Patents Examined by Ben M Rifkin
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Patent number: 11966833Abstract: A computing unit for accelerating a neural network is disclosed. The computing unit may include an input unit that includes a digital-to-analog conversion unit and an analog-to-digital conversion unit that is configured to receive an analog signal from the output of a last interconnected analog crossbar circuit of a plurality of analog crossbar circuits and convert the second analog signal into a digital output vector, and a plurality of interconnected analog crossbar circuits that include the first interconnected analog crossbar circuit and the last interconnected crossbar circuits, wherein a second interconnected analog crossbar circuit of the plurality of interconnected analog crossbar circuits is configured to receive a third analog signal from another interconnected analog crossbar circuit of the plurality of interconnected crossbar circuits and perform one or more operations on the third analog signal based on the matrix weights stored by the crosspoints of the second interconnected analog crossbar.Type: GrantFiled: August 9, 2018Date of Patent: April 23, 2024Assignee: Google LLCInventors: Pierre-Luc Cantin, Olivier Temam
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Patent number: 11803174Abstract: A building management system (BMS) includes sensors that measure time series values of building variables and a deterministic model generator that uses historical values for the time series of building variables to train a deterministic model that predicts deterministic values for the time series. The BMS includes a stochastic model generator that uses differences between actual values for the time series and the predicted deterministic values to train a stochastic model that predicts a stochastic value for the time series. The BMS includes a forecast adjuster that adjusts the predicted deterministic values using the predicted stochastic value to generate an adjusted forecast for the time series. The BMS includes a demand response optimizer that uses the adjusted forecast to generate an optimal set of control actions for building equipment of the BMS. The building equipment operate to affect the building variables.Type: GrantFiled: May 20, 2015Date of Patent: October 31, 2023Assignee: Johnson Controls Technology CompanyInventors: Mohammad N. Elbsat, Michael J. Wenzel
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Patent number: 11663520Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training machine learning systems. One of the methods includes receiving a plurality of training examples; and training a machine learning system on each of the plurality of training examples to determine trained values for weights of a machine learning model, wherein training the machine learning system comprises: assigning an initial value for a regularization penalty for a particular weight for a particular feature; and adjusting the initial value for the regularization penalty for the particular weight for the particular feature during the training of the machine learning system.Type: GrantFiled: August 26, 2019Date of Patent: May 30, 2023Assignee: Google LLCInventors: Yoram Singer, Tal Shaked, Tushar Deepak Chandra, Tze Way Eugene Ie
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Patent number: 11601703Abstract: A system and method provides video recommendations for a target video in a video sharing environment. The system selects one or more videos that are on one or more video playlists together with the target video. The video co-occurrence data of the target video associates the target video and another video on one or more same video playlists and frequency of the target video and another video on the video playlists is computed. Based on the video co-occurrence data of the target video, one or more co-occurrence videos are selected and ranked based on the video co-occurrence data of the target video. The system selects one or more videos from the co-occurrence videos as video recommendations for the target video.Type: GrantFiled: September 26, 2016Date of Patent: March 7, 2023Assignee: Google LLCInventors: Li Wei, Kun Zhang, Yu He, Xinmei Cai
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Patent number: 11526773Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting the accuracy of user submissions. One of the methods includes receiving, from a user, an update to an attribute of an entity related to a topic. If the user is determined to be reliable relative to the topic based on user profile data of the user, the knowledge base is updated with the update to the attribute of the entity.Type: GrantFiled: March 4, 2019Date of Patent: December 13, 2022Assignee: GOOGLE LLCInventors: Krzysztof Czuba, Evgeniy Gabrilovich
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Patent number: 11511420Abstract: A machine learning device, which learns an operation program of a robot, includes a state observation unit which observes as a state variable at least one of a shaking of an arm of the robot and a length of an operation trajectory of the arm of the robot; a determination data obtaining unit which obtains as determination data a cycle time in which the robot performs processing; and a learning unit which learns the operation program of the robot based on an output of the state observation unit and an output of the determination data obtaining unit.Type: GrantFiled: September 12, 2017Date of Patent: November 29, 2022Assignee: FANUC CORPORATIONInventor: Syuntarou Toda
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Patent number: 11507063Abstract: A building management system (BMS) includes sensors that measure time series values of building variables and a deterministic model generator that uses historical values for the time series of building variables to train a deterministic model that predicts deterministic values for the time series. The BMS includes a stochastic model generator that uses differences between actual values for the time series and the predicted deterministic values to train a stochastic model that predicts a stochastic value for the time series. The BMS includes a forecast adjuster that adjusts the predicted deterministic values using the predicted stochastic value to generate an adjusted forecast for the time series. The BMS includes a demand response optimizer that uses the adjusted forecast to generate an optimal set of control actions for building equipment of the BMS. The building equipment operate to affect the building variables.Type: GrantFiled: May 20, 2015Date of Patent: November 22, 2022Assignee: Johnson Controls Technology CompanyInventors: Mohammad N. Elbsat, Michael J. Wenzel
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Patent number: 11489857Abstract: A method and system for controlling access to an Internet resource is disclosed herein. When a request for an Internet resource, such as a Web site, is transmitted by an end-user of a LAN, a security appliance for the LAN analyzes a reputation index for the Internet resource before transmitting the request over the Internet. The reputation index is based on a reputation vector which includes a plurality of factors for the Internet resource such as country of domain registration, country of service hosting, country of an internet protocol address block, age of a domain registration, popularity rank, internet protocol address, number of hosts, to-level domain, a plurality of run-time behaviors, JavaScript block count, picture count, immediate redirect and response latency. If the reputation index for the Internet resource is at or above a threshold value established for the LAN, then access to the Internet resource is permitted.Type: GrantFiled: May 6, 2013Date of Patent: November 1, 2022Assignee: Webroot Inc.Inventors: Ron Hegli, Hal Lonas, Christopher K. Harris
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Patent number: 11429272Abstract: A multi-factor probabilistic model evaluates user input to determine if the user input was intended for an on-screen user interface control. When user input is received, a probability is computed that the user input was intended for each on-screen user interface control. The user input is then associated with the user interface control that has the highest computed probability. The probability that user input was intended for each user interface control may be computed utilizing a multitude of factors including the probability that the user input is near each user interface control, the probability that the motion of the user input is consistent with the user interface control, the probability that the shape of the user input is consistent with the user interface control, and that the size of the user input is consistent with the user interface control.Type: GrantFiled: March 26, 2010Date of Patent: August 30, 2022Assignee: Microsoft Technology Licensing, LLCInventor: Andrew David Wilson
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Patent number: 11416763Abstract: A classifier training method includes detecting error data from training data; and training a classifier configured to detect an object based on the error data.Type: GrantFiled: February 9, 2016Date of Patent: August 16, 2022Assignee: Samsung Electronics Co., Ltd.Inventors: Jingu Heo, Dong Kyung Nam
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Patent number: 11397896Abstract: An autonomous thinking pattern generator including a pattern converter configured to convert input information to patterns, the input information including image information, sound information or language, a pattern recorder configured to record the patterns, a pattern controller configured to set and change the patterns, and form connective relations between the patterns, and an information analyzer configured to evaluate values of the input information is provided. The pattern recorder is configured to record the patterns corresponding to the input information which is determined as worthy by the information analyzer autonomously.Type: GrantFiled: October 20, 2014Date of Patent: July 26, 2022Inventor: Hiroaki Miyazaki
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Patent number: 11343156Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for routing events of an event stream in a stream processing system. One of the methods includes receiving, by a router, an event stream of events; identifying, for each event, by the router, a respective partition of context data that includes context data related to the event and providing the event to a respective local modeler that stores the partition of context data identified for the event in operational memory of the local modeler; processing, by each local modeler, events received from the router and aggregating information associated with each event to generate aggregated information; providing, by one or more of the local modelers, to a central modeler, the respective aggregated information; and determining, by the central modeler, a plurality of parameters of a machine learning model using the received aggregated information.Type: GrantFiled: May 12, 2015Date of Patent: May 24, 2022Assignee: Pivotal Software, Inc.Inventors: Michael Brand, Lyndon John Adams, David Russell Brown, Kee Siong Ng
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Patent number: 11250342Abstract: A classifier is computed as follows. For a first set of values of primary field(s) of primary data instances of a labeled primary training dataset, a second set(s) of secondary fields of unclassified second data instances of secondary dataset(s) is identified. First set of values are matched to corresponding values in respective secondary field(s), and linked to other secondary fields of respective secondary data instance(s) of the respective matched secondary field. A set of classification features is generated. Each including: (i) condition(s), and (ii) a value selected from the linked other secondary fields of the respective secondary data instance(s) of the respective matched secondary field(s). The respective classification feature outputs a binary value computed by the condition(s) that compares between the value selected from the other linked secondary fields and a new received data instance. A classifier is computed according to a selected subset of the classification features.Type: GrantFiled: May 26, 2016Date of Patent: February 15, 2022Assignee: SparkBeyond Ltd.Inventors: Meir Maor, Ron Karidi, Sagie Davidovich, Amir Ronen
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Patent number: 11240286Abstract: In filtering requests to be forwarded to a runtime environment, a filtering apparatus intercepts a new runtime request for the runtime environment and determines execution paths that may be traversed by the runtime request when executed in the runtime environment. The filtering apparatus assigns a probability of traversal by the runtime request to each of the execution paths and identifies at least one given execution path that reference a stressed resource of the runtime environment. Based on the probabilities assigned to the at least one given execution path, the filtering apparatus determines whether or not to block the runtime request from being sent to the runtime environment. If the probability assigned to the at least one given execution path exceeds a configured threshold, the runtime request is blocked from being sent to the runtime environment. Otherwise, the runtime request is sent to the runtime environment.Type: GrantFiled: June 29, 2015Date of Patent: February 1, 2022Assignee: International Business Machines CorporationInventors: Kyle G. Brown, Samir A. Nasser
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Patent number: 11238343Abstract: Embodiments of the invention relate to a scalable neural hardware for the noisy-OR model of Bayesian networks. One embodiment comprises a neural core circuit including a pseudo-random number generator for generating random numbers. The neural core circuit further comprises a plurality of incoming electronic axons, a plurality of neural modules, and a plurality of electronic synapses interconnecting the axons to the neural modules. Each synapse interconnects an axon with a neural module. Each neural module receives incoming spikes from interconnected axons. Each neural module represents a noisy-OR gate. Each neural module spikes probabilistically based on at least one random number generated by the pseudo-random number generator unit.Type: GrantFiled: November 30, 2018Date of Patent: February 1, 2022Assignee: International Business Machines CorporationInventors: John V. Arthur, Steven K. Esser, Paul A. Merolla, Dharmendra S. Modha
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Patent number: 11232378Abstract: A system for generating a graphical user interface in a client device. The system may include a processor in communication with the client device and a database. The processor may execute: receiving a request for occupancy information of a specified merchant; obtaining a plurality of credit card authorizations associated with the merchant; generating a posted transaction array based on the credit card authorizations; removing outlier members of the posted transaction array by applying a threshold filter; generating a transaction frequency array based on the posted transaction array, the transaction frequency array comprising weekdays and aggregated transactions associated with the weekdays; modifying the transaction frequency array by applying a transformation to the aggregated transactions; generating a smoothed array by applying a kernel density estimate to the transaction frequency array; and generating a graphical user interface displaying information in the smoothed array.Type: GrantFiled: May 22, 2018Date of Patent: January 25, 2022Assignee: Capital One Services, LLCInventors: Ashish Bansal, Jonathan Mark Stahlman, Kai-Ting Neo
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Patent number: 11176445Abstract: Embodiments of the invention relate to canonical spiking neurons for spatiotemporal associative memory. An aspect of the invention provides a spatiotemporal associative memory including a plurality of electronic neurons having a layered neural net relationship with directional synaptic connectivity. The plurality of electronic neurons configured to detect the presence of a spatiotemporal pattern in a real-time data stream, and extract the spatiotemporal pattern. The plurality of electronic neurons are further configured to, based on learning rules, store the spatiotemporal pattern in the plurality of electronic neurons, and upon being presented with a version of the spatiotemporal pattern, retrieve the stored spatiotemporal pattern.Type: GrantFiled: April 21, 2017Date of Patent: November 16, 2021Assignee: International Business Machines CorporationInventors: Steve Kyle Esser, Dharmendra S. Modha, Anthony Ndirango
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Patent number: 11170302Abstract: Methods and apparatus are provided that permit estimation of eigenphase or eigenvalue gaps in which random or pseudo-random unitaries are applied to a selected initial quantum state to produce a random quantum state. A target unitary is then applied to the random quantum state one or more times, or an evolution time is allowed to elapse after application of the target unitary. An inverse of the pseudo-random unitary used to produce the random quantum state is applied, and the resultant state is measured with respect to the initial quantum state. Measured values are used to produce Bayesian updates, and eigenvalue/eigenvector gaps are estimated. In some examples, the disclosed methods are used in amplitude estimate and control map determinations. Eigenvalue gaps for time-dependent Hamiltonians can be evaluated by adiabatic evolution of the Hamiltonian from an initial Hamiltonian to a final Hamiltonian.Type: GrantFiled: February 17, 2017Date of Patent: November 9, 2021Assignee: Microsoft Technology Licensing, LLCInventors: Nathan Wiebe, Ilia Zintchenko
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Patent number: 11163269Abstract: A computer-implemented method is provided for training a classification model. The method includes preparing, by a processor, positive and negative class data. The method further includes iteratively training the classification model, by the processor, using the positive class data and the negative class data such that the positive class data is reconstructed and the negative class data is prevented from being constructed, by the classification model. In response to a selection of a non-integer value as a number of negative learning iterations to be performed to train the classification model, a particular set of the negative class data that is reconstructed best by the classification model from among all of the negative class data is selected to be used for negative learning by the classification model. The training based on the positive class data is performed once before the negative learning iterations and once after each negative learning iteration.Type: GrantFiled: September 11, 2017Date of Patent: November 2, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventor: Asim Munawar
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Patent number: 11156968Abstract: A computer-implemented method is provided for training a classification model. The method includes preparing, by a processor, positive and negative class data. The method further includes iteratively training the classification model, by the processor, using the positive class data and the negative class data such that the positive class data is reconstructed and the negative class data is prevented from being constructed, by the classification model. In response to a selection of a non-integer value as a number of negative learning iterations to be performed to train the classification model, a particular set of the negative class data that is reconstructed best by the classification model from among all of the negative class data is selected to be used for negative learning by the classification model. The training based on the positive class data is performed once before the negative learning iterations and once after each negative learning iteration.Type: GrantFiled: December 15, 2017Date of Patent: October 26, 2021Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATIONInventor: Asim Munawar