Time Series Analysis & Forecasting

Our research and engineering team develop sophisticated mathematical models and algorithms to analyze historical data, uncover trends, seasonality, and dependencies, and make accurate predictions about future trends or values. We uncover financial insights to power products on Yahoo! Finance and detect popular trends to facilitate Yahoo! News and Search.

Publications

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October 15, 2020

IEEE Control Systems Magazine

Feedback Control in Programmatic Advertising: The Frontier of Optimization in Real-Time Bidding

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July 24, 2020

CIKM 2020

Prospective Modeling of Users for Online Display Advertising via Deep Time-Aware Model

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January 1, 2019

American Control Conference 2019

Identification of Seasonality in Internet Traffic to Support Control of Online Advertising

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January 1, 2019

AdKDD

Time-Aware Prospective Modeling of Users for Online Display Advertising

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January 1, 2019

ICMLA 2019

A Deep Structural Model for Analyzing Correlated Multivariate Time Series

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January 1, 2019

Financial Cryptography and Data Security 2019

Forecasting Suspicious Account Activity at Large-Scale Online Service Providers

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January 1, 2019

KDD

Recurrent Neural Networks for Stochastic Control in Real-Time Bidding

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