Chebyshev Moment Regularization (CMR): Condition-Number Control with Moment Shaping
Fuente:
arXiv
Saved in:
| Main Author: | Baek, Jinwoo |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Matrix Phylogeny: Compact Spectral Fingerprints for Trap-Robust Preconditioner Selection
by: Baek, Jinwoo
Published: (2025)
by: Baek, Jinwoo
Published: (2025)
Numerical Fragility in Transformers: A Layer-wise Theory for Explaining, Forecasting, and Mitigating Instability
by: Baek, Jinwoo
Published: (2025)
by: Baek, Jinwoo
Published: (2025)
Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning
by: Dong, Yijun, et al.
Published: (2024)
by: Dong, Yijun, et al.
Published: (2024)
Exact Gaussian Moment Matching for Residual Networks: a Second-Order Method
by: Kuang, Simon, et al.
Published: (2026)
by: Kuang, Simon, et al.
Published: (2026)
Beyond Muon: MUD (MomentUm Decorrelation) for Faster Transformer Training
by: Southworth, Ben S., et al.
Published: (2026)
by: Southworth, Ben S., et al.
Published: (2026)
Condition Numbers and Eigenvalue Spectra of Shallow Networks on Spheres
by: Liu, Xinliang, et al.
Published: (2025)
by: Liu, Xinliang, et al.
Published: (2025)
ChebNet: Efficient and Stable Constructions of Deep Neural Networks with Rectified Power Units via Chebyshev Approximations
by: Tang, Shanshan, et al.
Published: (2019)
by: Tang, Shanshan, et al.
Published: (2019)
Accelerating Eigenvalue Dataset Generation via Chebyshev Subspace Filter
by: Wang, Hong, et al.
Published: (2025)
by: Wang, Hong, et al.
Published: (2025)
Chebyshev Spectral Neural Networks for Solving Partial Differential Equations
by: Yin, Pengsong, et al.
Published: (2024)
by: Yin, Pengsong, et al.
Published: (2024)
Deep Neural-network Prior for Orbit Recovery from Method of Moments
by: Khoo, Yuehaw, et al.
Published: (2023)
by: Khoo, Yuehaw, et al.
Published: (2023)
Lattice-based Deep Neural Networks: Regularity and Tailored Regularization
by: Keller, Alexander, et al.
Published: (2026)
by: Keller, Alexander, et al.
Published: (2026)
N-Adaptive Ritz Method: A Neural Network Enriched Partition of Unity for Boundary Value Problems
by: Baek, Jonghyuk, et al.
Published: (2024)
by: Baek, Jonghyuk, et al.
Published: (2024)
Improving the Adaptive Moment Estimation (ADAM) stochastic optimizer through an Implicit-Explicit (IMEX) time-stepping approach
by: Bhattacharjee, Abhinab, et al.
Published: (2024)
by: Bhattacharjee, Abhinab, et al.
Published: (2024)
Graph Neural Regularizers for PDE Inverse Problems
by: Lauga, William, et al.
Published: (2025)
by: Lauga, William, et al.
Published: (2025)
Preconditioning for Accelerated Gradient Descent Optimization and Regularization
by: Ye, Qiang
Published: (2024)
by: Ye, Qiang
Published: (2024)
Efficient Differentiable Approximation of Generalized Low-rank Regularization
by: Li, Naiqi, et al.
Published: (2025)
by: Li, Naiqi, et al.
Published: (2025)
Number Theoretic Accelerated Learning of Physics-Informed Neural Networks
by: Matsubara, Takashi, et al.
Published: (2023)
by: Matsubara, Takashi, et al.
Published: (2023)
Learned Finite Element-based Regularization of the Inverse Problem in Electrocardiographic Imaging
by: Haas, Manuel, et al.
Published: (2026)
by: Haas, Manuel, et al.
Published: (2026)
Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains
by: Lingsch, Levi, et al.
Published: (2023)
by: Lingsch, Levi, et al.
Published: (2023)
Inverse Evolution Layers: Physics-informed Regularizers for Deep Neural Networks
by: Liu, Chaoyu, et al.
Published: (2023)
by: Liu, Chaoyu, et al.
Published: (2023)
Regularity of Second-Order Elliptic PDEs in Spectral Barron Spaces
by: Chen, Ziang, et al.
Published: (2026)
by: Chen, Ziang, et al.
Published: (2026)
SpectraKAN: Conditioning Spectral Operators
by: Cheng, Chun-Wun, et al.
Published: (2026)
by: Cheng, Chun-Wun, et al.
Published: (2026)
Invertible ResNets for Inverse Imaging Problems: Competitive Performance with Provable Regularization Properties
by: Arndt, Clemens, et al.
Published: (2024)
by: Arndt, Clemens, et al.
Published: (2024)
Mode-Shape Expansion Using Physics-Constrained Gaussian Process Regression
by: Ghahari, Farid
Published: (2026)
by: Ghahari, Farid
Published: (2026)
Shape-informed surrogate models based on signed distance function domain encoding
by: Zhang, Linying, et al.
Published: (2024)
by: Zhang, Linying, et al.
Published: (2024)
Provable Emergence of Deep Neural Collapse and Low-Rank Bias in $L^2$-Regularized Nonlinear Networks
by: Zangrando, Emanuele, et al.
Published: (2024)
by: Zangrando, Emanuele, et al.
Published: (2024)
A Distributed Block Chebyshev-Davidson Algorithm for Parallel Spectral Clustering
by: Pang, Qiyuan, et al.
Published: (2022)
by: Pang, Qiyuan, et al.
Published: (2022)
Monotone Peridynamic Neural Operator for Nonlinear Material Modeling with Conditionally Unique Solutions
by: Wang, Jihong, et al.
Published: (2025)
by: Wang, Jihong, et al.
Published: (2025)
Conditional Pseudo-Reversible Normalizing Flow for Surrogate Modeling in Quantifying Uncertainty Propagation
by: Yang, Minglei, et al.
Published: (2024)
by: Yang, Minglei, et al.
Published: (2024)
Barron Space Representations for Elliptic PDEs with Homogeneous Boundary Conditions
by: Chen, Ziang, et al.
Published: (2025)
by: Chen, Ziang, et al.
Published: (2025)
Hausdorff Moment Transforms and Their Performance
by: Wang, Xinyun, et al.
Published: (2022)
by: Wang, Xinyun, et al.
Published: (2022)
Shape Derivative-Informed Neural Operators with Application to Risk-Averse Shape Optimization
by: Gong, Xindi, et al.
Published: (2026)
by: Gong, Xindi, et al.
Published: (2026)
Fast Green Function Evaluation for Method of Moment
by: Yang, Shunchuan, et al.
Published: (2019)
by: Yang, Shunchuan, et al.
Published: (2019)
Controlling Statistical, Discretization, and Truncation Errors in Learning Fourier Linear Operators
by: Subedi, Unique, et al.
Published: (2024)
by: Subedi, Unique, et al.
Published: (2024)
Deep Reinforcement Learning for the Heat Transfer Control of Pulsating Impinging Jets
by: Salavatidezfouli, Sajad, et al.
Published: (2023)
by: Salavatidezfouli, Sajad, et al.
Published: (2023)
Quantitative Stability and Numerical Resolution of the Moment Measure Problem
by: Bonnet, Guillaume, et al.
Published: (2026)
by: Bonnet, Guillaume, et al.
Published: (2026)
Learning Regularization Functionals for Inverse Problems: A Comparative Study
by: Hertrich, Johannes, et al.
Published: (2025)
by: Hertrich, Johannes, et al.
Published: (2025)
A Neural-preconditioned Poisson Solver for Mixed Dirichlet and Neumann Boundary Conditions
by: Lan, Kai Weixian, et al.
Published: (2023)
by: Lan, Kai Weixian, et al.
Published: (2023)
Moments of Dirichlet splines and their applications to hypergeometric functions
by: Neuman, Edward, et al.
Published: (1993)
by: Neuman, Edward, et al.
Published: (1993)
Random Subspace Cubic-Regularization Methods, with Applications to Low-Rank Functions
by: Cartis, Coralia, et al.
Published: (2025)
by: Cartis, Coralia, et al.
Published: (2025)
Similar Items
-
Matrix Phylogeny: Compact Spectral Fingerprints for Trap-Robust Preconditioner Selection
by: Baek, Jinwoo
Published: (2025) -
Numerical Fragility in Transformers: A Layer-wise Theory for Explaining, Forecasting, and Mitigating Instability
by: Baek, Jinwoo
Published: (2025) -
Sketchy Moment Matching: Toward Fast and Provable Data Selection for Finetuning
by: Dong, Yijun, et al.
Published: (2024) -
Exact Gaussian Moment Matching for Residual Networks: a Second-Order Method
by: Kuang, Simon, et al.
Published: (2026) -
Beyond Muon: MUD (MomentUm Decorrelation) for Faster Transformer Training
by: Southworth, Ben S., et al.
Published: (2026)