Abstract: Methods, systems, and devices for distributed hyperparameter tuning and load balancing are described. A device (e.g., an application server) may generate a first set of combinations of hyperparameter values associated with training a mathematical model. The mathematical model may include a machine learning model, an optimization model, or any combination. The device may identify a subset of combinations from the first set of combinations that are associated with a computational runtime that exceeds a first threshold and may distribute the subset of combinations across a set of machines. The device may then test each of the first set of combinations in a parallel processing operation to generate a first set of validation error values and may test a second set of combinations of hyperparameter values using an objective function that is based on the first set of validation error values.

Abstract: Features related to a system and method for scheduling a resources to perform discrete tasks are described. The scheduling features include generating schedules predicted to appeal to the tasked resource (e.g., delivery partner) such as by time, day of the week, location, item types, etc. Using machine learning, the schedule and terms thereof can be dynamically generated to suit the tastes of each tasked resource and the overall demand for services. Using historical data, the modeling also accounts for likelihood an offer will be accepted and risk of cancellation for a given resource. The machine learning may be based on a mixed integer problem as constrained by partner and system capacity parameters.

Abstract: The present disclosure provides an optical palpation device for evaluating a mechanical property of a sample material. The device comprises a body having a sensing portion and a sensing layer positioned at the sensing portion of the body and having a sensing surface positioned for direct or indirect contact with a surface area of the sample material. The sensing layer is deformable and has a predetermined deformation-dependent optical property. The device further comprises a light detector positioned to detect light transmitted through at least a portion of the sensing layer.

Abstract: Features related to a system and method for scheduling a resources to perform discrete tasks are described. The scheduling features include generating schedules predicted to appeal to the tasked resource (e.g., delivery partner) such as by time, day of the week, location, item types, etc. Using machine learning, the schedule and terms thereof can be dynamically generated to suit the tastes of each tasked resource and the overall demand for services. Using historical data, the modeling also accounts for likelihood an offer will be accepted and risk of cancellation for a given resource. The machine learning may be based on a mixed integer problem as constrained by partner and system capacity parameters.

Abstract: Features related to a system and method for scheduling a resources to perform discrete tasks are described. The scheduling features include generating schedules predicted to appeal to the tasked resource (e.g., delivery partner) such as by time, day of the week, location, item types, etc. Using machine learning, the schedule and terms thereof can be dynamically generated to suit the tastes of each tasked resource and the overall demand for services. Using historical data, the modeling also accounts for likelihood an offer will be accepted and risk of cancellation for a given resource. The machine learning may be based on a mixed integer problem as constrained by partner and system capacity parameters.

Abstract: A suction cleaner (60) comprising a body (50); a compartment (42) for accommodating a dust collection bag (44); and a source of suction (32) for causing suction airflow into a bag in the compartment, wherein the source of suction is disposed at least partially beneath the compartment and communicates therewith by a passage (46) which extends from an upper region of the compartment.

Abstract: A suction cleaner (60) comprising a body (50); a compartment (42) for accommodating a dust collection bag (44); and a source of suction (32) for causing suction airflow into a bag in the compartment, wherein the source of suction is disposed at least partially beneath the compartment and communicates therewith by a passage (46) which extends from an upper region of the compartment.