Cover Image

On Exact Learning of $d$-Monotone Functions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Bshouty, Nader H.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Data Structures and Algorithms
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Note on Second-Order Expected Maximum-Load Bounds for Binary Linear Hashing
by: Bshouty, Nader H.
Published: (2026)

Classes Testable with $O(1/ε)$ Queries for Small $ε$ Independent of the Number of Variables
by: Bshouty, Nader H., et al.
Published: (2026)

Learning with Monotone Adversarial Corruptions
by: Larsen, Kasper Green, et al.
Published: (2026)

Semi-Bandit Learning for Monotone Stochastic Optimization
by: Agarwal, Arpit, et al.
Published: (2023)

Exact Learning of Weighted Graphs Using Composite Queries
by: Goodrich, Michael T., et al.
Published: (2025)

Practical Parallel Algorithms for Non-Monotone Submodular Maximization
by: Cui, Shuang, et al.
Published: (2023)

Fairness in Monotone $k$-submodular Maximization: Algorithms and Applications
by: Zhu, Yanhui, et al.
Published: (2024)

Deletion Robust Non-Monotone Submodular Maximization over Matroids
by: Dütting, Paul, et al.
Published: (2022)

Practical and Parallelizable Algorithms for Non-Monotone Submodular Maximization with Size Constraint
by: Chen, Yixin, et al.
Published: (2020)

Fast Adaptive Non-Monotone Submodular Maximization Subject to a Knapsack Constraint
by: Amanatidis, Georgios, et al.
Published: (2020)

Learning and Testing Convex Functions
by: Pinto Jr., Renato Ferreira, et al.
Published: (2025)

Exact multiplicative updates for convolutional $β$-NMF in 2D
by: T., Pedro J. Villasana, et al.
Published: (2018)

Collaborative Learning with Different Labeling Functions
by: Deng, Yuyang, et al.
Published: (2024)

Testably Learning Polynomial Threshold Functions
by: Slot, Lucas, et al.
Published: (2024)

On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries
by: Joshi, Nirmit, et al.
Published: (2024)

Exact and Approximate Algorithms for Polytree Learning
by: Harviainen, Juha, et al.
Published: (2026)

Attribute-Efficient PAC Learning of Low-Degree Polynomial Threshold Functions with Nasty Noise
by: Zeng, Shiwei, et al.
Published: (2023)

A $d^{1/2+o(1)}$ Monotonicity Tester for Boolean Functions on $d$-Dimensional Hypergrids
by: Black, Hadley, et al.
Published: (2023)

Learned Static Function Data Structures
by: Hermann, Stefan, et al.
Published: (2025)

Chasing Convex Functions with Long-term Constraints
by: Lechowicz, Adam, et al.
Published: (2024)

Optimal Approximation -- Smoothness Tradeoffs for Soft-Max Functions
by: Epasto, Alessandro, et al.
Published: (2020)

Curvature Beyond Positivity: Greedy Guarantees for Arbitrary Submodular Functions
by: Chen, Yixin, et al.
Published: (2026)

Exact Causal Attention with 10% Fewer Operations
by: Rybin, Dmitry, et al.
Published: (2025)

Learning on the Edge: Online Learning with Stochastic Feedback Graphs
by: Esposito, Emmanuel, et al.
Published: (2022)

No-Regret M${}^{\natural}$-Concave Function Maximization: Stochastic Bandit Algorithms and Hardness of Adversarial Full-Information Setting
by: Oki, Taihei, et al.
Published: (2024)

Learning-Augmented Algorithms for $k$-median via Online Learning
by: Hebbar, Anish, et al.
Published: (2026)

Learned LSM-trees: Two Approaches Using Learned Bloom Filters
by: Fidalgo, Nicholas, et al.
Published: (2025)

Learning-Augmented Hierarchical Clustering
by: Braverman, Vladimir, et al.
Published: (2025)

Learning-Augmented Frequent Directions
by: Aamand, Anders, et al.
Published: (2025)

Active Learning with Simple Questions
by: Kontonis, Vasilis, et al.
Published: (2024)

Testable Learning with Distribution Shift
by: Klivans, Adam R., et al.
Published: (2023)

Learning the Positions in CountSketch
by: Li, Yi, et al.
Published: (2023)

Learning Low Degree Hypergraphs
by: Balkanski, Eric, et al.
Published: (2022)

Robust Learning-Augmented Dictionaries
by: Zeynali, Ali, et al.
Published: (2024)

Robust Learning with Optimal Error
by: Blanc, Guy
Published: (2026)

Learning Augmented Graph $k$-Clustering
by: Fan, Chenglin, et al.
Published: (2025)

Online Learning in the Random Order Model
by: Bernasconi, Martino, et al.
Published: (2025)

Testing Noise Assumptions of Learning Algorithms
by: Goel, Surbhi, et al.
Published: (2025)

Limitations of Membership Queries in Testable Learning
by: Lange, Jane, et al.
Published: (2025)

Transductive and Learning-Augmented Online Regression
by: Raman, Vinod, et al.
Published: (2025)