Abstract: A system and method are disclosed for a supply chain planner to generate a distributional demand forecast for slow-moving inventory in a supply chain. The distributional demand forecast model takes into account explanatory variables and historical sales data to address seasonality and special events and permits sharing of demand information across different stores and stock-keeping units. The supply chain planner performs inference on the explanatory variables and historical sales data to generate process parameters and latent variables. Other embodiments are also disclosed.

Abstract: A system and method are disclosed for a supply chain planner to generate a distributional demand forecast for slow-moving inventory in a supply chain. The distributional demand forecast model takes into account explanatory variables and historical sales data to address seasonality and special events and permits sharing of demand information across different stores and stock-keeping units. The supply chain planner performs inference on the explanatory variables and historical sales data to generate process parameters and latent variables. Other embodiments are also disclosed.

Abstract: A system and method are disclosed for a supply chain planner to generate a distributional demand forecast for slow-moving inventory in a supply chain. The distributional demand forecast model takes into account explanatory variables and historical sales data to address seasonality and special events and permits sharing of demand information across different stores and stock-keeping units. The supply chain planner performs inference on the explanatory variables and historical sales data to generate process parameters and latent variables. Other embodiments are also disclosed.

Abstract: A system and method are disclosed for a supply chain planner to generate a distributional demand forecast for slow-moving inventory in a supply chain. The distributional demand forecast model takes into account explanatory variables and historical sales data to address seasonality and special events and permits sharing of demand information across different stores and stock-keeping units. The supply chain planner performs inference on the explanatory variables and historical sales data to generate process parameters and latent variables. Other embodiments are also disclosed.

Abstract: A unit is disclosed for generating combined feature maps in accordance with a processing task to be performed, the unit comprising a feature map generating unit for receiving more than one modality and for generating more than one corresponding feature map using more than one corresponding transformation; wherein the generating of each of the more than one corresponding feature map is performed by applying a given corresponding transformation on a given corresponding modality, wherein the more than one corresponding transformation is generated following an initial training performed in accordance with the processing task to be performed and a combining unit for selecting and combining the corresponding more than one feature map generated by the feature map generating unit in accordance with at least one combining operation and for providing at least one corresponding combined feature map; wherein the combining unit is operating in accordance with the processing task to be performed and the combining operation

Abstract: The invention relates to a system for providing a dialogue enabled speech application system, more particularly to a system apparatus and method for providing a mixed-initiative dialog with a user. The invention provides a discourse manager unit utilizing a dynamic finite-state machine that allows the creation of temporary transitions to accommodate a given context of the conversation without leading to an explosion in the number of finite-state machine states. The invention is particularly useful for use in natural-dialogue speech applications in particular for allowing users to perform actions by simply providing information to the system through spoken request.