43 citations · 153 across the 27 of their papers we have counts for
3 papers · 1 filter
Constructing Graph Node Embeddings via Discrimination of Similarity Distributions
Stanislav Tsepa, Maxim Panov
The problem of unsupervised learning node embeddings in graphs is one of the important directions in modern network science. In this work we propose a novel framework, which is aim…
Dropout-based Active Learning for Regression
Evgenii Tsymbalov, Maxim Panov, Alexander Shapeev
Active learning is relevant and challenging for high-dimensional regression models when the annotation of the samples is expensive. Yet most of the existing sampling methods cannot…
Sparse Group Inductive Matrix Completion
Ivan Nazarov, Boris Shirokikh, Maria Burkina +2
We consider the problem of matrix completion with side information (\textit{inductive matrix completion}). In real-world applications many side-channel features are typically non-i…