公开(公告)号：US10542270B2

公开(公告)日：2020-01-21

申请号：US15874515

申请日：2018-01-18

Applicant: salesforce.com, inc.

Inventor： Yingbo Zhou ,  Luowei Zhou ,  Caiming Xiong ,  Richard Socher

IPC: H04N7/12 ,  H04N11/12 ,  H04N19/46 ,  H04N19/44 ,  H04N19/60 ,  H04N19/187 ,  H04N21/81 ,  H04N19/33 ,  H04N19/126 ,  H04N21/488 ,  H04N19/132

Abstract: Systems and methods for dense captioning of a video include a multi-layer encoder stack configured to receive information extracted from a plurality of video frames, a proposal decoder coupled to the encoder stack and configured to receive one or more outputs from the encoder stack, a masking unit configured to mask the one or more outputs from the encoder stack according to one or more outputs from the proposal decoder, and a decoder stack coupled to the masking unit and configured to receive the masked one or more outputs from the encoder stack. Generating the dense captioning based on one or more outputs of the decoder stack. In some embodiments, the one or more outputs from the proposal decoder include a differentiable mask. In some embodiments, during training, error in the dense captioning is back propagated to the decoder stack, the encoder stack, and the proposal decoder.

公开(公告)号：US20190258939A1

公开(公告)日：2019-08-22

申请号：US15980207

申请日：2018-05-15

Applicant: salesforce.com, inc.

Inventor： Sewon Min ,  Victor Zhong ,  Caiming Xiong ,  Richard Socher

IPC: G06N3/08 ,  G06F17/27

Abstract: A natural language processing system that includes a sentence selector and a question answering module. The sentence selector receives a question and sentences that are associated with a context. For a question and each sentence, the sentence selector determines a score. A score represents whether the question is answerable with the sentence. Sentence selector then generates a minimum set of sentences from the scores associated with the question and sentences. The question answering module generates an answer for the question from the minimum set of sentences.

公开(公告)号：US20180373987A1

公开(公告)日：2018-12-27

申请号：US15983782

申请日：2018-05-18

Applicant: Salesforce.com,inc.

Inventor： Huishuai Zhang ,  Caiming Xiong

IPC: G06N3/08 ,  G06N7/00 ,  G06F17/11 ,  G06F17/16

Abstract: Embodiments for training a neural network are provided. A neural network is divided into a first block and a second block, and the parameters in the first block and second block are trained in parallel. To train the parameters, a gradient from a gradient mini-batch included in training data is generated. A curvature-vector product from a curvature mini-batch included in the training data is also generated. The gradient and the curvature-vector product generate a conjugate gradient. The conjugate gradient is used to determine a change in parameters in the first block in parallel with a change in parameters in the second block. The curvature matrix in the curvature-vector product includes zero values when the terms correspond to parameters from different blocks.

公开(公告)号：US20180336198A1

公开(公告)日：2018-11-22

申请号：US15885613

申请日：2018-01-31

Applicant: salesforce.com, inc.

Inventor： Victor Zhong ,  Caiming Xiong ,  Richard Socher

IPC: G06F17/30 ,  G06N3/08 ,  G06N7/00

Abstract: A computing system uses neural networks to translate natural language queries to database queries. The computing system uses a plurality of machine learning based models, each machine learning model for generating a portion of the database query. The machine learning models use an input representation generated based on terms of the input natural language query, a set of columns of the database schema, and the vocabulary of a database query language, for example, structured query language SQL. The plurality of machine learning based models may include an aggregation classifier model for determining an aggregation operator in the database query, a result column predictor model for determining the result columns of the database query, and a condition clause predictor model for determining the condition clause of the database query. The condition clause predictor is based on reinforcement learning.