US 11,900,254 B2
System and method for multi-task learning
Matthew Holbrook, Chicago, IL (US); Jennifer Hobbs, Chicago, IL (US); and Patrick Joseph Lucey, Chicago, IL (US)
Assigned to STATS LLC, Chicago, IL (US)
Filed by STATS LLC, Chicago, IL (US)
Filed on Feb. 27, 2023, as Appl. No. 18/175,262.
Application 18/175,262 is a continuation of application No. 16/804,914, filed on Feb. 28, 2020, granted, now 11,593,647.
Claims priority of provisional application 62/812,511, filed on Mar. 1, 2019.
Prior Publication US 2023/0222340 A1, Jul. 13, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. G06N 3/08 (2023.01); G06N 3/04 (2023.01)
CPC G06N 3/08 (2013.01) [G06N 3/04 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method of generating a multi-modal prediction, comprising:
identifying, by a computing system, information related to a sporting event, the information comprising dense features of the sporting event and sparse features of the sporting event;
generating, by the computing system, dense representations of the sparse features using one or more embedding layers of a machine learning architecture;
generating, by the computing system, an input vector comprising the dense features and the dense representations of the sparse features;
simultaneously generating, by the computing system using a mixture density layer of the machine learning architecture, a plurality of values associated with a next event to occur based on the input vector; and
outputting, by the computing system, a graphical user interface comprising graphical representations of the plurality of values.