49 citations · 98 across the 9 of their papers we have counts for
11 papers
Insights From the NeurIPS 2021 NetHack Challenge
Eric Hambro, Sharada Mohanty, Dmitrii Babaev +26
In this report, we summarize the takeaways from the first NeurIPS 2021 NetHack Challenge. Participants were tasked with developing a program or agent that can win (i.e., 'ascend' i…
Project Achoo: A Practical Model and Application for COVID-19 Detection from Recordings of Breath, Voice, and Cough
Alexander Ponomarchuk, Ilya Burenko, Elian Malkin +4
The COVID-19 pandemic created a significant interest and demand for infection detection and monitoring solutions. In this paper we propose a machine learning method to quickly tria…
Towards forecast techniques for business analysts of large commercial data sets using matrix factorization methods
Rodrigo Rivera-Castro, Ivan Nazarov, Evgeny Burnaev
This research article suggests that there are significant benefits in exposing demand planners to forecasting methods using matrix completion techniques. This study aims to contrib…
Topology-based Clusterwise Regression for User Segmentation and Demand Forecasting
Rodrigo Rivera-Castro, Aleksandr Pletnev, Polina Pilyugina +4
Topological Data Analysis (TDA) is a recent approach to analyze data sets from the perspective of their topological structure. Its use for time series data has been limited. In thi…
An industry case of large-scale demand forecasting of hierarchical components
Rodrigo Rivera-Castro, Ivan Nazarov, Yuke Xiang +3
Demand forecasting of hierarchical components is essential in manufacturing. However, its discussion in the machine-learning literature has been limited, and judgemental forecasts…
Bayesian Sparsification Methods for Deep Complex-valued Networks
Ivan Nazarov, Evgeny Burnaev
With continual miniaturization ever more applications of deep learning can be found in embedded systems, where it is common to encounter data with natural complex domain representa…
Demand forecasting techniques for build-to-order lean manufacturing supply chains
Rodrigo Rivera-Castro, Ivan Nazarov, Yuke Xiang +3
Build-to-order (BTO) supply chains have become common-place in industries such as electronics, automotive and fashion. They enable building products based on individual requirement…
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…
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…
Steganographic Generative Adversarial Networks
Denis Volkhonskiy, Ivan Nazarov, Evgeny Burnaev
Steganography is collection of methods to hide secret information ("payload") within non-secret information "container"). Its counterpart, Steganalysis, is the practice of determin…
Conformalized Kernel Ridge Regression
Evgeny Burnaev, Ivan Nazarov
General predictive models do not provide a measure of confidence in predictions without Bayesian assumptions. A way to circumvent potential restrictions is to use conformal methods…