Patents by Inventor Pedro Andres Forero

Pedro Andres Forero has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20250016105
    Abstract: A method for controlling congestion in intermittently-connected and lossy computer networks comprising: determining, at a local network node, a payoff score for each of a plurality of active flows of network traffic, wherein each active flow consists of a stream of in-transit packets at the local network node that come from a common source and share a common destination, wherein each active flow's payoff score is based on a pricing model that considers both a sojourn time and a position in a queue of each of an active flow's constituent packets; allocating unused buffer space across all active flows in the local network node based on relative traffic loads with a buffer-space allocation (BSA) agent; and controlling a rate at which packets from all active flows are received at the local network node with a hop-by-hop local-flow-control (LFC) agent according to each flow's payoff score.
    Type: Application
    Filed: July 21, 2023
    Publication date: January 9, 2025
    Inventors: Pedro Andres Forero, Peng Zhang, Dusan Radosevic
  • Patent number: 10268931
    Abstract: A method for constructing a dictionary to represent data from a training data set comprising: modeling the data as a linear combination of columns; modeling outliers in the data set via deterministic outlier vectors; formatting the training data set in matrix form for processing; defining an underlying structure in the data set; quantifying a similarity across the data; building a Laplacian matrix; using group-Lasso regularizers to succinctly represent the data; choosing scalar parameters for controlling the number of dictionary columns used to represent the data and the number of elements of the training data set identified as outliers; using BCD and PG methods on the vector-matrix-formatted data set to estimate a dictionary, corresponding expansion coefficients, and the outlier vectors; and using a length of the outlier vectors to identify outliers in the data.
    Type: Grant
    Filed: March 29, 2017
    Date of Patent: April 23, 2019
    Assignee: The United States of America as represented by Secretary of the Navy
    Inventors: Scott Allen Shafer, Pedro Andres Forero, Joshua David Harguess
  • Publication number: 20170286811
    Abstract: A method for constructing a dictionary to represent data from a training data set comprising: modeling the data as a linear combination of columns; modeling outliers in the data set via deterministic outlier vectors; formatting the training data set in matrix form for processing; defining an underlying structure in the data set; quantifying a similarity across the data; building a Laplacian matrix; using group-Lasso regularizers to succinctly represent the data; choosing scalar parameters for controlling the number of dictionary columns used to represent the data and the number of elements of the training data set identified as outliers; using BCD and PG methods on the vector-matrix-formatted data set to estimate a dictionary, corresponding expansion coefficients, and the outlier vectors; and using a length of the outlier vectors to identify outliers in the data.
    Type: Application
    Filed: March 29, 2017
    Publication date: October 5, 2017
    Inventors: Scott Allen Shafer, Pedro Andres Forero, Joshua David Harguess