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weak-learning

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DhruvSrikanth / Boosting-Theory

A collection of papers produced on the theory of boosting as applied to binary classification. Further extensions to the multi-class classification problem and necessary and sufficient conditions to ensure boostability i.e. weak learning conditions. Finally, an overview over boosting algorithms and models employed in industry.

machine-learning xgboost adaboost boosting-algorithms research-paper binary-classification gradient-boosting boosting multi-class-classification weak-learning weak-learning-conditions

Updated Jun 28, 2023

mit-ll / Weak-Learning-Summarization

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This repository contains scripts for a weak learning summarization pipeline in Arabic and English.

nlp summarization extractive-summarization arabic-nlp automatic-text-summarization weak-learning

Updated Oct 28, 2022
Python

FulgentMcGuffin / published_papers

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(1) portfolio paper https://dl.acm.org/doi/abs/10.1145/3487553.3524634 (2) ncRNA paper https://ieeexplore.ieee.org/document/9746494 (3) Collaborative learning applied to other datasets https://ieeexplore.ieee.org/document/9746494

portfolio neural-networks sparse-regression weakly-supervised-learning penalized-regression collaborative-learning portfolio-management weak-learners rayleigh non-coding-rna weak-learning

Updated Jul 8, 2026
Jupyter Notebook

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