Abstract: Generally discussed herein are devices, systems, and methods for generating synthetic datasets. A method includes obtaining a first training labelled dataset, obtaining a second training labelled dataset, determining an optimal transport (OT) map from a target labelled dataset to the first training labelled dataset, determining an OT map from the target labelled dataset to the second training labelled dataset, identifying, in a generalized geodesic hull formed by the first and second training labelled datasets in a distribution space and based on the OT maps, a point proximate the target dataset in the distribution space, and producing the synthetic labelled ML dataset by combining, based on distances between probability distribution representations of the first and second labelled training datasets in the distribution space and the point, the first and second labelled training datasets resulting in a labelled synthetic dataset.

Abstract: Generally discussed herein are devices, systems, and methods for machine learning (ML) by flowing a dataset towards a target dataset. A method can include receiving a request to operate on a first dataset including first feature, label pairs, identifying a second dataset from multiple datasets, the second dataset including second feature, label pairs, determining a distance between the first feature, label and the second feature, label pairs, and flowing the first dataset using a dataset objective that operates based on the determined distance to generate an optimized dataset.

Abstract: Generally discussed herein are devices, systems, and methods for machine learning (ML) by flowing a dataset towards a target dataset. A method can include receiving a request to operate on a first dataset including first feature, label pairs, identifying a second dataset from multiple datasets, the second dataset including second feature, label pairs, determining a distance between the first feature, label and the second feature, label pairs, and flowing the first dataset using a dataset objective that operates based on the determined distance to generate an optimized dataset.

Abstract: Generally discussed herein are devices, systems, and methods for machine learning (ML) by flowing a dataset towards a target dataset. A method can include receiving a request to operate on a first dataset including first feature, label pairs, identifying a second dataset from multiple datasets, the second dataset including second feature, label pairs, determining a distance between the first feature, label and the second feature, label pairs, and flowing the first dataset using a dataset objective that operates based on the determined distance to generate an optimized dataset.