A Simple Approximation Algorithm for Optimal Decision Tree
Fuente:
arXiv
Saved in:
| Main Authors: | Zhuo, Zhengjia, Nagarajan, Viswanath |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Semi-Bandit Learning for Monotone Stochastic Optimization
by: Agarwal, Arpit, et al.
Published: (2023)
by: Agarwal, Arpit, et al.
Published: (2023)
Lower Bound on the Greedy Approximation Ratio for Adaptive Submodular Cover
by: Harris, Blake, et al.
Published: (2024)
by: Harris, Blake, et al.
Published: (2024)
Minimum Cost Adaptive Submodular Cover
by: Al-Thani, Hessa, et al.
Published: (2022)
by: Al-Thani, Hessa, et al.
Published: (2022)
Identifying Approximate Minimizers under Stochastic Uncertainty
by: Al-Thani, Hessa, et al.
Published: (2025)
by: Al-Thani, Hessa, et al.
Published: (2025)
Distributionally Robust $k$-of-$n$ Sequential Testing
by: Tan, Rayen, et al.
Published: (2026)
by: Tan, Rayen, et al.
Published: (2026)
Approximation Algorithms for D-optimal Design
by: Singh, Mohit, et al.
Published: (2018)
by: Singh, Mohit, et al.
Published: (2018)
Approximation Algorithms for Combinatorial Optimization with Predictions
by: Antoniadis, Antonios, et al.
Published: (2024)
by: Antoniadis, Antonios, et al.
Published: (2024)
An Approximation Algorithm for Graph Label Selection
by: John, Josia, et al.
Published: (2026)
by: John, Josia, et al.
Published: (2026)
Near-Optimal Algorithms for Omniprediction
by: Okoroafor, Princewill, et al.
Published: (2025)
by: Okoroafor, Princewill, et al.
Published: (2025)
Optimal Approximate Matrix Multiplication over Sliding Windows
by: Yao, Ziqi, et al.
Published: (2025)
by: Yao, Ziqi, et al.
Published: (2025)
Optimal Approximation -- Smoothness Tradeoffs for Soft-Max Functions
by: Epasto, Alessandro, et al.
Published: (2020)
by: Epasto, Alessandro, et al.
Published: (2020)
A Faster $k$-means++ Algorithm
by: Liang, Jiehao, et al.
Published: (2022)
by: Liang, Jiehao, et al.
Published: (2022)
Decision-Theoretic Approaches for Improved Learning-Augmented Algorithms
by: Angelopoulos, Spyros, et al.
Published: (2025)
by: Angelopoulos, Spyros, et al.
Published: (2025)
Constant-Factor Approximation for the Uniform Decision Tree
by: Szyfelbein, Michał
Published: (2026)
by: Szyfelbein, Michał
Published: (2026)
Sequential Testing with Subadditive Costs
by: Harris, Blake, et al.
Published: (2025)
by: Harris, Blake, et al.
Published: (2025)
Optimal Algorithms for Augmented Testing of Discrete Distributions
by: Aliakbarpour, Maryam, et al.
Published: (2024)
by: Aliakbarpour, Maryam, et al.
Published: (2024)
MAGNOLIA: Matching Algorithms via GNNs for Online Value-to-go Approximation
by: Hayderi, Alexandre, et al.
Published: (2024)
by: Hayderi, Alexandre, et al.
Published: (2024)
Optimal Prediction-Augmented Algorithms for Testing Independence of Distributions
by: Aliakbarpour, Maryam, et al.
Published: (2026)
by: Aliakbarpour, Maryam, et al.
Published: (2026)
Overcoming Brittleness in Pareto-Optimal Learning-Augmented Algorithms
by: Angelopoulos, Spyros, et al.
Published: (2024)
by: Angelopoulos, Spyros, et al.
Published: (2024)
Sublinear Time Algorithm for Online Weighted Bipartite Matching
by: Hu, Hang, et al.
Published: (2022)
by: Hu, Hang, et al.
Published: (2022)
Approximately Optimal Core Shapes for Tensor Decompositions
by: Ghadiri, Mehrdad, et al.
Published: (2023)
by: Ghadiri, Mehrdad, et al.
Published: (2023)
Precedence-Constrained Decision Trees and Coverings
by: Szyfelbein, Michał, et al.
Published: (2026)
by: Szyfelbein, Michał, et al.
Published: (2026)
Online Algorithms for Repeated Optimal Stopping: Balancing Baseline Guarantees and Regret
by: Harada, Tsubasa, et al.
Published: (2025)
by: Harada, Tsubasa, et al.
Published: (2025)
On Computing Optimal Tree Ensembles
by: Komusiewicz, Christian, et al.
Published: (2023)
by: Komusiewicz, Christian, et al.
Published: (2023)
Learning Small Decision Trees with Few Outliers: A Parameterized Perspective
by: Gahlawat, Harmender, et al.
Published: (2025)
by: Gahlawat, Harmender, et al.
Published: (2025)
Approximate Tree Completion and Learning-Augmented Algorithms for Metric Minimum Spanning Trees
by: Veldt, Nate, et al.
Published: (2025)
by: Veldt, Nate, et al.
Published: (2025)
Active Learning with Simple Questions
by: Kontonis, Vasilis, et al.
Published: (2024)
by: Kontonis, Vasilis, et al.
Published: (2024)
Are Graph Neural Networks Optimal Approximation Algorithms?
by: Yau, Morris, et al.
Published: (2023)
by: Yau, Morris, et al.
Published: (2023)
Fast and Simple Densest Subgraph with Predictions
by: Bui, Thai, et al.
Published: (2025)
by: Bui, Thai, et al.
Published: (2025)
A Simple Sparse Matrix Vector Multiplication Approach to Padded Convolution
by: Chaudhry, Zan
Published: (2024)
by: Chaudhry, Zan
Published: (2024)
Exact and Approximate Algorithms for Polytree Learning
by: Harviainen, Juha, et al.
Published: (2026)
by: Harviainen, Juha, et al.
Published: (2026)
A Simple Learning-Augmented Algorithm for Online Packing with Concave Objectives
by: Grigorescu, Elena, et al.
Published: (2024)
by: Grigorescu, Elena, et al.
Published: (2024)
Simple KNN-Based Outlier Detection Achieves Robust Clustering
by: Jiang, Tianle, et al.
Published: (2026)
by: Jiang, Tianle, et al.
Published: (2026)
Sublinear Time Quantum Algorithm for Attention Approximation
by: Song, Zhao, et al.
Published: (2026)
by: Song, Zhao, et al.
Published: (2026)
Efficient Calibration for Decision Making
by: Gopalan, Parikshit, et al.
Published: (2025)
by: Gopalan, Parikshit, et al.
Published: (2025)
Smooth Calibration and Decision Making
by: Hartline, Jason, et al.
Published: (2025)
by: Hartline, Jason, et al.
Published: (2025)
Calibration Error for Decision Making
by: Hu, Lunjia, et al.
Published: (2024)
by: Hu, Lunjia, et al.
Published: (2024)
A Faster Generalized Two-Stage Approximate Top-K
by: Samaga, Yashas, et al.
Published: (2025)
by: Samaga, Yashas, et al.
Published: (2025)
Guessing Efficiently for Constrained Subspace Approximation
by: Bhaskara, Aditya, et al.
Published: (2025)
by: Bhaskara, Aditya, et al.
Published: (2025)
The Space Complexity of Approximating Logistic Loss
by: Dexter, Gregory, et al.
Published: (2024)
by: Dexter, Gregory, et al.
Published: (2024)
Similar Items
-
Semi-Bandit Learning for Monotone Stochastic Optimization
by: Agarwal, Arpit, et al.
Published: (2023) -
Lower Bound on the Greedy Approximation Ratio for Adaptive Submodular Cover
by: Harris, Blake, et al.
Published: (2024) -
Minimum Cost Adaptive Submodular Cover
by: Al-Thani, Hessa, et al.
Published: (2022) -
Identifying Approximate Minimizers under Stochastic Uncertainty
by: Al-Thani, Hessa, et al.
Published: (2025) -
Distributionally Robust $k$-of-$n$ Sequential Testing
by: Tan, Rayen, et al.
Published: (2026)