Explanipedia

DEVELOPMENT OF ECONOMIC AND MATHEMATICAL MODEL FOR SUBSTANTITIONOPTIMAL COMPOSITION OF THE MACHINE AND TRACTOR FLEETWHEN CALCULATING REQUIREMENTS FOR AGRICULTURAL MACHINERY Open

Y.V. Binyukov, Yu. V. Polichshuk, А.П. Комаров, Nikolay Laptev, M. A Plokhotenko · 2025

The article presents the requirements for standards of need for technical equipment, the general structural scheme of research on the development of standards of need for agricultural machinery and the results of work on the development of…

AI-Assisted SQL Authoring at Industry Scale Open

Chandra Maddila, Negar Ghorbani, Kosay Jabre, Vijayaraghavan Murali, Edwin Kim , et al. · 2024

SqlCompose brings generative AI into the data analytics domain. SQL is declarative, has formal table schemas, and is often written in a non-linear manner. We address each of these challenges and develop a set of models that shows the impor…

NeuralProphet: Explainable Forecasting at Scale Open

Oskar Triebe, Hansika Hewamalage, Polina Pilyugina, Nikolay Laptev, Christoph Bergmeir , et al. · 2021

We introduce NeuralProphet, a successor to Facebook Prophet, which set an industry standard for explainable, scalable, and user-friendly forecasting frameworks. With the proliferation of time series data, explainable forecasting remains a …

Self-supervised learning for fast and scalable time series hyper-parameter tuning Open

Peiyi Zhang, Xiaodong Jiang, Ginger M. Holt, Nikolay Laptev, Caner Kömürlü , et al. · 2021

Hyper-parameters of time series models play an important role in time series analysis. Slight differences in hyper-parameters might lead to very different forecast results for a given model, and therefore, selecting good hyper-parameter va…

Digital Psychological Platform for Mass Web-Surveys Open

Evgeny Nikulchev, Dmitry Ilin, Anastasiya Silaeva, Pavel Kolyasnikov, V. Belov , et al. · 2020

Web-surveys are one of the most popular forms of primary data collection used for various researches. However, mass surveys involve some challenges. It is required to consider different platforms and browsers, as well as different data tra…

Scalable Data Classification for Security and Privacy Open

Paulo Tanaka, Sameet Sapra, Nikolay Laptev · 2020

Content based data classification is an open challenge. Traditional Data Loss Prevention (DLP)-like systems solve this problem by fingerprinting the data in question and monitoring endpoints for the fingerprinted data. With a large number …

Privacy at Facebook Scale Open

Paulo Tanaka, Sameet Sapra, Nikolay Laptev · 2020

Content based data classification is an open challenge. Traditional Data Loss Prevention (DLP)-like systems solve this problem by fingerprinting the data in question and monitoring endpoints for the fingerprinted data. With trillions of co…

Fast Dimensional Analysis for Root Cause Investigation in a Large-Scale Service Environment Open

Fred Lin, Keyur Muzumdar, Nikolay Laptev, Mihai-Valentin Curelea, Seunghak Lee , et al. · 2020

Root cause analysis in a large-scale production environment is challenging due to the complexity of the services running across global data centers. Due to the distributed nature of a large-scale system, the various hardware, software, and…

The use of automatic and parallel driving systems in agricultural production of the Republic of Kazakhstan and the efficiency of their use Open

Yuriy Polischuk, Nikolay Laptev, А. Г. Комаров · 2020

Precision farming systems are being intensively introduced into the agricultural production of the Republic of Kazakhstan. Based on the data of development firms and dealerships centers, precision farming allows the cost of fertilizing, se…

AR-Net: A simple Auto-Regressive Neural Network for time-series Open

Oskar Triebe, Nikolay Laptev, Ram Rajagopal · 2019

In this paper we present a new framework for time-series modeling that combines the best of traditional statistical models and neural networks. We focus on time-series with long-range dependencies, needed for monitoring fine granularity da…

Deep and Confident Prediction for Time Series at Uber Open

Lingxue Zhu, Nikolay Laptev · 2017

Reliable uncertainty estimation for time series prediction is critical in\nmany fields, including physics, biology, and manufacturing. At Uber,\nprobabilistic time series forecasting is used for robust prediction of number\nof trips during…

Online Article Ranking as a Constrained, Dynamic, Multi-Objective Optimization Problem Open

Jeya Balaji Balasubramanian, Akshay Soni, Yashar Mehdad, Nikolay Laptev · 2017

The content ranking problem in a social news website, is typically a function that maximizes a scalar metric of interest like dwell-time. However, like in most real-world applications we are interested in more than one metric---for instanc…

Online Article Ranking as a Constrained, Dynamic, Multi-Objective Optimization Problem. Open

Jeya Balaji Balasubramanian, Akshay Soni, Yashar Mehdad, Nikolay Laptev · 2017

The content ranking problem in a social news website, is typically a function that maximizes a scalar metric of interest like dwell-time. However, like in most real-world applications we are interested in more than one metric---for instanc…

Rank-to-engage: New Listwise Approaches to Maximize Engagement Open

Swayambhoo Jain, Akshay Soni, Nikolay Laptev, Yashar Mehdad · 2017

For many internet businesses, presenting a given list of items in an order that maximizes a certain metric of interest (e.g., click-through-rate, average engagement time etc.) is crucial. We approach the aforementioned task from a learning…

EVALUATION OF MOTIVATION CONDITIONS FOR REPRODUCTION OF LABOR RESOURCES AND SOCIAL-LABOR RELATIONS IN AGRICULTURE (ON THE EXAMPLE OF THE ULYANOVSK REGION) Open

Nikolay Laptev, N. D. Ananyeva, Maria Rybkina · 2017

The article assesses the motivational conditions for the reproduction of labor resources and social and labor relations in agriculture in the Ulyanovsk region. Reproduction of labor resources is considered. The demographic situation in the…

Earnings Announcement Promotions: A Yahoo Finance Field Experiment Open

Alastair Lawrence, James Ryans, Estelle Sun, Nikolay Laptev · 2017

DECT: Distributed Evolving Context Tree for Understanding User Behavior Pattern Evolution Open

Xiaokui Shu, Nikolay Laptev, Danfeng Yao · 2016

Internet user behavior models characterize user browsing dynamics or the transitions among web pages. The models help Internet companies improve their services by accurately targeting customers and providing them the information they want.…

DECT: Distributed Evolving Context Tree for Mining Web Behavior Evolution Open

Xiaokui Shu, Nikolay Laptev, Danfeng Yao · 2016

Internet user behavior models characterize user browsing dynamics or the transitions among web pages. The mod- els help Internet companies improve their services by accu- rately targeting customers and providing them the informa- tion they…

Yahoo Finance Search and Earnings Announcements Open

Alastair Lawrence, James Ryans, Estelle Sun, Nikolay Laptev · 2016

Inertial Hidden Markov Models: Modeling Change in Multivariate Time Series Open

George D. Montañez, Saeed Amizadeh, Nikolay Laptev · 2015

Faced with the problem of characterizing systematic changes in multivariate time series in an unsupervised manner, we derive and test two methods of regularizing hidden Markov models for this task. Regularization on state transitions provi…

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