Saved in:
| Main Authors: | Chavent, Marie, Chavent, Guy |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2402.04692 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
mDAE : modified Denoising AutoEncoder for missing data imputation
by: Dupuy, Mariette, et al.
Published: (2024)
by: Dupuy, Mariette, et al.
Published: (2024)
Counterfactual explainability and analysis of variance
by: Gao, Zijun, et al.
Published: (2024)
by: Gao, Zijun, et al.
Published: (2024)
Neglected Hessian component explains mysteries in Sharpness regularization
by: Dauphin, Yann N., et al.
Published: (2024)
by: Dauphin, Yann N., et al.
Published: (2024)
Geometric design of the tangent term in landing algorithms for orthogonality constraints
by: Goyens, Florentin, et al.
Published: (2025)
by: Goyens, Florentin, et al.
Published: (2025)
PCA-VAE: Differentiable Subspace Quantization without Codebook Collapse
by: Lu, Hao, et al.
Published: (2026)
by: Lu, Hao, et al.
Published: (2026)
Graph Regularized PCA
by: Briola, Antonio, et al.
Published: (2026)
by: Briola, Antonio, et al.
Published: (2026)
Low-Precision Streaming PCA
by: Dasgupta, Sanjoy, et al.
Published: (2025)
by: Dasgupta, Sanjoy, et al.
Published: (2025)
Attention-based PCA
by: Maulen-Soto, Rodrigo, et al.
Published: (2026)
by: Maulen-Soto, Rodrigo, et al.
Published: (2026)
A space-decoupling framework for optimization on bounded-rank matrices with orthogonally invariant constraints
by: Yang, Yan, et al.
Published: (2025)
by: Yang, Yan, et al.
Published: (2025)
PCA, SVD, and Centering of Data
by: Kim, Donggun, et al.
Published: (2023)
by: Kim, Donggun, et al.
Published: (2023)
Kernel PCA for Out-of-Distribution Detection
by: Fang, Kun, et al.
Published: (2024)
by: Fang, Kun, et al.
Published: (2024)
Exponential Convergence of CAVI for Bayesian PCA
by: Datta, Arghya, et al.
Published: (2025)
by: Datta, Arghya, et al.
Published: (2025)
Mean-Shift PCA by Knockoff Mean
by: Li, Mengda, et al.
Published: (2026)
by: Li, Mengda, et al.
Published: (2026)
PCA for Point Processes
by: Picard, Franck, et al.
Published: (2024)
by: Picard, Franck, et al.
Published: (2024)
A Geometric Analysis of PCA
by: Hanchi, Ayoub El, et al.
Published: (2025)
by: Hanchi, Ayoub El, et al.
Published: (2025)
Rethinking PCA Through Duality
by: Quan, Jan, et al.
Published: (2025)
by: Quan, Jan, et al.
Published: (2025)
A Generalized Mean Approach for Distributed-PCA
by: Jou, Zhi-Yu, et al.
Published: (2024)
by: Jou, Zhi-Yu, et al.
Published: (2024)
Fair PCA, One Component at a Time
by: Matakos, Antonis, et al.
Published: (2025)
by: Matakos, Antonis, et al.
Published: (2025)
A PCA-based Data Prediction Method
by: Daugulis, Peteris, et al.
Published: (2025)
by: Daugulis, Peteris, et al.
Published: (2025)
When three experiments are better than two: Avoiding intractable correlated aleatoric uncertainty by leveraging a novel bias--variance tradeoff
by: Scherer, Paul, et al.
Published: (2025)
by: Scherer, Paul, et al.
Published: (2025)
Deflated HeteroPCA: Overcoming the curse of ill-conditioning in heteroskedastic PCA
by: Zhou, Yuchen, et al.
Published: (2023)
by: Zhou, Yuchen, et al.
Published: (2023)
Oja's Algorithm for Streaming Sparse PCA
by: Kumar, Syamantak, et al.
Published: (2024)
by: Kumar, Syamantak, et al.
Published: (2024)
There and back again: bridging meso- and nanoscales to understand lipid vesicle patterning
by: Cornet, Julie, et al.
Published: (2024)
by: Cornet, Julie, et al.
Published: (2024)
TL-PCA: Transfer Learning of Principal Component Analysis
by: Hendy, Sharon, et al.
Published: (2024)
by: Hendy, Sharon, et al.
Published: (2024)
Capturing the Denoising Effect of PCA via Compression Ratio
by: Mukherjee, Chandra Sekhar, et al.
Published: (2022)
by: Mukherjee, Chandra Sekhar, et al.
Published: (2022)
Achieving Fair PCA Using Joint Eigenvalue Decomposition
by: Rathore, Vidhi, et al.
Published: (2025)
by: Rathore, Vidhi, et al.
Published: (2025)
Mild Over-Parameterization Benefits Asymmetric Tensor PCA
by: Ding, Shihong, et al.
Published: (2026)
by: Ding, Shihong, et al.
Published: (2026)
PCA of probability measures: Sparse and Dense sampling regimes
by: Erell, Gachon, et al.
Published: (2026)
by: Erell, Gachon, et al.
Published: (2026)
Sparse PCA With Multiple Components
by: Cory-Wright, Ryan, et al.
Published: (2022)
by: Cory-Wright, Ryan, et al.
Published: (2022)
Spectral Guarantees for Adversarial Streaming PCA
by: Price, Eric, et al.
Published: (2024)
by: Price, Eric, et al.
Published: (2024)
Variable selection for minimum-variance portfolios
by: Moura, Guilherme V., et al.
Published: (2025)
by: Moura, Guilherme V., et al.
Published: (2025)
Asymptotically perfect seeded graph matching without edge correlation (and applications to inference)
by: Qi, Tong, et al.
Published: (2025)
by: Qi, Tong, et al.
Published: (2025)
Quantum principal component analysis without eigenvector recovery
by: Yuan, Yewei, et al.
Published: (2026)
by: Yuan, Yewei, et al.
Published: (2026)
Bias-variance decompositions: the exclusive privilege of Bregman divergences
by: Heskes, Tom
Published: (2025)
by: Heskes, Tom
Published: (2025)
On weight and variance uncertainty in neural networks for regression tasks
by: Monemi, Moein, et al.
Published: (2025)
by: Monemi, Moein, et al.
Published: (2025)
Robust variance-regularized risk minimization with concomitant scaling
by: Holland, Matthew J.
Published: (2023)
by: Holland, Matthew J.
Published: (2023)
Sharp Analysis of Power Iteration for Tensor PCA
by: Wu, Yuchen, et al.
Published: (2024)
by: Wu, Yuchen, et al.
Published: (2024)
Efficient Sparse PCA via Block-Diagonalization
by: Del Pia, Alberto, et al.
Published: (2024)
by: Del Pia, Alberto, et al.
Published: (2024)
Sparse PCA with False Discovery Rate Controlled Variable Selection
by: Machkour, Jasin, et al.
Published: (2024)
by: Machkour, Jasin, et al.
Published: (2024)
Randomized PCA Forest for Unsupervised Outlier Detection
by: Rajabinasab, Muhammad, et al.
Published: (2025)
by: Rajabinasab, Muhammad, et al.
Published: (2025)
Similar Items
-
mDAE : modified Denoising AutoEncoder for missing data imputation
by: Dupuy, Mariette, et al.
Published: (2024) -
Counterfactual explainability and analysis of variance
by: Gao, Zijun, et al.
Published: (2024) -
Neglected Hessian component explains mysteries in Sharpness regularization
by: Dauphin, Yann N., et al.
Published: (2024) -
Geometric design of the tangent term in landing algorithms for orthogonality constraints
by: Goyens, Florentin, et al.
Published: (2025) -
PCA-VAE: Differentiable Subspace Quantization without Codebook Collapse
by: Lu, Hao, et al.
Published: (2026)