Abstract: In one embodiment, a method includes receiving a query comprising a query content object and constraints, generating a feature vector representing the query content object, accessing a sparse graph comprising nodes corresponding to candidate content objects represented by compact codes and links connecting the nodes, selecting an entry node, selecting similar content objects iteratively by identifying linked nodes of the entry node, decompressing the compact codes representing candidate content objects to generate feature vectors, selecting zero or more similar content objects based on a comparison between the feature vector representing the query content object and the feature vectors representing the candidate content objects, returning the selected similar content objects if a completion condition is satisfied, else repeating the iterative selection by using a linked node corresponding to a most similar content object as the entry node, and sending instructions for presenting one or more of the selected si

Abstract: Disclosed herein are a system, a method and a device for radioactive data generation. A defined marker can be applied or inserted within data of at least one class of a dataset having a plurality of classes of data. The defined marker data can be used to determine if a neural network model was trained using the respective class of data. A device can determine characteristics of a neural network model. The device can compare the characteristics of the neural network model with characteristics of the defined marker data incorporated into a first class of data. The device can determine, responsive to the comparing, whether the neural network model was trained using a dataset having a plurality of classes of data that includes the first class of data incorporated with the defined marker data.

Abstract: In one embodiment, a method includes receiving a query comprising a query content object and constraints, generating a feature vector representing the query content object, accessing a sparse graph comprising nodes corresponding to candidate content objects represented by compact codes and links connecting the nodes, selecting an entry node, selecting similar content objects iteratively by identifying linked nodes of the entry node, decompressing the compact codes representing candidate content objects to generate feature vectors, selecting zero or more similar content objects based on a comparison between the feature vector representing the query content object and the feature vectors representing the candidate content objects, returning the selected similar content objects if a completion condition is satisfied, else repeating the iterative selection by using a linked node corresponding to a most similar content object as the entry node, and sending instructions for presenting one or more of the selected si