Abstract: A computerized optimization method, system, and computer readable storage medium for performing pattern searching includes (a) providing an initial mesh of vectors; (b) providing initial points to be used as a base vector establishing a center region of the mesh of vectors; (c) for each base vector, obtaining a transformed mesh via an isometric transformation of the initial mesh of vectors; (d) evaluating the model objective function via each transformed mesh of vectors; (e) selecting a next set of base vectors by selecting a most favorable set of transformed mesh vectors to correspond with the objective function; (f) repeating steps (c) through (e) in an iterative sequence until a termination criterion of the iterative sequence is met; and (g) storing the selected most favorable transformed mesh vectors in a memory.

Abstract: A method for generating one or more push notifications to a user device is described. The method comprises: obtaining history data representing a history of online activities of a user and candidate data representing a set of candidate information; generating, based on the history data and the candidate data, user profile vectors representing a user profile associated with the user and content vectors representing a set of content profiles associated with the set of candidate information; generating, based on a machine learning model trained with a history of online activities, embedding user feature vectors and embedding content feature vectors based on the history data and the candidate data; and providing for transmission information for one or more push notifications including first candidate information of to a user device associated with the user, the first candidate information being determined from the set of candidate information based on the aforementioned vectors.

Abstract: A method for generating one or more push notifications to a user device is described. The method comprises: obtaining history data representing a history of online activities of a user and candidate data representing a set of candidate information; generating, based on the history data and the candidate data, user profile vectors representing a user profile associated with the user and content vectors representing a set of content profiles associated with the set of candidate information; generating, based on a machine learning model trained with a history of online activities, embedding user feature vectors and embedding content feature vectors based on the history data and the candidate data; and providing for transmission information for one or more push notifications including first candidate information of to a user device associated with the user, the first candidate information being determined from the set of candidate information based on the aforementioned vectors.