Regret in polyhedral online convex optimization equals Θ(√((1+RS_T) T log V_max)) where RS_T counts active region switches.
A Decision - Theoretic Generalization of On - Line Learning and an Application to Boosting
6 Pith papers cite this work. Polarity classification is still indexing.
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2026 6representative citing papers
Presents MBFC-2025 dataset and multi-view embeddings with fusion methods for media bias and factuality, reporting SOTA results on ACL-2020 and new benchmarks on MBFC-2025.
One-pass algorithms achieve Õ(M²/ε) space for regression splits and Õ(1/ε) space for Gini splits with matching Ω lower bounds.
AgentGA optimizes agent seeds with genetic algorithms and parent-archive inheritance to improve autonomous code generation, beating a baseline on 15 of 16 Kaggle competitions.
LHCb reports first searches and the most stringent limits to date on rare decays such as b to s tau+ tau- and tau to three muons.
Nested cross-validation reveals optimistic bias in standard validation for EEG alcoholism classification, with AdaBoost reaching 78.3% accuracy and most model differences not statistically significant per McNemar's test.
citing papers explorer
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Polyhedral Instability Governs Regret in Online Learning
Regret in polyhedral online convex optimization equals Θ(√((1+RS_T) T log V_max)) where RS_T counts active region switches.
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A Multi-View Media Profiling Suite: Resources, Evaluation, and Analysis
Presents MBFC-2025 dataset and multi-view embeddings with fusion methods for media bias and factuality, reporting SOTA results on ACL-2020 and new benchmarks on MBFC-2025.
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Nearly Optimal Bounds for Computing Decision Tree Splits in Data Streams
One-pass algorithms achieve Õ(M²/ε) space for regression splits and Õ(1/ε) space for Gini splits with matching Ω lower bounds.
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AgentGA: Evolving Code Solutions in Agent-Seed Space
AgentGA optimizes agent seeds with genetic algorithms and parent-archive inheritance to improve autonomous code generation, beating a baseline on 15 of 16 Kaggle competitions.
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Rare and very rare decays at the LHCb experiment
LHCb reports first searches and the most stringent limits to date on rare decays such as b to s tau+ tau- and tau to three muons.
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Impact of Validation Strategy on Machine Learning Performance in EEG-Based Alcoholism Classification
Nested cross-validation reveals optimistic bias in standard validation for EEG alcoholism classification, with AdaBoost reaching 78.3% accuracy and most model differences not statistically significant per McNemar's test.