Blue Yonder Group, Inc.

Nortel Networks Corporation

Servicenow, Inc.

Imagia Cybernetics Inc.

Servicenow Canada Inc.

Nicolas Chapados

Peter R Stubley

Yoshua Bengio

Dmitri Carpov

Nicolas Guizard

Mohammad Havaei

Florent Chandelier

R&eacute;al R Tremblay

Claudia Pateras

Daniel Wong

Lisa Dijorio

Andrew Jesson

Cecile Low-Kam

Florian Soudan

A method for forecasting future values of a target variable using past values thereof, the values of the target variable being affected by one or more covariates wherein the covariates are independent from the target variable. The method comprises using a covariate-specific AI model, computing a covariate effect of the covariates on the target variable. The covariates effect is a defined modification to the values of the target variable caused by the covariates. The method also comprises computing intrinsic past values of the target variable by removing the covariate effect of the covariates from past values of the target variable. The method further comprises using a target-variable-specific AI model, generating an intrinsic forecast of the future values of the target variable; and computing a forecast that includes the covariate effect using the intrinsic forecast of the future values of the target variable and the covariate effect.

Covariate processing with neural network execution blocks

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.

Method and system of demand forecasting for inventory management of slow-moving inventory in a supply chain

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 reduces each corresponding numeric value of each of the more than one feature map generated by the feature map generation unit down to one numeric value in the at least one corresponding combined feature map.

Method and system for processing a task with robustness to missing input information

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.

Method and apparatus for discourse management

Growing community of inventors

Montreal, Canada

Nicolas Chapados