Cover Image

Adversarial Resilience in Sequential Prediction via Abstention

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Goel, Surbhi, Hanneke, Steve, Moran, Shay, Shetty, Abhishek
Format:	Preprint
Published:	2023
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

Tolerant Algorithms for Learning with Arbitrary Covariate Shift
by: Goel, Surbhi, et al.
Published: (2024)

Private List Learnability vs. Online List Learnability
by: Hanneke, Steve, et al.
Published: (2025)

PAC Learning with Bandit Feedback: Sharp Sample Complexity in the Realizable Setting
by: Hanneke, Steve, et al.
Published: (2026)

Distribution-Free Sequential Prediction with Abstentions
by: Yu, Jialin, et al.
Published: (2026)

On the Learning Curves of Revenue Maximization
by: Hanneke, Steve, et al.
Published: (2026)

Ramsey Theorems for Trees and a General 'Private Learning Implies Online Learning' Theorem
by: Fioravanti, Simone, et al.
Published: (2024)

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

Tradeoffs between Mistakes and ERM Oracle Calls in Online and Transductive Online Learning
by: Attias, Idan, et al.
Published: (2025)

Stochastic Bandits with ReLU Neural Networks
by: Xu, Kan, et al.
Published: (2024)

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

Learning-Augmented Algorithms with Explicit Predictors
by: Elias, Marek, et al.
Published: (2024)

Provably Learning from Modern Language Models via Low Logit Rank
by: Golowich, Noah, et al.
Published: (2025)

Revisiting Agnostic PAC Learning
by: Hanneke, Steve, et al.
Published: (2024)

Collaborative Prediction: Tractable Information Aggregation via Agreement
by: Collina, Natalie, et al.
Published: (2025)

On the Distance from Calibration in Sequential Prediction
by: Qiao, Mingda, et al.
Published: (2024)

Taming Imperfect Process Verifiers: A Sampling Perspective on Backtracking
by: Rohatgi, Dhruv, et al.
Published: (2025)

What is Learnable in Valiant's Theory of the Learnable?
by: Hanneke, Steve, et al.
Published: (2026)

Tractable Agreement Protocols
by: Collina, Natalie, et al.
Published: (2024)

Omnipredictors for Regression and the Approximate Rank of Convex Functions
by: Gopalan, Parikshit, et al.
Published: (2024)

Breaking the $T^{2/3}$ Barrier for Sequential Calibration
by: Dagan, Yuval, 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)

Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures
by: Gao, Jie, et al.
Published: (2025)

Spectral Guarantees for Adversarial Streaming PCA
by: Price, Eric, et al.
Published: (2024)

Improving Online Algorithms via ML Predictions
by: Kumar, Ravi, et al.
Published: (2024)

Fast-MWEM: Private Data Release in Sublinear Time
by: Haris, Themistoklis, et al.
Published: (2026)

Adversarial Attacks on Combinatorial Multi-Armed Bandits
by: Balasubramanian, Rishab, et al.
Published: (2023)

Smooth Nash Equilibria: Algorithms and Complexity
by: Daskalakis, Constantinos, et al.
Published: (2023)

Efficient Testable Learning of General Halfspaces with Adversarial Label Noise
by: Diakonikolas, Ilias, et al.
Published: (2024)

On the Adversarial Robustness of Online Importance Sampling
by: Kenneth-Mordoch, Yotam, et al.
Published: (2025)

Fully Dynamic Adversarially Robust Correlation Clustering in Polylogarithmic Update Time
by: Braverman, Vladimir, et al.
Published: (2024)

Fast White-Box Adversarial Streaming Without a Random Oracle
by: Feng, Ying, et al.
Published: (2024)

The Art of Being Difficult: Combining Human and AI Strengths to Find Adversarial Instances for Heuristics
by: Nikoleit, Henri, et al.
Published: (2026)

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

Online Classification with Predictions
by: Raman, Vinod, et al.
Published: (2024)

Energy-Efficient Scheduling with Predictions
by: Balkanski, Eric, et al.
Published: (2024)

Online Prediction with Limited Selectivity
by: Liu, Licheng, et al.
Published: (2025)

Binary Search with Distributional Predictions
by: Dinitz, Michael, et al.
Published: (2024)

Fair Secretaries with Unfair Predictions
by: Balkanski, Eric, et al.
Published: (2024)

Connectivity Oracles for Predictable Vertex Failures
by: Hu, Bingbing, et al.
Published: (2023)

Online Algorithms with Uncertainty-Quantified Predictions
by: Sun, Bo, et al.
Published: (2023)