Patents by Inventor Dakuo Wang
Dakuo Wang 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).
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Patent number: 11966340Abstract: To automate time series forecasting machine learning pipeline generation, a data allocation size of time series data may be determined based on one or more characteristics of a time series data set. The time series data may be allocated for use by candidate machine learning pipelines based on the data allocation size. Features for the time series data may be determined and cached by the candidate machine learning pipelines. Predictions of each of the candidate machine learning pipelines using at least the one or more features may be evaluated. A ranked list of machine learning pipelines may be automatically generated from the candidate machine learning pipelines for time series forecasting based upon evaluating predictions of each of the one or more candidate machine learning pipelines.Type: GrantFiled: March 15, 2022Date of Patent: April 23, 2024Assignee: International Business Machines CorporationInventors: Long Vu, Bei Chen, Xuan-Hong Dang, Peter Daniel Kirchner, Syed Yousaf Shah, Dhavalkumar C. Patel, Si Er Han, Ji Hui Yang, Jun Wang, Jing James Xu, Dakuo Wang, Gregory Bramble, Horst Cornelius Samulowitz, Saket K. Sathe, Wesley M. Gifford, Petros Zerfos
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Publication number: 20240111950Abstract: A computer-implemented method for fine-grained referring expression comprehension is provided. The computer-implemented method includes receiving, at a processor, a textual expression and an image as inputs and executing, at the processor, fine-grained referring expression comprehension. The executing includes decomposing the textual expression into different textual modules, extracting visual regional proposals from the image, using language-guided graph neural networks to mine fine-grained object relations from the visual regional proposals and aggregating different matching similarities between the different textual modules and the fine-grained object relations.Type: ApplicationFiled: September 28, 2022Publication date: April 4, 2024Inventors: Zhenfang Chen, Chuang Gan, Bo Wu, Dakuo Wang
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Patent number: 11928156Abstract: Obtain, at a computing device, a segment of computer code. With a classification module of a machine learning system executing on the computing device, determine a required annotation category for the segment of computer code. With an annotation generation module of the machine learning system executing on the computing device, generate a natural language annotation of the segment of computer code based on the segment of computer code and the required annotation category. Provide the natural language annotation to a user interface for display adjacent the segment of computer code.Type: GrantFiled: November 3, 2020Date of Patent: March 12, 2024Assignee: International Business Machines CorporationInventors: Dakuo Wang, Lingfei Wu, Xuye Liu, Yi Wang, Chuang Gan, Jing Xu, Xue Ying Zhang, Jun Wang, Jing James Xu
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Patent number: 11861469Abstract: An embodiment of the invention may include a method, computer program product, and system for creating a data analysis tool. The method may include a computing device that generates an AI pipeline based on an input dataset, wherein the AI pipeline is generated using an Automated Machine Learning program. The method may include converting the AI pipeline to a non-native format of the Automated Machine Learning program. This may enable the AI pipeline to be used outside of the Automated Machine Learning program, thereby increasing the usefulness of the created program by not tying it to the Automated Machine Learning program. Additionally, this may increase the efficiency of running the AI pipeline by eliminating unnecessary computations performed by the Automated Machine Learning program.Type: GrantFiled: July 2, 2020Date of Patent: January 2, 2024Assignee: International Business Machines CorporationInventors: Peter Daniel Kirchner, Gregory Bramble, Horst Cornelius Samulowitz, Dakuo Wang, Arunima Chaudhary, Gregory Filla
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Patent number: 11854305Abstract: A bi-directional spatial-temporal transformer neural network (BDSTT) is trained to predict original coordinates of a skeletal joint in a specific frame through relative relationships of the skeletal joint to other joints and to the state of the skeletal joint in other frames. Obtain a plurality of frames comprising coordinates of the skeletal joint and coordinates of other joints. Produce a spatially masked frame by masking the original coordinates of the skeletal joint. Provide the specific frame, the spatially masked frame, and at least one more frame to a coordinate prediction head of the BDSTT. Obtain, from the coordinate prediction head, a prediction of coordinates for the skeletal joint. Adjust parameters of the BDSTT until a mean-squared error, between the prediction of coordinates for the skeletal joint and the original coordinates of the skeletal joint, converges.Type: GrantFiled: May 9, 2021Date of Patent: December 26, 2023Assignee: International Business Machines CorporationInventors: Bo Wu, Chuang Gan, Dakuo Wang, Kaizhi Qian
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Publication number: 20230394846Abstract: A vehicle light signal detection and recognition method, system, and computer program product include bounding, using a coarse attention module, one or more regions of an image of an automobile including at least one of a brake light and a signal light generated by automobile signals which include illuminated sections to generate one or more bounded region, removing, using a fine attention module, noise from the one or more bounded regions to generate one or more noise-free bounded regions, and identifying the at least one of the brake light and the signal light from the one or more noise-free bounded regions.Type: ApplicationFiled: August 7, 2023Publication date: December 7, 2023Inventors: Bo Wu, Chuang GAN, Yang ZHANG, Dakuo WANG
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Patent number: 11824819Abstract: A method, a computer program product, and a computer system generate an accurate mental model of an automated agent. The method includes receiving an input from a user device associated with a user during a communication session between the user and the automated agent. The method includes determining a response to the input. The method includes determining a confidence score of the response relative to a confidence threshold. The method includes determining an assertiveness feature associated with the response, the assertiveness feature comprising an expression of the automated agent based on the confidence score. The method includes transmitting the response and the assertiveness feature to the user device, the expression configured to update anthropomorphic characteristics of a graphical representation of the automated agent shown on a graphical user interface of the communication session displayed on a display device of the user device.Type: GrantFiled: January 26, 2022Date of Patent: November 21, 2023Assignee: International Business Machines CorporationInventors: Qian Pan, James Johnson, Zahra Ashktorab, Dakuo Wang
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Publication number: 20230368529Abstract: One or more computer processors improve action recognition by removing inference introduced by visual appearances of objects within a received video segment. The one or more computer processors extract appearance information and structure information from a received video segment. The one or more computer processors calculate a factual inference (TE) for the received video segment utilizing the extracted appearance information and structure information. The one or more computer processors calculate a counterfactual debiasing inference (NDE) for the received video segment. The one or more computer processors calculate a total indirect effect (TIE) by subtracting the calculated counterfactual debiased inference from the calculated factual inference. The one or more computer processors action recognize the received video segment by selecting a classification result associated with a highest calculated TIE.Type: ApplicationFiled: May 10, 2022Publication date: November 16, 2023Inventors: Bo Wu, Chuang Gan, Pin-Yu Chen, Zhenfang Chen, Dakuo Wang
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Patent number: 11816889Abstract: Unsupervised learning for video classification. One or more features from one or more video clips are extracted using a spatial-temporal encoder. The one or more extracted features are processed, using a video instance discrimination task, to generate a classification label, the classification label indicating whether two of the video clips are from a same video. The one or more extracted features are processed, using a pair-wise speed discrimination task, to generate a comparison label, the comparison label indicating a relative playback speed between two given video clips. A search is performed in a video database for a video that is similar to a given video based on the comparison label.Type: GrantFiled: March 29, 2021Date of Patent: November 14, 2023Assignee: International Business Machines CorporationInventors: Chuang Gan, Dakuo Wang, Antonio Jose Jimeno Yepes, Bo Wu
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Publication number: 20230306738Abstract: According to one embodiment, a method, computer system, and computer program product for identifying one or more intrinsic physical properties of one or more objects is provided. The present invention may include identifying one or more objects in a video set, extracting observable physical properties of the identified one or more objects from the video set, including one or more trajectories, and inferring, by a property-based graph neural network, intrinsic properties of the one or more objects based on the trajectories.Type: ApplicationFiled: March 24, 2022Publication date: September 28, 2023Inventors: Zhenfang Chen, Chuang Gan, Bo Wu, Dakuo Wang
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Patent number: 11763084Abstract: A method comprises receiving a new data set; identifying at least one prior data set of a plurality of prior data sets that matches the new data set; generating a natural language data science problem statement for the new data set based on information associated with the at least prior one data set that matches the new data set; outputting the generated natural language data science problem statement for user verification; and in response to receiving user input verifying the natural language generated data science problem statement, generating one or more AutoAI configuration settings for the new data set based on one or more AutoAI configuration settings associated with the at least one prior data set that matches the new data set.Type: GrantFiled: August 10, 2020Date of Patent: September 19, 2023Assignee: International Business Machines CorporationInventors: Dakuo Wang, Arunima Chaudhary, Chuang Gan, Mo Yu, Qian Pan, Sijia Liu, Daniel Karl I. Weidele, Abel Valente
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Patent number: 11741722Abstract: A vehicle light signal detection and recognition method, system, and computer program product include bounding, using a coarse attention module, one or more regions of an image of an automobile including at least one of a brake light and a signal light generated by automobile signals which include illuminated sections to generate one or more bounded region, removing, using a fine attention module, noise from the one or more bounded regions to generate one or more noise-free bounded regions, and identifying the at least one of the brake light and the signal light from the one or more noise-free bounded regions.Type: GrantFiled: September 4, 2020Date of Patent: August 29, 2023Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Bo Wu, Chuang Gan, Yang Zhang, Dakuo Wang
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Patent number: 11736423Abstract: Systems, computer-implemented methods, and/or computer program products facilitating a process to identify and respond to a primary electronic message are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can include a determination component can determine that a primary electronic message has not received a response electronic message. An analysis component can generate a generated electronic message addressing the informational or emotional content of the primary electronic message. In one or more embodiments, an updating component can update the analytical model based on one or more feedbacks to the generated electronic message, where the analytical model can remain active while being updated.Type: GrantFiled: May 4, 2021Date of Patent: August 22, 2023Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Dakuo Wang, Mo Yu, Chuang Gan, Bo Wu
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Patent number: 11727686Abstract: Systems and techniques that facilitate few-shot temporal action localization based on graph convolutional networks are provided. In one or more embodiments, a graph component can generate a graph that models a support set of temporal action classifications. Nodes of the graph can correspond to respective temporal action classifications in the support set. Edges of the graph can correspond to similarities between the respective temporal action classifications. In various embodiments, a convolution component can perform a convolution on the graph, such that the nodes of the graph output respective matching scores indicating levels of match between the respective temporal action classifications and an action to be classified. In various embodiments, an instantiation component can input into the nodes respective input vectors based on a proposed feature vector representing the action to be classified.Type: GrantFiled: September 21, 2021Date of Patent: August 15, 2023Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Chuang Gan, Ming Tan, Yang Zhang, Dakuo Wang
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Publication number: 20230239258Abstract: A method, a computer program product, and a computer system generate an accurate mental model of an automated agent. The method includes receiving an input from a user device associated with a user during a communication session between the user and the automated agent. The method includes determining a response to the input. The method includes determining a confidence score of the response relative to a confidence threshold. The method includes determining an assertiveness feature associated with the response, the assertiveness feature comprising an expression of the automated agent based on the confidence score. The method includes transmitting the response and the assertiveness feature to the user device, the expression configured to update anthropomorphic characteristics of a graphical representation of the automated agent shown on a graphical user interface of the communication session displayed on a display device of the user device.Type: ApplicationFiled: January 26, 2022Publication date: July 27, 2023Inventors: Qian Pan, James Johnson, Zahra Ashktorab, Dakuo Wang
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Patent number: 11688111Abstract: Systems, computer-implemented methods, and computer program products to facilitate visualization of a model selection process are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise an interaction backend handler component that obtains one or more assessment metrics of a model pipeline candidate. The computer executable components can further comprise a visualization render component that renders a progress visualization of the model pipeline candidate based on the one or more assessment metrics.Type: GrantFiled: July 29, 2020Date of Patent: June 27, 2023Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Dakuo Wang, Bei Chen, Ji Hui Yang, Abel Valente, Arunima Chaudhary, Chuang Gan, John Dillon Eversman, Voranouth Supadulya, Daniel Karl I. Weidele, Jun Wang, Jing James Xu, Dhavalkumar C. Patel, Long Vu, Syed Yousaf Shah, Si Er Han
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Patent number: 11689488Abstract: A deep learning module classifies messages received from a plurality of entities into one or more conversation threads. In response to receiving a subsequent message, the deep learning module determines which of the one or more conversation threads and a new conversation thread is contextually a best fit for the subsequent message. The subsequent message is added to the determined conversation thread.Type: GrantFiled: May 6, 2021Date of Patent: June 27, 2023Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventors: Ming Tan, Haoyu Wang, Dakuo Wang, Chuang Gan
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Publication number: 20230177032Abstract: A computer-implemented method according to one embodiment includes identifying a data set and meta information; and augmenting the data set with additional features in response to an automatic analysis of the data set in view of the meta information.Type: ApplicationFiled: December 8, 2021Publication date: June 8, 2023Inventors: Daniel Karl I. Weidele, Lisa Amini, Udayan Khurana, Kavitha Srinivas, Horst Cornelius Samulowitz, Takaaki Tateishi, Carolina Maria Spina, Dakuo Wang, Abel Valente, Arunima Chaudhary, Toshihiro Takahashi
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Patent number: 11663823Abstract: Dual-modality relation networks for audio-visual event localization can be provided. A video feed for audio-visual event localization can be received. Based on a combination of extracted audio features and video features of the video feed, informative features and regions in the video feed can be determined by running a first neural network. Based on the informative features and regions in the video feed determined by the first neural network, relation-aware video features can be determined by running a second neural network. Based on the informative features and regions in the video feed, relation-aware audio features can be determined by running a third neural network. A dual-modality representation can be obtained based on the relation-aware video features and the relation-aware audio features by running a fourth neural network. The dual-modality representation can be input to a classifier to identity an audio-visual event in the video feed.Type: GrantFiled: August 10, 2020Date of Patent: May 30, 2023Assignee: International Business Machines CorporationInventors: Chuang Gan, Dakuo Wang, Yang Zhang, Bo Wu, Xiaoxiao Guo
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Publication number: 20230153634Abstract: A domain of an input dataset is identified and one or more archived domain knowledge features corresponding to the identified domain are identified. One or more user feature definitions for one or more user features defined by a user are inputted. The identified archived domain knowledge features and the user features are processed to generate a set of candidate features for presentation to the user. A selection of a subset of the candidate features is obtained from the user and one or more predictive models are generated based on the selected features.Type: ApplicationFiled: November 14, 2021Publication date: May 18, 2023Inventors: Dakuo Wang, Udayan Khurana, Chuang Gan, Gregory Bramble, Abel Valente, Arunima Chaudhary, Carolina Maria Spina, Micah Smith