公开(公告)号：US20240078431A1

公开(公告)日：2024-03-07

申请号：US18454262

申请日：2023-08-23

Applicant: NEC Laboratories America, Inc.

Inventor： Xuchao Zhang ,  Haifeng Chen ,  Chang Lu

IPC: G06N3/08 ,  G06F40/40 ,  G06N3/042 ,  G06N3/048

CPC classification number: G06N3/08 ,  G06F40/40 ,  G06N3/042 ,  G06N3/048

Abstract: Methods and systems for training a language model include retrieving a knowledge sentence, related to an input sentence, from a knowledge base. The input sentence, the knowledge sentence, and a prompt are encoded into an intermediate representation. The intermediate representation is decoded to generate a named entity from the input sentence that is of a type specified by the prompt. A language model is fine-tuned based on the named entity.

公开(公告)号：US20240071572A1

公开(公告)日：2024-02-29

申请号：US18471667

申请日：2023-09-21

Applicant: NEC Laboratories America, Inc.

Inventor： Renqiang Min ,  Hans Peter Graf ,  Ziqi Chen

IPC: G16B40/00 ,  G06N3/08 ,  G16B15/30

CPC classification number: G16B40/00 ,  G06N3/08 ,  G16B15/30

Abstract: A system for binding peptide search for immunotherapy is presented. The system includes employing a deep neural network to predict a peptide presentation given Major Histocompatibility Complex allele sequences and peptide sequences, training a Variational Autoencoder (VAE) to reconstruct peptides by converting the peptide sequences into continuous embedding vectors, running a Monte Carlo Tree Search to generate a first set of positive peptide vaccine candidates, running a Bayesian Optimization search with the trained VAE and a Backpropagation search with the trained VAE to generate a second set of positive peptide vaccine candidates, using a sampling from a Position Weight Matrix (sPWM) to generate a third set of positive peptide vaccine candidates, screening and merging the first, second, and third sets of positive peptide vaccine candidates, and outputting qualified peptides for immunotherapy from the screened and merged sets of positive peptide vaccine candidates.

公开(公告)号：US20240064555A1

公开(公告)日：2024-02-22

申请号：US18451412

申请日：2023-08-17

Applicant: NEC Laboratories America, Inc.

Inventor： Srimat Chakradhar ,  Murugan Sankaradas ,  Sandesh Dhawaskar Sathyanarayana

IPC: H04W28/02 ,  H04L45/302 ,  H04W28/24

CPC classification number: H04W28/0268 ,  H04L45/302 ,  H04W28/24

Abstract: Methods and systems for transmission over a heterogeneous network include determining a path through a first network, including collecting quality of service (QoS) parameters for network devices in the path. The QoS parameters of the network devices are configured to provide a predetermined QoS assurance across the path. A network flow is transmitted from a network slice of a second network through the first network, along the path.

公开(公告)号：US20240061739A1

公开(公告)日：2024-02-22

申请号：US18359309

申请日：2023-07-26

Applicant: NEC Laboratories America, Inc.

Inventor： Zhengzhang Chen ,  Haifeng Chen ,  Liang Tong ,  Dongjie Wang

IPC: G06F11/07

CPC classification number: G06F11/079 ,  G06F11/0709

Abstract: A computer-implemented method for identifying root cause failure and fault events is provided. The method includes detecting a trigger point, converting, via an encoder, previous system state data, new batch data in a next system state, and a causal graph to system state-invariant embeddings and system state-dependent embeddings, generating a learned causal graph, via a graph generation layer, by integrating state-invariant and state-dependent information, and predicting, by a prediction layer, future time-series data on the learned causal graph.

公开(公告)号：US11909479B2

公开(公告)日：2024-02-20

申请号：US17863720

申请日：2022-07-13

Applicant: NEC Laboratories America, Inc.

Inventor： Mohammad Khojastepour ,  Nariman Torkzaban

IPC: H04B7/06 ,  H04B7/10 ,  H04B7/155

CPC classification number: H04B7/0617 ,  H04B7/10 ,  H04B7/15507

Abstract: A method for shaping a mmWave wireless channel in a wireless network is presented. The method includes enabling communication between a multi-antenna transmitter and a multi-antenna receiver, positioning a reconfigurable intelligent surface (RIS) in a vicinity of the multi-antenna transmitter and the multi-antenna receiver, constructing the RIS as a uniform planar array (UPA) structure forming a multi-beamforming framework, a surface of the UPA defining an array of discrete elements arranged in a grid pattern, wherein parameters of the discrete elements of the UPA are controllable to achieve multiple disjoint beams covering different solid angles, and enabling the plurality of users of the plurality of mobile devices positioned in blind spots of a coverage map to communicate with the multi-antenna transmitter by employing the MS to generate sharp and effective beams having almost uniform gain in a desired angular coverage interval (ACI).

公开(公告)号：US20240054782A1

公开(公告)日：2024-02-15

申请号：US18366931

申请日：2023-08-08

Applicant: NEC Laboratories America, Inc.

Inventor： Kai Li ,  Renqiang Min ,  Haifeng Xia

IPC: G06V20/40 ,  G06V10/774

CPC classification number: G06V20/41 ,  G06V20/46 ,  G06V10/774 ,  G06V20/48

Abstract: Methods and systems for video processing include enriching an input video feature from an input video frame set using a meta-action bank video sub-actions to generate enriched features. Reinforced image representation is performed using reinforcement learning to compare support image frames and query image frames and determine an importance of the input video frame. A classification is performed on the input video frame based on the importance and the enriched features to generate a label. An action is performed responsive to the generated label.

公开(公告)号：US20240046606A1

公开(公告)日：2024-02-08

申请号：US18363175

申请日：2023-08-01

Applicant: NEC Laboratories America, Inc.

Inventor： Kai Li ,  Renqiang Min ,  Deep Patel ,  Erik Kruus ,  Xin Hu

IPC: G06V10/62 ,  G06V20/40 ,  G06V10/82 ,  G06V10/774 ,  G06V10/776 ,  G06V10/77

CPC classification number: G06V10/62 ,  G06V20/41 ,  G06V20/46 ,  G06V10/82 ,  G06V10/774 ,  G06V10/776 ,  G06V10/7715

Abstract: Methods and systems for temporal action localization include processing a video stream to identify an action and a start time and a stop time for the action using a neural network model that separately processes information of appearance and motion modalities from the video stream using transformer branches that include a self-attention and a cross-attention between the appearance and motion modalities. An action is performed responsive to the identified action.

公开(公告)号：US20240046128A1

公开(公告)日：2024-02-08

申请号：US18471564

申请日：2023-09-21

Applicant: NEC Laboratories America, Inc.

Inventor： Wenchao Yu ,  Wei Cheng ,  Haifeng Chen ,  Yuncong Chen ,  Xuchao Zhang ,  Tianxiang Zhao

IPC: G16H50/20

CPC classification number: G16H50/20

Abstract: A method for learning a self-explainable imitator by discovering causal relationships between states and actions is presented. The method includes obtaining, via an acquisition component, demonstrations of a target task from experts for training a model to generate a learned policy, training the model, via a learning component, the learning component computing actions to be taken with respect to states, generating, via a dynamic causal discovery component, dynamic causal graphs for each environment state, encoding, via a causal encoding component, discovered causal relationships by updating state variable embeddings, and outputting, via an output component, the learned policy including trajectories similar to the demonstrations from the experts.

公开(公告)号：US20240037403A1

公开(公告)日：2024-02-01

申请号：US18484872

申请日：2023-10-11

Applicant: NEC Laboratories America, Inc.

Inventor： Wei Cheng ,  Dongkuan Xu ,  Haifeng Chen

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: A method for performing contrastive learning for graph tasks and datasets by employing an information-aware graph contrastive learning framework is presented. The method includes obtaining two semantically similar views of a graph coupled with a label for training by employing a view augmentation component, feeding the two semantically similar views into respective encoder networks to extract latent representations preserving both structure and attribute information in the two views, optimizing a contrastive loss based on a contrastive mode by maximizing feature consistency between the latent representations, training a neural network with the optimized contrastive loss, and predicting a new graph label or a new node label in the graph.

公开(公告)号：US20240037401A1

公开(公告)日：2024-02-01

申请号：US18484851

申请日：2023-10-11

Applicant: NEC Laboratories America, Inc.

Inventor： Wei Cheng ,  Dongkuan Xu ,  Haifeng Chen

IPC: G06N3/08

CPC classification number: G06N3/08

Abstract: A method for performing contrastive learning for graph tasks and datasets by employing an information-aware graph contrastive learning framework is presented. The method includes obtaining two semantically similar views of a graph coupled with a label for training by employing a view augmentation component, feeding the two semantically similar views into respective encoder networks to extract latent representations preserving both structure and attribute information in the two views, optimizing a contrastive loss based on a contrastive mode by maximizing feature consistency between the latent representations, training a neural network with the optimized contrastive loss, and predicting a new graph label or a new node label in the graph.