Learning and Testing Convex Functions
Fuente:
arXiv
Saved in:
| Main Authors: | Pinto Jr., Renato Ferreira, Marcussen, Cassandra, Mossel, Elchanan, Nadimpalli, Shivam |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Better Models and Algorithms for Learning Ising Models from Dynamics
by: Gaitonde, Jason, et al.
Published: (2025)
by: Gaitonde, Jason, et al.
Published: (2025)
Bypassing the Noisy Parity Barrier: Learning Higher-Order Markov Random Fields from Dynamics
by: Gaitonde, Jason, et al.
Published: (2024)
by: Gaitonde, Jason, et al.
Published: (2024)
Finding the root in random nearest neighbor trees
by: Brandenberger, Anna, et al.
Published: (2024)
by: Brandenberger, Anna, et al.
Published: (2024)
Sample-Efficient Linear Regression with Self-Selection Bias
by: Gaitonde, Jason, et al.
Published: (2024)
by: Gaitonde, Jason, et al.
Published: (2024)
Testing Support Size More Efficiently Than Learning Histograms
by: Pinto Jr., Renato Ferreira, et al.
Published: (2024)
by: Pinto Jr., Renato Ferreira, et al.
Published: (2024)
Errors are Robustly Tamed in Cumulative Knowledge Processes
by: Brandenberger, Anna, et al.
Published: (2023)
by: Brandenberger, Anna, et al.
Published: (2023)
Finding the Root in Random Nearest Neighbor Trees
by: Anna Brandenberger, et al.
Published: (2026)
by: Anna Brandenberger, et al.
Published: (2026)
Quality control in sublinear time: a case study via random graphs
by: Marcussen, Cassandra, et al.
Published: (2025)
by: Marcussen, Cassandra, et al.
Published: (2025)
Optimal Non-Adaptive Tolerant Junta Testing via Local Estimators
by: Nadimpalli, Shivam, et al.
Published: (2024)
by: Nadimpalli, Shivam, et al.
Published: (2024)
On Algorithmic Robustness of Corrupted Markov Chains
by: Gaitonde, Jason, et al.
Published: (2025)
by: Gaitonde, Jason, et al.
Published: (2025)
Testing Convex Truncation
by: De, Anindya, et al.
Published: (2023)
by: De, Anindya, et al.
Published: (2023)
Lower Bounds for Convexity Testing
by: Chen, Xi, et al.
Published: (2024)
by: Chen, Xi, et al.
Published: (2024)
Comparison Theorems for the Mixing Times of Systematic and Random Scan Dynamics
by: Gaitonde, Jason, et al.
Published: (2024)
by: Gaitonde, Jason, et al.
Published: (2024)
Directed Isoperimetry and Monotonicity Testing: A Dynamical Approach
by: Pinto Jr, Renato Ferreira
Published: (2024)
by: Pinto Jr, Renato Ferreira
Published: (2024)
Influence Maximization in Ising Models
by: Chen, Zongchen, et al.
Published: (2023)
by: Chen, Zongchen, et al.
Published: (2023)
Sparsifying Suprema of Gaussian Processes
by: De, Anindya, et al.
Published: (2024)
by: De, Anindya, et al.
Published: (2024)
Chasing Convex Functions with Long-term Constraints
by: Lechowicz, Adam, et al.
Published: (2024)
by: Lechowicz, Adam, et al.
Published: (2024)
DNF Learning via Locally Mixing Random Walks
by: Alman, Josh, et al.
Published: (2025)
by: Alman, Josh, et al.
Published: (2025)
Reconstructing Riemannian Metrics From Random Geometric Graphs
by: Huang, Han, et al.
Published: (2025)
by: Huang, Han, et al.
Published: (2025)
Faster exact learning of k-term DNFs with membership and equivalence queries
by: Alman, Josh, et al.
Published: (2025)
by: Alman, Josh, et al.
Published: (2025)
The Power of Two Matrices in Spectral Algorithms for Community Recovery
by: Dhara, Souvik, et al.
Published: (2022)
by: Dhara, Souvik, et al.
Published: (2022)
Testing with Non-identically Distributed Samples
by: Garg, Shivam, et al.
Published: (2023)
by: Garg, Shivam, et al.
Published: (2023)
No Price Tags? No Problem: Query Strategies for Unpriced Information
by: Nadimpalli, Shivam, et al.
Published: (2025)
by: Nadimpalli, Shivam, et al.
Published: (2025)
Computational Complexity in Property Testing
by: Pinto Jr., Renato Ferreira, et al.
Published: (2025)
by: Pinto Jr., Renato Ferreira, et al.
Published: (2025)
Testing noisy low-degree polynomials for sparsity
by: Bao, Yiqiao, et al.
Published: (2025)
by: Bao, Yiqiao, et al.
Published: (2025)
Testing Sumsets is Hard
by: Chen, Xi, et al.
Published: (2024)
by: Chen, Xi, et al.
Published: (2024)
Omnipredictors for Regression and the Approximate Rank of Convex Functions
by: Gopalan, Parikshit, et al.
Published: (2024)
by: Gopalan, Parikshit, et al.
Published: (2024)
Near-optimal Swap Regret Minimization for Convex Losses
by: Hu, Lunjia, et al.
Published: (2026)
by: Hu, Lunjia, et al.
Published: (2026)
Testing Noise Assumptions of Learning Algorithms
by: Goel, Surbhi, et al.
Published: (2025)
by: Goel, Surbhi, et al.
Published: (2025)
Optimal Bounds for Adversarial Constrained Online Convex Optimization
by: Ferreira, Ricardo N., et al.
Published: (2025)
by: Ferreira, Ricardo N., et al.
Published: (2025)
Efficient Discrepancy Testing for Learning with Distribution Shift
by: Chandrasekaran, Gautam, et al.
Published: (2024)
by: Chandrasekaran, Gautam, et al.
Published: (2024)
On Exact Learning of $d$-Monotone Functions
by: Bshouty, Nader H.
Published: (2025)
by: Bshouty, Nader H.
Published: (2025)
Collaborative Learning with Different Labeling Functions
by: Deng, Yuyang, et al.
Published: (2024)
by: Deng, Yuyang, et al.
Published: (2024)
Testably Learning Polynomial Threshold Functions
by: Slot, Lucas, et al.
Published: (2024)
by: Slot, Lucas, et al.
Published: (2024)
Learning-Augmented Online Bipartite Matching in the Random Arrival Order Model
by: Burathep, Kunanon, et al.
Published: (2025)
by: Burathep, Kunanon, et al.
Published: (2025)
Capacity Provisioning Motivated Online Non-Convex Optimization Problem with Memory and Switching Cost
by: Vaze, Rahul, et al.
Published: (2024)
by: Vaze, Rahul, et al.
Published: (2024)
$O(\sqrt{T})$ Static Regret and Instance Dependent Constraint Violation for Constrained Online Convex Optimization
by: Vaze, Rahul, et al.
Published: (2025)
by: Vaze, Rahul, et al.
Published: (2025)
On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries
by: Joshi, Nirmit, et al.
Published: (2024)
by: Joshi, Nirmit, et al.
Published: (2024)
Finite and Corruption-Robust Regret Bounds in Online Inverse Linear Optimization under M-Convex Action Sets
by: Oki, Taihei, et al.
Published: (2026)
by: Oki, Taihei, et al.
Published: (2026)
Log-concave Sampling from a Convex Body with a Barrier: a Robust and Unified Dikin Walk
by: Gu, Yuzhou, et al.
Published: (2024)
by: Gu, Yuzhou, et al.
Published: (2024)
Similar Items
-
Better Models and Algorithms for Learning Ising Models from Dynamics
by: Gaitonde, Jason, et al.
Published: (2025) -
Bypassing the Noisy Parity Barrier: Learning Higher-Order Markov Random Fields from Dynamics
by: Gaitonde, Jason, et al.
Published: (2024) -
Finding the root in random nearest neighbor trees
by: Brandenberger, Anna, et al.
Published: (2024) -
Sample-Efficient Linear Regression with Self-Selection Bias
by: Gaitonde, Jason, et al.
Published: (2024) -
Testing Support Size More Efficiently Than Learning Histograms
by: Pinto Jr., Renato Ferreira, et al.
Published: (2024)