6 citations · 18 across the 33 of their papers we have counts for
5 papers · 1 filter
Towards a Relationship-Aware Transformer for Tabular Data
Andrei V. Konstantinov, Valerii A. Zuev, Lev V. Utkin
Deep learning models for tabular data typically do not allow for imposing a graph of external dependencies between samples, which can be useful for accounting for relatedness in ta…
Survival Analysis as Imprecise Classification with Trainable Kernels
Andrei V. Konstantinov, Vlada A. Efremenko, Lev V. Utkin
Survival analysis is a fundamental tool for modeling time-to-event data in healthcare, engineering, and finance, where censored observations pose significant challenges. While trad…
Ensemble-Based Survival Models with the Self-Attended Beran Estimator Predictions
Lev V. Utkin, Semen P. Khomets, Vlada A. Efremenko +2
Survival analysis predicts the time until an event of interest, such as failure or death, but faces challenges due to censored data, where some events remain unobserved. Ensemble-b…
A novel gradient-based method for decision trees optimizing arbitrary differential loss functions
Andrei V. Konstantinov, Lev V. Utkin
There are many approaches for training decision trees. This work introduces a novel gradient-based method for constructing decision trees that optimize arbitrary differentiable los…
Survival Concept-Based Learning Models
Stanislav R. Kirpichenko, Lev V. Utkin, Andrei V. Konstantinov +1
Concept-based learning enhances prediction accuracy and interpretability by leveraging high-level, human-understandable concepts. However, existing CBL frameworks do not address su…