Unveiling the Cycloid Trajectory of EM Iterations in Mixed Linear Regression
Fuente:
arXiv
Saved in:
| Main Authors: | Luo, Zhankun, Hashemi, Abolfazl |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Structural Properties, Cycloid Trajectories and Non-Asymptotic Guarantees of EM Algorithm for Mixed Linear Regression
by: Luo, Zhankun, et al.
Published: (2025)
by: Luo, Zhankun, et al.
Published: (2025)
Characterizing Evolution in Expectation-Maximization Estimates for Overspecified Mixed Linear Regression
by: Luo, Zhankun, et al.
Published: (2025)
by: Luo, Zhankun, et al.
Published: (2025)
Iterative Reweighted Framework Based Algorithms for Sparse Linear Regression with Generalized Elastic Net Penalty
by: Ding, Yanyun, et al.
Published: (2024)
by: Ding, Yanyun, et al.
Published: (2024)
Minimax Linear Regression under the Quantile Risk
by: Hanchi, Ayoub El, et al.
Published: (2024)
by: Hanchi, Ayoub El, et al.
Published: (2024)
Online and Offline Robust Multivariate Linear Regression
by: Godichon-Baggioni, Antoine, et al.
Published: (2024)
by: Godichon-Baggioni, Antoine, et al.
Published: (2024)
Functional Linear Regression of Cumulative Distribution Functions
by: Zhang, Qian, et al.
Published: (2022)
by: Zhang, Qian, et al.
Published: (2022)
Max-Linear Regression by Convex Programming
by: Kim, Seonho, et al.
Published: (2021)
by: Kim, Seonho, et al.
Published: (2021)
Mixed Regression via Approximate Message Passing
by: Tan, Nelvin, et al.
Published: (2023)
by: Tan, Nelvin, et al.
Published: (2023)
On the Interpolation Error of Nonlinear Attention versus Linear Regression
by: Liao, Zhenyu, et al.
Published: (2025)
by: Liao, Zhenyu, et al.
Published: (2025)
Asymptotics of Random Feature Regression Beyond the Linear Scaling Regime
by: Hu, Hong, et al.
Published: (2024)
by: Hu, Hong, et al.
Published: (2024)
Improved Scaling Laws in Linear Regression via Data Reuse
by: Lin, Licong, et al.
Published: (2025)
by: Lin, Licong, et al.
Published: (2025)
Transfer Learning for Benign Overfitting in High-Dimensional Linear Regression
by: Kim, Yeichan, et al.
Published: (2025)
by: Kim, Yeichan, et al.
Published: (2025)
Self-Normalized Martingales and Uniform Regret Bounds for Linear Regression
by: Chen, Fan, et al.
Published: (2026)
by: Chen, Fan, et al.
Published: (2026)
Sharp Risk Bounds for Early-Stopping in Gaussian Linear Regression
by: Wegel, Tobias, et al.
Published: (2025)
by: Wegel, Tobias, et al.
Published: (2025)
TrIM: Transformed Iterative Mondrian Forests for Gradient-based Dimension Reduction and High-Dimensional Regression
by: Baptista, Ricardo, et al.
Published: (2024)
by: Baptista, Ricardo, et al.
Published: (2024)
Finite Sample Confidence Regions for Linear Regression Parameters Using Arbitrary Predictors
by: Guille-Escuret, Charles, et al.
Published: (2024)
by: Guille-Escuret, Charles, et al.
Published: (2024)
Estimating Generalization Performance Along the Trajectory of Proximal SGD in Robust Regression
by: Tan, Kai, et al.
Published: (2024)
by: Tan, Kai, et al.
Published: (2024)
Finite-Sample Inference for Sparsely Permuted Linear Regression
by: Ota, Hirofumi, et al.
Published: (2026)
by: Ota, Hirofumi, et al.
Published: (2026)
Optimal Excess Risk Bounds for Empirical Risk Minimization on $p$-Norm Linear Regression
by: Hanchi, Ayoub El, et al.
Published: (2023)
by: Hanchi, Ayoub El, et al.
Published: (2023)
The Thermodynamic Costs of Simple Linear Regression
by: D'Ambrosia, Samuel H., et al.
Published: (2026)
by: D'Ambrosia, Samuel H., et al.
Published: (2026)
Online Covariance Estimation in Averaged SGD: Improved Batch-Mean Rates and Minimax Optimality via Trajectory Regression
by: Ni, Yijin, et al.
Published: (2026)
by: Ni, Yijin, et al.
Published: (2026)
Precise Asymptotics for Spectral Methods in Mixed Generalized Linear Models
by: Zhang, Yihan, et al.
Published: (2022)
by: Zhang, Yihan, et al.
Published: (2022)
Batches Stabilize the Minimum Norm Risk in High Dimensional Overparameterized Linear Regression
by: Ioushua, Shahar Stein, et al.
Published: (2023)
by: Ioushua, Shahar Stein, et al.
Published: (2023)
Bivariate Matrix-valued Linear Regression (BMLR): Finite-sample performance under Identifiability and Sparsity Assumptions
by: Bettache, Nayel
Published: (2024)
by: Bettache, Nayel
Published: (2024)
Locally Near Optimal Piecewise Linear Regression in High Dimensions via Difference of Max-Affine Functions
by: Kanj, Haitham, et al.
Published: (2026)
by: Kanj, Haitham, et al.
Published: (2026)
Asymptotic Optimism for Tensor Regression Models with Applications to Neural Network Compression
by: Shi, Haoming, et al.
Published: (2026)
by: Shi, Haoming, et al.
Published: (2026)
Scaling Laws in Linear Regression: Compute, Parameters, and Data
by: Lin, Licong, et al.
Published: (2024)
by: Lin, Licong, et al.
Published: (2024)
Decentralized Sparse Linear Regression via Gradient-Tracking: Linear Convergence and Statistical Guarantees
by: Maros, Marie, et al.
Published: (2022)
by: Maros, Marie, et al.
Published: (2022)
Asymptotic Optimism of Random-Design Linear and Kernel Regression Models
by: Luo, Hengrui, et al.
Published: (2025)
by: Luo, Hengrui, et al.
Published: (2025)
Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions
by: Bing, Simon, et al.
Published: (2023)
by: Bing, Simon, et al.
Published: (2023)
A Computational Transition for Detecting Multivariate Shuffled Linear Regression by Low-Degree Polynomials
by: Li, Zhangsong
Published: (2025)
by: Li, Zhangsong
Published: (2025)
Preventing Model Collapse Under Overparametrization: Optimal Mixing Ratios for Interpolation Learning and Ridge Regression
by: Garg, Anvit, et al.
Published: (2025)
by: Garg, Anvit, et al.
Published: (2025)
Computational-Statistical Gaps for Improper Learning in Sparse Linear Regression
by: Buhai, Rares-Darius, et al.
Published: (2024)
by: Buhai, Rares-Darius, et al.
Published: (2024)
Trajectory-Restricted Optimization Conditions and Geometry-Aware Linear Convergence
by: Chaudhry, Faris, et al.
Published: (2026)
by: Chaudhry, Faris, et al.
Published: (2026)
Shuffled Linear Regression via Spectral Matching
by: Liu, Hang, et al.
Published: (2024)
by: Liu, Hang, et al.
Published: (2024)
Transformers Handle Endogeneity in In-Context Linear Regression
by: Liang, Haodong, et al.
Published: (2024)
by: Liang, Haodong, et al.
Published: (2024)
Sparse Linear Regression is Easy on Random Supports
by: Chandrasekaran, Gautam, et al.
Published: (2025)
by: Chandrasekaran, Gautam, et al.
Published: (2025)
Linear Regression under Missing or Corrupted Coordinates
by: Diakonikolas, Ilias, et al.
Published: (2025)
by: Diakonikolas, Ilias, et al.
Published: (2025)
Differentially Private Inference for Longitudinal Linear Regression
by: Sopa, Getoar, et al.
Published: (2026)
by: Sopa, Getoar, et al.
Published: (2026)
Finite-Sample Identification of Linear Regression Models with Residual-Permuted Sums
by: Szentpéteri, Szabolcs, et al.
Published: (2024)
by: Szentpéteri, Szabolcs, et al.
Published: (2024)
Similar Items
-
Structural Properties, Cycloid Trajectories and Non-Asymptotic Guarantees of EM Algorithm for Mixed Linear Regression
by: Luo, Zhankun, et al.
Published: (2025) -
Characterizing Evolution in Expectation-Maximization Estimates for Overspecified Mixed Linear Regression
by: Luo, Zhankun, et al.
Published: (2025) -
Iterative Reweighted Framework Based Algorithms for Sparse Linear Regression with Generalized Elastic Net Penalty
by: Ding, Yanyun, et al.
Published: (2024) -
Minimax Linear Regression under the Quantile Risk
by: Hanchi, Ayoub El, et al.
Published: (2024) -
Online and Offline Robust Multivariate Linear Regression
by: Godichon-Baggioni, Antoine, et al.
Published: (2024)