boosting algorithm

Boosting with List-Decodable Codes COLT 2026 Distribution-Free Sequential Prediction with Abstentions COLT 2026 Improved Replicable Boosting with Majority-of-Majorities ALT 2026 Neural Routed Boosting: Robust Learning against Heteroscedastic Noise UAI 2026 Boosting Causal Additive Models JMLR 2025 Kernel-based L_2-Boosting with Structure Constraints JMLR 2025 A Boosting-Type Convergence Result for AdaBoost.MH with Factorized Multi-Class Classifiers NeurIPS 2024 Efficient Quantum Agnostic Improper Learning of Decision Trees AISTATS 2024 Optimal Parallelization of Boosting NeurIPS 2024 Sample-Efficient Agnostic Boosting NeurIPS 2024 The Many Faces of Optimal Weak-to-Strong Learning NeurIPS 2024 AdaBoost is not an Optimal Weak to Strong Learner ICML 2023 Boosted Off-Policy Learning AISTATS 2023 Fair Densities via Boosting the Sufficient Statistics of Exponential Families ICML 2023 Gap Minimization for Knowledge Sharing and Transfer JMLR 2023 Multitask Learning via Shared Features: Algorithms and Hardness COLT 2023 On the Robustness of Randomized Ensembles to Adversarial Perturbations ICML 2023 Random Classification Noise does not defeat All Convex Potential Boosters Irrespective of Model Choice ICML 2023 A Resilient Distributed Boosting Algorithm ICML 2022 Being Properly Improper ICML 2022 ExactBoost: Directly Boosting the Margin in Combinatorial and Non-decomposable Metrics AISTATS 2022 Fair Wrapping for Black-box Predictions NeurIPS 2022 Online Agnostic Multiclass Boosting NeurIPS 2022 Optimal Weak to Strong Learning NeurIPS 2022 Boosted CVaR Classification NeurIPS 2021