ARMDN: Associative and Recurrent Mixture Density Networks for eRetail Demand Forecasting

10 Mar 2018Srayanta MukherjeeDevashish ShankarAtin GhoshNilam TathawadekarPramod KompalliSunita SarawagiKrishnendu Chaudhury

Accurate demand forecasts can help on-line retail organizations better plan their supply-chain processes. The challenge, however, is the large number of associative factors that result in large, non-stationary shifts in demand, which traditional time series and regression approaches fail to model... (read more)

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