Vasilii Feofanov

Orcid: 0000-0002-5777-4205

According to our database1, Vasilii Feofanov authored at least 17 papers between 2019 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

2019
2020
2021
2022
2023
2024
2025
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Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2025
Self-training: A survey.
Neurocomputing, 2025

2024
Multi-class Probabilistic Bounds for Majority Vote Classifiers with Partially Labeled Data.
J. Mach. Learn. Res., 2024

Measuring Pre-training Data Quality without Labels for Time Series Foundation Models.
CoRR, 2024

User-friendly Foundation Model Adapters for Multivariate Time Series Classification.
CoRR, 2024

Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention.
CoRR, 2024

Characterising Gradients for Unsupervised Accuracy Estimation under Distribution Shift.
CoRR, 2024

MaNo: Exploiting Matrix Norm for Unsupervised Accuracy Estimation Under Distribution Shifts.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Analysing Multi-Task Regression via Random Matrix Theory with Application to Time Series Forecasting.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention.
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.
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.
Proceedings of the International Conference on Machine Learning, 2023

2022
Self-Training: A Survey.
CoRR, 2022

Wrapper feature selection with partially labeled data.
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).
PhD thesis, 2021

Multi-class Probabilistic Bounds for Self-learning.
CoRR, 2021

2019
Semi-supervised Wrapper Feature Selection with Imperfect Labels.
CoRR, 2019

Transductive Bounds for the Multi-Class Majority Vote Classifier.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019


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