Vasilii Feofanov

According to our database, Vasilii Feofanov authored at least 16 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Self-training: A survey.

Massih-Reza Amini, Vasilii Feofanov, Loïc Pauletto, Lies Hadjadj, Emilie Devijver, Yury Maximov

Neurocomputing, 2025

2024

Multi-class Probabilistic Bounds for Majority Vote Classifiers with Partially Labeled Data.

Vasilii Feofanov, Emilie Devijver, Massih-Reza Amini

J. Mach. Learn. Res., 2024

User-friendly Foundation Model Adapters for Multivariate Time Series Classification.

Vasilii Feofanov, Romain Ilbert, Malik Tiomoko, Themis Palpanas, Ievgen Redko

CoRR, 2024

Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting.

Romain Ilbert, Malik Tiomoko, Cosme Louart, Ambroise Odonnat, Vasilii Feofanov, Themis Palpanas, Ievgen Redko

CoRR, 2024

MANO: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts.

Renchunzi Xie, Ambroise Odonnat, Vasilii Feofanov, Weijian Deng, Jianfeng Zhang, Bo An

CoRR, 2024

Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention.

Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov, Aladin Virmaux, Giuseppe Paolo, Themis Palpanas, Ievgen Redko

CoRR, 2024

Characterising Gradients for Unsupervised Accuracy Estimation under Distribution Shift.

Renchunzi Xie, Ambroise Odonnat, Vasilii Feofanov, Ievgen Redko, Jianfeng Zhang, Bo An

CoRR, 2024

SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention.

Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov, Aladin Virmaux, Giuseppe Paolo, Themis Palpanas, Ievgen Redko

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Leveraging Ensemble Diversity for Robust Self-Training in the Presence of Sample Selection Bias.

Ambroise Odonnat, Vasilii Feofanov, Ievgen Redko

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Random Matrix Analysis to Balance between Supervised and Unsupervised Learning under the Low Density Separation Assumption.

Vasilii Feofanov, Malik Tiomoko, Aladin Virmaux

Proceedings of the International Conference on Machine Learning, 2023

2022

Self-Training: A Survey.

Massih-Reza Amini, Vasilii Feofanov, Loïc Pauletto, Emilie Devijver, Yury Maximov

CoRR, 2022

Wrapper feature selection with partially labeled data.

Vasilii Feofanov, Emilie Devijver, Massih-Reza Amini

Appl. Intell., 2022

2021

Learning with Partially Labeled Data for Multi-class Classification and Feature Selection. (Classification Multi-classe et Sélection de Variables avec des Données Partiellement Étiquetées).

Vasilii Feofanov

PhD thesis, 2021

Multi-class Probabilistic Bounds for Self-learning.

Vasilii Feofanov, Emilie Devijver, Massih-Reza Amini

CoRR, 2021

2019

Semi-supervised Wrapper Feature Selection with Imperfect Labels.

Vasilii Feofanov, Massih-Reza Amini, Emilie Devijver

CoRR, 2019

Transductive Bounds for the Multi-Class Majority Vote Classifier.

Vasilii Feofanov, Emilie Devijver, Massih-Reza Amini

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019