OKRidge: Scalable Optimal k-Sparse Ridge Regression
Fuente:
arXiv
Saved in:
| Main Authors: | Liu, Jiachang, Rosen, Sam, Zhong, Chudi, Rudin, Cynthia |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Models That Are Interpretable But Not Transparent
by: Zhong, Chudi, et al.
Published: (2025)
by: Zhong, Chudi, et al.
Published: (2025)
Scalable First-order Method for Certifying Optimal k-Sparse GLMs
by: Liu, Jiachang, et al.
Published: (2025)
by: Liu, Jiachang, et al.
Published: (2025)
FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models
by: Liu, Jiachang, et al.
Published: (2024)
by: Liu, Jiachang, et al.
Published: (2024)
From Sequential Nodes to GPU Batches: Parallel Branch and Bound for Optimal $k$-Sparse GLMs
by: Liu, Jiachang, et al.
Published: (2026)
by: Liu, Jiachang, et al.
Published: (2026)
Optimal Sparse Survival Trees
by: Zhang, Rui, et al.
Published: (2024)
by: Zhang, Rui, et al.
Published: (2024)
Amazing Things Come From Having Many Good Models
by: Rudin, Cynthia, et al.
Published: (2024)
by: Rudin, Cynthia, et al.
Published: (2024)
Sparse and Faithful Explanations Without Sparse Models
by: Sun, Yiyang, et al.
Published: (2024)
by: Sun, Yiyang, et al.
Published: (2024)
GPU-friendly and Linearly Convergent First-order Methods for Certifying Optimal $k$-sparse GLMs
by: Liu, Jiachang, et al.
Published: (2026)
by: Liu, Jiachang, et al.
Published: (2026)
Leo Breiman, the Rashomon Effect, and the Occam Dilemma
by: Rudin, Cynthia
Published: (2025)
by: Rudin, Cynthia
Published: (2025)
Fast and Interpretable Mortality Risk Scores for Critical Care Patients
by: Zhu, Chloe Qinyu, et al.
Published: (2023)
by: Zhu, Chloe Qinyu, et al.
Published: (2023)
Near Optimal Decision Trees in a SPLIT Second
by: Babbar, Varun, et al.
Published: (2025)
by: Babbar, Varun, et al.
Published: (2025)
The Double-Edged Nature of the Rashomon Set for Trustworthy Machine Learning
by: Hsu, Ethan, et al.
Published: (2025)
by: Hsu, Ethan, et al.
Published: (2025)
Optimal Rates and Saturation for Noiseless Kernel Ridge Regression
by: Long, Jihao, et al.
Published: (2024)
by: Long, Jihao, et al.
Published: (2024)
Resolving Predictive Multiplicity for the Rashomon Set
by: Haghighat, Parian, et al.
Published: (2026)
by: Haghighat, Parian, et al.
Published: (2026)
Sparse learned kernels for interpretable and efficient medical time series processing
by: Chen, Sully F., et al.
Published: (2023)
by: Chen, Sully F., et al.
Published: (2023)
"What is Different Between These Datasets?" A Framework for Explaining Data Distribution Shifts
by: Babbar, Varun, et al.
Published: (2024)
by: Babbar, Varun, et al.
Published: (2024)
Navigating the Effect of Parametrization for Dimensionality Reduction
by: Huang, Haiyang, et al.
Published: (2024)
by: Huang, Haiyang, et al.
Published: (2024)
Improving Decision Sparsity
by: Sun, Yiyang, et al.
Published: (2024)
by: Sun, Yiyang, et al.
Published: (2024)
Optimal Rates of Kernel Ridge Regression under Source Condition in Large Dimensions
by: Zhang, Haobo, et al.
Published: (2024)
by: Zhang, Haobo, et al.
Published: (2024)
Doctor Rashomon and the UNIVERSE of Madness: Variable Importance with Unobserved Confounding and the Rashomon Effect
by: Donnelly, Jon, et al.
Published: (2025)
by: Donnelly, Jon, et al.
Published: (2025)
Dimension Reduction with Locally Adjusted Graphs
by: Wang, Yingfan, et al.
Published: (2024)
by: Wang, Yingfan, et al.
Published: (2024)
Affinity Graph Connectivity in Convex Clustering
by: Rosen, Sam, et al.
Published: (2026)
by: Rosen, Sam, et al.
Published: (2026)
Optimal and Structure-Adaptive CATE Estimation with Kernel Ridge Regression
by: Kim, Seok-Jin
Published: (2026)
by: Kim, Seok-Jin
Published: (2026)
Transfer Learning of CATE with Kernel Ridge Regression
by: Kim, Seok-Jin, et al.
Published: (2025)
by: Kim, Seok-Jin, et al.
Published: (2025)
The Rashomon Effect for Visualizing High-Dimensional Data
by: Sun, Yiyang, et al.
Published: (2026)
by: Sun, Yiyang, et al.
Published: (2026)
Interpretable Generalized Additive Models for Datasets with Missing Values
by: McTavish, Hayden, et al.
Published: (2024)
by: McTavish, Hayden, et al.
Published: (2024)
Optimal Cross-Validation for Sparse Linear Regression
by: Cory-Wright, Ryan, et al.
Published: (2023)
by: Cory-Wright, Ryan, et al.
Published: (2023)
Data Fusion for Partial Identification of Causal Effects
by: Lanners, Quinn, et al.
Published: (2025)
by: Lanners, Quinn, et al.
Published: (2025)
On the Saturation Effect of Kernel Ridge Regression
by: Li, Yicheng, et al.
Published: (2024)
by: Li, Yicheng, et al.
Published: (2024)
Safe and Interpretable Estimation of Optimal Treatment Regimes
by: Parikh, Harsh, et al.
Published: (2023)
by: Parikh, Harsh, et al.
Published: (2023)
The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance
by: Donnelly, Jon, et al.
Published: (2023)
by: Donnelly, Jon, et al.
Published: (2023)
Trustworthy Feature Importance Avoids Unrestricted Permutations
by: Borgonovo, Emanuele, et al.
Published: (2026)
by: Borgonovo, Emanuele, et al.
Published: (2026)
Kernel Ridge Regression Inference
by: Singh, Rahul, et al.
Published: (2023)
by: Singh, Rahul, et al.
Published: (2023)
Interpretable Causal Inference for Analyzing Wearable, Sensor, and Distributional Data
by: Katta, Srikar, et al.
Published: (2023)
by: Katta, Srikar, et al.
Published: (2023)
Optimal Multitask Linear Regression and Contextual Bandits under Sparse Heterogeneity
by: Huang, Xinmeng, et al.
Published: (2023)
by: Huang, Xinmeng, et al.
Published: (2023)
Scalable Sparse Regression for Model Discovery: The Fast Lane to Insight
by: Golden, Matthew
Published: (2024)
by: Golden, Matthew
Published: (2024)
Test Set Sizing for the Ridge Regression
by: Dubbs, Alexander
Published: (2025)
by: Dubbs, Alexander
Published: (2025)
Lepskii Principle for Distributed Kernel Ridge Regression
by: Lin, Shao-Bo
Published: (2024)
by: Lin, Shao-Bo
Published: (2024)
To Grok Grokking: Provable Grokking in Ridge Regression
by: Xu, Mingyue, et al.
Published: (2026)
by: Xu, Mingyue, et al.
Published: (2026)
Cubit: Token Mixer with Kernel Ridge Regression
by: Zheng, Chuanyang, et al.
Published: (2026)
by: Zheng, Chuanyang, et al.
Published: (2026)
Similar Items
-
Models That Are Interpretable But Not Transparent
by: Zhong, Chudi, et al.
Published: (2025) -
Scalable First-order Method for Certifying Optimal k-Sparse GLMs
by: Liu, Jiachang, et al.
Published: (2025) -
FastSurvival: Hidden Computational Blessings in Training Cox Proportional Hazards Models
by: Liu, Jiachang, et al.
Published: (2024) -
From Sequential Nodes to GPU Batches: Parallel Branch and Bound for Optimal $k$-Sparse GLMs
by: Liu, Jiachang, et al.
Published: (2026) -
Optimal Sparse Survival Trees
by: Zhang, Rui, et al.
Published: (2024)