Abstract: A method of training a machine learning model includes receiving training data comprising a graph structure and one or more feature attributes and determining an encoded graph based on applying the machine learning model to the graph structure and the one or more feature attributes. The machine learning model comprises a graph convolutional network layer. The encoded graph comprises one or more nodes and one or more paths connecting the one or more nodes. The method also includes selecting a plurality of positive samples through random walks along the one or more paths of the encoded graph, selecting a plurality of negative samples from the encoded graph by randomly sampling the one or more nodes of the encoded graph, determining a loss value, and updating, based on the loss value, one or more learnable parameter values of the machine learning model.

Abstract: The invention is a method to build and erect super high rise buildings with a completely new concept of civil engineering, which is based on concept and method of building of vertical columnar structures by multi stacking of columns using hydraulic suspension and elevator arm system, and then strengthening them with concrete. This is followed with building of gateway support structure around vertical columnar structure and central core to stabilize the high rise building. Next stage is the building of horizontal steel framework platforms at ground level and elevating them by central core elevator and cable hoist system. The passage of horizontal platforms through gateway structure is conducted by alternating opening and closing of gates. The process enables to populate the vertical columnar structures with horizontal platforms, which are then inter locked with vertical columnar structures and central concrete core wall Finally the steel framework platforms are strengthened with concrete.

Abstract: The invention is a method to build and erect super high rise buildings with a completely new concept of civil engineering, which is based on concept and method of building of vertical columnar structures by multi stacking of columns using hydraulic suspension and elevator arm system, and then strengthening them with concrete. This is followed with building of gateway support structure around vertical columnar structure and central core to stabilize the high rise building. Next stage is the building of horizontal steel framework platforms at ground level and elevating them by central core elevator and cable hoist system. The passage of horizontal platforms through gateway structure is conducted by alternating opening and closing of gates. The process enables to populate the vertical columnar structures with horizontal platforms, which are then inter locked with vertical columnar structures and central concrete core wall Finally the steel framework platforms are strengthened with concrete.

Abstract: A system and method operates with a document collection in which documents are represented as normalized document vectors. The document vector space is partitioned into a set of disjoint clusters and a concept vector is computed for each partition, the concept vector comprising the mean vector of all the documents in each partition. Documents are then reassigned to the cluster having their closest concept vector, and a new set of concept vectors for the new partitioning is computed. From an initial partitioning, the concept vectors are iteratively calculated to a stopping threshold value, leaving a concept vector subspace of the document vectors. The documents can then be projected onto the concept vector subspace to be represented as a linear combination of the concept vectors, thereby reducing the dimensionality of the document space.

Abstract: A method, apparatus, article of manufacture, and a memory structure for clustering data points in parallel using a distributed-memory multi-processor system is disclosed. The disclosed system has particularly advantageous application to a rapid and flexible k-means computation for data mining. The method comprises the steps of dividing a set of data points into a plurality of data blocks, initializing a set of k global centroid values in each of the data blocks k initial global centroid values, performing a plurality of asynchronous processes on the data blocks, each asynchronous process assigning each data point in each data block to the closest global centroid value within each data block, computing a set of k block accumulation values from the data points assigned to the k global centroid values, and recomputing the k global centroid values from the k block accumulation values.