公开(公告)号：US20220107828A1

公开(公告)日：2022-04-07

申请号：US17555072

申请日：2021-12-17

Applicant: Intel Corporation

Inventor： Hesham Mostafa

IPC: G06F9/455

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to generate usage dependent code embeddings. An example apparatus includes parsing circuitry to select a usage context of a code snippet including at least one line of code (LOC) before the code snippet or an LOC at which the code snippet is called, the code snippet, and at least one LOC after the code snippet or the LOC. The example apparatus additionally includes embedding circuitry to generate a first list of token embedding vectors for first tokens of a second list of tokens for the code snippet and a third list of token embedding vectors for second tokens of a fourth list of tokens for the usage context. The example apparatus also includes concatenation circuitry to concatenate a transformed token embedding vector of a close token and a fifth list of transformed token embedding vectors for the first list.

公开(公告)号：US12078498B2

公开(公告)日：2024-09-03

申请号：US17131427

申请日：2020-12-22

Applicant: Intel Corporation

Inventor： Nesreen K. Ahmed ,  Ignacio J. Alvarez ,  Ravikumar Balakrishnan ,  Hesham Mostafa ,  Giuseppe Raffa ,  Nageen Himayat

IPC: G06N20/00 ,  G01C21/34 ,  G06N3/08

CPC classification number: G01C21/3484 ,  G06N3/08 ,  G06N20/00

Abstract: Methods, systems, and computer programs are presented for implementing Personalized Mobility as a Service (PMaaS) to improve transportation services delivery. One storage medium includes instructions for detecting, by a mobility as a service (MaaS) system, a request for a trip from a user device of a user. The storage medium further includes instructions for mapping, using a model executing on the machine, the user to a persona from a plurality of persona models. Each persona model has one or more characteristics associated with users of the MaaS system. Further yet, the storage medium includes instructions for determining trip parameters for the trip based on the persona mapped to the user, the trip parameters defining one or more trip segments for the trip, and instructions for providing trip parameters to the user device.

公开(公告)号：US11681541B2

公开(公告)日：2023-06-20

申请号：US17555072

申请日：2021-12-17

Applicant: Intel Corporation

Inventor： Hesham Mostafa

IPC: G06F9/44 ,  G06F9/455

CPC classification number: G06F9/45529

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to generate usage dependent code embeddings. An example apparatus includes parsing circuitry to select a usage context of a code snippet including at least one line of code (LOC) before the code snippet or an LOC at which the code snippet is called, the code snippet, and at least one LOC after the code snippet or the LOC. The example apparatus additionally includes embedding circuitry to generate a first list of token embedding vectors for first tokens of a second list of tokens for the code snippet and a third list of token embedding vectors for second tokens of a fourth list of tokens for the usage context. The example apparatus also includes concatenation circuitry to concatenate a transformed token embedding vector of a close token and a fifth list of transformed token embedding vectors for the first list.

公开(公告)号：US20230177349A1

公开(公告)日：2023-06-08

申请号：US17920839

申请日：2021-05-29

Applicant: Intel Corporation

Inventor： Ravikumar Balakrishnan ,  Nageen Himayat ,  Mustafa Riza Akdeniz ,  Sagar Dhakal ,  Arjun Anand ,  Hesham Mostafa

IPC: G06N3/098 ,  H04L67/10

CPC classification number: G06N3/098 ,  H04L67/10

Abstract: The apparatus of an edge computing node, a system, a method and a machine-readable medium. The apparatus includes a processor to cause an initial set of weights for a global machine learning (ML) model to be transmitted a set of client compute nodes of the edge computing network; process Hessians computed by each of the client compute nodes based on a dataset stored on the client compute node; evaluate a gradient expression for the ML model based on a second dataset and an updated set of weights received from the client compute nodes; and generate a meta-updated set of weights for the global model based on the initial set of weights, the Hessians received, and the evaluated gradient expression.

公开(公告)号：US20220284353A1

公开(公告)日：2022-09-08

申请号：US17631858

申请日：2020-09-23

Applicant: Intel Corporation

Inventor： Hesham Mostafa ,  Casimir M. Wierzynski

IPC: G06N20/20 ,  G06N7/00

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to train a machine learning model. An example apparatus to generate adaptive hyper-parameters includes a model aggregator to, in response to obtaining at least one model trained using a first set of hyper-parameters of a probability distribution, generate a loss reduction, a hyper-parameter generator to, when the loss reduction satisfies a loss threshold, update the probability distribution and generate a second set of hyper-parameters using the updated probability distribution, and an interface to transmit the second set of hyper-parameters to a client.