86 citations · 270 across the 28 of their papers we have counts for
6 papers · 1 filter
Gradient Boosting to Boost the Efficiency of Hydraulic Fracturing
Ivan Makhotin, Dmitry Koroteev, Evgeny Burnaev
In this paper, we present a data-driven model for forecasting the production increase after hydraulic fracturing (HF). We use data from fracturing jobs performed at one of the Sibe…
Large Scale Variable Fidelity Surrogate Modeling
Evgeny Burnaev, Alexey Zaytsev
Engineers widely use Gaussian process regression framework to construct surrogate models aimed to replace computationally expensive physical models while exploring design space. Th…
Model Selection for Anomaly Detection
Evgeny Burnaev, Pavel Erofeev, Dmitry Smolyakov
Anomaly detection based on one-class classification algorithms is broadly used in many applied domains like image processing (e.g. detection of whether a patient is "cancerous" or…
Influence of Resampling on Accuracy of Imbalanced Classification
Evgeny Burnaev, Pavel Erofeev, Artem Papanov
In many real-world binary classification tasks (e.g. detection of certain objects from images), an available dataset is imbalanced, i.e., it has much less representatives of a one…
Inductive Conformal Martingales for Change-Point Detection
Denis Volkhonskiy, Ilia Nouretdinov, Alexander Gammerman +2
We consider the problem of quickest change-point detection in data streams. Classical change-point detection procedures, such as CUSUM, Shiryaev-Roberts and Posterior Probability s…
Conformal k-NN Anomaly Detector for Univariate Data Streams
Vladislav Ishimtsev, Ivan Nazarov, Alexander Bernstein +1
Anomalies in time-series data give essential and often actionable information in many applications. In this paper we consider a model-free anomaly detection method for univariate t…