Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving, by a neural network (NN), a dataset for generating features from the dataset. A first set of features is computed from the dataset using at least a feature layer of the NN. The first set of features i) is characterized by a measure of informativeness; and ii) is computed such that a size of the first set of features is compressible into a second set of features that is smaller in size than the first set of features and that has a same measure of informativeness as the measure of informativeness of the first set of features. The second set of features if generated from the first set of features using a compression method that compresses the first set of features to generate the second set of features.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving, by a neural network (NN), a dataset for generating features from the dataset. A first set of features is computed from the dataset using at least a feature layer of the NN. The first set of features i) is characterized by a measure of informativeness; and ii) is computed such that a size of the first set of features is compressible into a second set of features that is smaller in size than the first set of features and that has a same measure of informativeness as the measure of informativeness of the first set of features. The second set of features if generated from the first set of features using a compression method that compresses the first set of features to generate the second set of features.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for a graph processing system. In one aspect, the graph processing system obtains data identifying a first node and a second node from a graph of nodes and edges. The system processes numeric embeddings of the first node and the second node using a manifold neural network to generate respective manifold coordinates of the first node and the second node. The system applies a learned edge function to the manifold coordinates of the first node and the manifold coordinates of the second node to generate an edge score that represents a likelihood that an entity represented by the first node and an entity represented by the second node have a particular relationship.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving, by a neural network (NN), a dataset for generating features from the dataset. A first set of features is computed from the dataset using at least a feature layer of the NN. The first set of features i) is characterized by a measure of informativeness; and ii) is computed such that a size of the first set of features is compressible into a second set of features that is smaller in size than the first set of features and that has a same measure of informativeness as the measure of informativeness of the first set of features. The second set of features if generated from the first set of features using a compression method that compresses the first set of features to generate the second set of features.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for selecting representative frames for videos. One of the methods includes receiving a search query; determining a query representation for the search query; obtaining data identifying a plurality of responsive videos for the search query, wherein each responsive video comprises a plurality of frames, wherein each frame has a respective frame representation; selecting, for each responsive video, a representative frame from the responsive video using the query representation and the frame representations for the frames in the responsive video; and generating a response to the search query, wherein the response to the search query includes a respective video search result for each of the responsive videos, and wherein the respective video search result for each of the responsive videos includes a presentation of the representative video frame from the responsive video.

Abstract: A method for reporting timing exception status is presented. The method begins by computing a set of edges of a sub-domain and a set of edges of a timing exception. A slack value is computed based on either the edges of the sub-domain common to the set of edges of the timing exception or the timing paths of the sub-domain. If the sub-domain has a valid slack value, the method compares the sub-domain timing exception type to the timing exception type of the timing exception. The method identifies the timing exception as being overridden if both timing exception types are different and either the slack value computed based on edges of the sub-domain is valid, or the sub-domain has the valid slack value and an intersection of the set of edges of the sub-domain and of the timing exception forms a timing path. The method presents the overridden timing exceptions.