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Transnational machine learning with screens for flagging bid-rigging cartels
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Predicting fiscal crises
a machine learning approach -
Exploration of machine learning algorithms for maritime risk applications
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A machine learning approach to volatility forecasting
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Incentive effects of R&D tax incentives
a meta-analysis focusing on R&D tax policy designs -
Bottom incomes and the measurement of poverty and inequality
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Forecasting realized volatility using machine learning and mixed-frequency data (the case of the Russian stock market)
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The hard problem of prediction for conflict prevention
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Predicting football outcomes from Spanish league using machine learning models
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Ensemble Learning for Portfolio Valuation and Risk Management
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Distributional aspects of microcredit expansions
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Mean convergence, combinatorics, and grade-point averages
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Targeted bidders in government tenders
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Determinants of regional raw milk prices in Russia
paper prepared for presentation at the 61th annual conference of the GEWISOLA -
Predicting voter ideology using machine learning
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The application of machine learning algorithms for spatial analysis
predicting of real estate prices in Warsaw -
Using past violence and current news to predict changes in violence
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Forecasting realized volatility in turbulent times using temporal fusion transformers
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A survey on AI-based scheduling models, optimization and prediction for hydropower generation
variants, challenges, and future directions -
Predicting fiscal crises
a machine learning approach -
Feature Importance for Human Epithelial (HEp-2) Cell Image Classification
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Strategic management in public procurement
the role of dynamic capabilities in equity and efficiency -
Predicting re-employment
machine learning versus assessments by unemployed workers and by their caseworkers -
The populist voter
a machine learning approach for the individual characteristics -
Nowcasting domestic liquidity in the Philippines using machine learning algorithms