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    SYSTEMS AND METHODS FOR CAUSALITY-BASED MULTIVARIATE TIME SERIES ANOMALY DETECTION
    43.
    发明申请
    SYSTEMS AND METHODS FOR CAUSALITY-BASED MULTIVARIATE TIME SERIES ANOMALY DETECTION 有权

    公开(公告)号：US20220382856A1

    公开(公告)日：2022-12-01

    申请号：US17514487

    申请日：2021-10-29

    Applicant: salesforce.com, inc.

    Inventor： Wenzhuo Yang ,  Chu Hong Hoi ,  Kun Zhang

    IPC: G06F21/55 ,  G06N20/00

    Abstract: Embodiments described herein provide a causality-based anomaly detection mechanism that formulates multivariate time series as instances that do not follow the regular causal mechanism. Specifically, the causality-based anomaly detection mechanism leverages the causal structure discovered from data so that the joint distribution of multivariate time series is factorized into simpler modules where each module corresponds to a local causal mechanism, reflected by the corresponding conditional distribution. Those local mechanisms are modular or autonomous and can then be handled separately. In light of this modularity property, the anomaly detection problem then naturally decomposed into a series of low-dimensional anomaly detection problems. Each sub-problem is concerned with a local mechanism.

    Spatial-temporal reasoning through pretrained language models for video-grounded dialogues
    44.
    发明授权
    Spatial-temporal reasoning through pretrained language models for video-grounded dialogues 有权

    公开(公告)号：US11487999B2

    公开(公告)日：2022-11-01

    申请号：US16860977

    申请日：2020-04-28

    Applicant: salesforce.com, inc.

    Inventor： Hung Le ,  Chu Hong Hoi

    IPC: G06N3/04 ,  G06N3/08 ,  G06F40/40 ,  H04N19/31 ,  H04N19/33 ,  G06V20/40

    Abstract: A system and method for generating a response in a video grounded dialogue are provided. A video-grounded dialogue neural network language model receives video input and text input. The text input includes a dialogue history between the model and a human user and a current utterance by the user. Encoded video input is generated using video encoding layers. Encoded text input is generated using text encoding layers. The encoded video input and the encoded text input are concatenated in to a single input sequence. A generative pre-trained transformer model generates the response to the current utterance from the singe input sequence.

    SYSTEMS AND METHODS FOR CONTRASTIVE LEARNING WITH SELF-LABELING REFINEMENT
    45.
    发明申请
    SYSTEMS AND METHODS FOR CONTRASTIVE LEARNING WITH SELF-LABELING REFINEMENT 有权

    公开(公告)号：US20220269946A1

    公开(公告)日：2022-08-25

    申请号：US17375728

    申请日：2021-07-14

    Applicant: salesforce.com, inc.

    Inventor： Pan Zhou ,  Caiming Xiong ,  Chu Hong Hoi

    IPC: G06N3/08 ,  G06N3/04

    Abstract: Embodiments described herein provide a contrastive learning mechanism with self-labeling refinement, which iteratively employs the network and data themselves to generate more accurate and informative soft labels for contrastive learning. Specifically, the contrastive learning framework includes a self-labeling refinery module to explicitly generate accurate labels, and a momentum mix-up module to increase similarity between a query and its positive, which in turn implicitly improves label accuracy.

    SYSTEM AND METHODS FOR TRAINING TASK-ORIENTED DIALOGUE (TOD) LANGUAGE MODELS
    47.
    发明申请
    SYSTEM AND METHODS FOR TRAINING TASK-ORIENTED DIALOGUE (TOD) LANGUAGE MODELS 有权

    公开(公告)号：US20220139384A1

    公开(公告)日：2022-05-05

    申请号：US17088206

    申请日：2020-11-03

    Applicant: salesforce.com, inc.

    Inventor： Chien-Sheng Wu ,  Chu Hong Hoi ,  Richard Socher ,  Caiming Xiong

    IPC: G10L15/18 ,  G10L15/06

    Abstract: Embodiments described herein provide methods and systems for training task-oriented dialogue (TOD) language models. In some embodiments, a TOD language model may receive a TOD dataset including a plurality of dialogues and a model input sequence may be generated from the dialogues using a first token prefixed to each user utterance and a second token prefixed to each system response of the dialogues. In some embodiments, the first token or the second token may be randomly replaced with a mask token to generate a masked training sequence and a masked language modeling (MLM) loss may be computed using the masked training sequence. In some embodiments, the TOD language model may be updated based on the MLM loss.

    Unsupervised representation learning with contrastive prototypes
    49.
    发明授权
    Unsupervised representation learning with contrastive prototypes 有权

    公开(公告)号：US11263476B2

    公开(公告)日：2022-03-01

    申请号：US16870621

    申请日：2020-05-08

    Applicant: salesforce.com, inc.

    Inventor： Junnan Li ,  Chu Hong Hoi

    IPC: G06K9/62 ,  G06T7/73

    Abstract: The system and method are directed to a prototypical contrastive learning (PCL). The PCL explicitly encodes the hierarchical semantic structure of the dataset into the learned embedding space and prevents the network from exploiting low-level cues for solving the unsupervised learning task. The PCL includes prototypes as the latent variables to help find the maximum-likelihood estimation of the network parameters in an expectation-maximization framework. The PCL iteratively performs an E-step for finding prototypes with clustering and M-step for optimizing the network on a contrastive loss.

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