Automatic robust estimation for exponential smoothing: Perspectives from statistics and machine learning

Constraint Learning Based Gradient Boosting Trees

(2019) Abraham Israeli et al.   EXPERT SYSTEMS WITH APPLICATIONS

Retail forecasting: Research and practice

(2019) Robert Fildes et al.   INTERNATIONAL JOURNAL OF FORECASTING

Exploring the sources of uncertainty: Why does bagging for time series forecasting work?

(2018) Fotios Petropoulos et al.   EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Ensemble of adaboost cascades of 3L-LBPs classifiers for license plates detection with low quality images

(2018) Meeras Salman Al-Shemarry et al.   EXPERT SYSTEMS WITH APPLICATIONS

Another look at forecast selection and combination: Evidence from forecast pooling

(2018) Nikolaos Kourentzes et al.   INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS

Empirical safety stock estimation based on kernel and GARCH models

(2018) Juan R. Trapero et al.   OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE

Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500

(2017) Christopher Krauss et al.   EUROPEAN JOURNAL OF OPERATIONAL RESEARCH

Multi-site solar power forecasting using gradient boosted regression trees

(2017) Caroline Persson et al.   SOLAR ENERGY

Distributions of forecasting errors of forecast combinations: Implications for inventory management

(2016) Devon K. Barrow et al.   INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS

Forecasting with multivariate temporal aggregation: The case of promotional modelling

(2016) Nikolaos Kourentzes et al.   INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS

A neural-AdaBoost based facial expression recognition system

(2013) Ebenezer Owusu et al.   EXPERT SYSTEMS WITH APPLICATIONS

An efficient version of inverse boosting for classification

(2012) Jingyang Gao et al.   TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL

Making and Evaluating Point Forecasts

(2011) Tilmann Gneiting   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Cost-sensitive boosting neural networks for software defect prediction

(2009) Jun Zheng   EXPERT SYSTEMS WITH APPLICATIONS

Noisy time series prediction using M-estimator based robust radial basis function neural networks with growing and pruning techniques

(2008) Chien-Cheng Lee et al.   EXPERT SYSTEMS WITH APPLICATIONS

How Useful Is Bagging in Forecasting Economic Time Series? A Case Study of U.S. Consumer Price Inflation

(2008) Atsushi Inoue et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION

Bagging for Gaussian process regression

(2008) Tao Chen et al.   NEUROCOMPUTING

Quantifying costs of forecast errors: A case study of the warehouse environment☆

(2006) N SANDERS et al.   OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE