Multi-class Probabilistic Bounds for Majority Vote Classifiers with Partially Labeled Data von Feofanov, Vasilii, Devijver, Emilie, Amini, Massih-Reza

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Wrapper feature selection with partially labeled data von Feofanov, Vasilii, Devijver, Emilie, Amini, Massih-Reza

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Self-training: A survey von Amini, Massih-Reza, Feofanov, Vasilii, Pauletto, Loïc, Hadjadj, Liès, Devijver, Émilie, Maximov, Yury

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Classification multi-classe et sélection de variables avec des données partiellement étiquetées von Feofanov, Vasilii

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Leveraging Ensemble Diversity for Robust Self-Training in the Presence of Sample Selection Bias von Odonnat, Ambroise, Feofanov, Vasilii, Redko, Ievgen

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Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption von Feofanov, Vasilii, Tiomoko, Malik, Virmaux, Aladin

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User-friendly Foundation Model Adapters for Multivariate Time Series Classification von Feofanov, Vasilii, Ilbert, Romain, Tiomoko, Malik, Palpanas, Themis, Redko, Ievgen

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Multi-class Probabilistic Bounds for Self-learning von Feofanov, Vasilii, Devijver, Emilie, Amini, Massih-Reza

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Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting von Ilbert, Romain, Tiomoko, Malik, Louart, Cosme, Odonnat, Ambroise, Feofanov, Vasilii, Palpanas, Themis, Redko, Ievgen

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MANO: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts von Xie, Renchunzi, Odonnat, Ambroise, Feofanov, Vasilii, Deng, Weijian, Zhang, Jianfeng, An, Bo

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SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention von Ilbert, Romain, Odonnat, Ambroise, Feofanov, Vasilii, Virmaux, Aladin, Paolo, Giuseppe, Palpanas, Themis, Redko, Ievgen

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Leveraging Gradients for Unsupervised Accuracy Estimation under Distribution Shift von Xie, Renchunzi, Odonnat, Ambroise, Feofanov, Vasilii, Redko, Ievgen, Zhang, Jianfeng, An, Bo

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Leveraging Ensemble Diversity for Robust Self-Training in the Presence of Sample Selection Bias von Ambroise Odonnat, Feofanov, Vasilii, Redko, Ievgen

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Semi-supervised Wrapper Feature Selection by Modeling Imperfect Labels von Feofanov, Vasilii, Devijver, Emilie, Amini, Massih-Reza

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Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption von Feofanov, Vasilii, Malik Tiomoko, Virmaux, Aladin

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User-friendly Foundation Model Adapters for Multivariate Time Series Classification von Feofanov, Vasilii, Ilbert, Romain, Malik Tiomoko, Palpanas, Themis, Redko, Ievgen

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Self-Training: A Survey von Amini, Massih-Reza, Feofanov, Vasilii, Pauletto, Loic, Hadjadj, Lies, Devijver, Emilie, Maximov, Yury

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Multi-class Probabilistic Bounds for Self-learning von Feofanov, Vasilii, Devijver, Emilie, Amini, Massih-Reza

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MANO: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts von Xie, Renchunzi, Ambroise Odonnat, Feofanov, Vasilii, Deng, Weijian, Zhang, Jianfeng, An, Bo

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Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting von Ilbert, Romain, Malik Tiomoko, Louart, Cosme, Ambroise Odonnat, Feofanov, Vasilii, Palpanas, Themis, Redko, Ievgen

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