truncated SVD for General High-rank Matrix Estimation Problems NeurIPS 2017 Reconstructing Undirected Graphs from Eigenspaces JMLR 2017 Estimating Jaccard Index with Missing Observations: A Matrix Calibration Approach NeurIPS 2015 Robust Tensor Decomposition with Gross Corruption NeurIPS 2014 Doubly Stochastic Normalization for Spectral Clustering NeurIPS 2006