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公开(公告)号：US20220414477A1
公开(公告)日：2022-12-29
申请号：US17358148
申请日：2021-06-25
摘要： In an approach for explaining a theorem proving model, a processor predicts a truth value of a query through a pre-trained theorem proving model, based on the query and one or more facts and rules in a knowledge base. A processor ranks the one or more facts and rules according to contribution, calculated in a pre-defined scoring method, made to the predicted truth value of the query. A processor generates a proof of the predicted truth value, wherein the proof is one or more logical steps that demonstrate the predicted truth value in a natural language. A processor outputs the proof.
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公开(公告)号：US11537943B2
公开(公告)日：2022-12-27
申请号：US16714070
申请日：2019-12-13
申请人： SAP SE
发明人： Yang Peng
摘要： Calls received by a data center that are associated with a request are monitored. Features are subsequently extracted from the monitored calls so that a machine learning model may use such features to determine that the request will cause the data center to malfunction. The machine learning model can be trained using data derived from a transaction log for the data center. At least one correction action to prevent the data center from malfunctioning can then be initiated in response to such determination. Related apparatus, systems, techniques and articles are also described.
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83.发明授权公开(公告)号：US11537840B2
公开(公告)日：2022-12-27
申请号：US16189264
申请日：2018-11-13
发明人： Danilo Pietro Pau , Emanuele Plebani , Fabio Giuseppe De Ambroggi , Floriana Guido , Angelo Bosco
摘要： A neural network classifies an input signal. For example, an accelerometer signal may be classified to detect human activity. In a first convolutional layer, two-valued weights are applied to the input signal. In a first two-valued function layer coupled at input to an output of the first convolutional layer, a two-valued function is applied. In a second convolutional layer coupled at input to an output of the first two-valued functional layer, weights of the second convolutional layer are applied. In a fully-connected layer coupled at input to an output of the second convolutional layer, two-valued weights of the fully connected layer are applied. In a second two-valued function layer coupled at input to an output of the fully connected layer, a two-valued function of the second two-valued function layer is applied. A classifier classifies the input signal based on an output signal of second two-valued function layer.
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公开(公告)号：US11531903B2
公开(公告)日：2022-12-20
申请号：US16945876
申请日：2020-08-02
申请人： Actimize LTD.
发明人： Ganir Tamir , Danny Butvinik , Yoav Avneon
摘要： A computerized-method for real-time detection of real concept drift in predictive machine learning models, by processing high-speed streaming data. The computerized-method includes: receiving a real-time data stream having labeled and unlabeled instances. Obtaining a window of ‘n’ instances having a portion of the ‘n’ instances as reliable labels. Computing posterior distribution of the reliable labels; and operating a Drift-Detection (DD) module. The DD module is configured to: operate a kernel density estimation on the computed posterior distribution for sensitivity control of the DD module; operate an error rate function on the estimated kernel density to yield an error value; and train an incremental estimator module, according to the kernel density estimation. When the error value is not above a preconfigured drift threshold repeating operations (i) through (iii), else when the error value is above the preconfigured drift threshold, at least one concept drift related action takes place.
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公开(公告)号：US20220398921A1
公开(公告)日：2022-12-15
申请号：US17838772
申请日：2022-06-13
发明人： Parth JAGGI , Scott SANNER , Baher ABDULHAI
摘要： There is provided a system and method for traffic signal control of a traffic network with a learned model. The method including: receiving sensor readings from the traffic network, the sensor readings including positions and speeds of vehicles approaching each intersection; using a learned dynamics model that takes the sensor readings as input, predicting a plurality of possibilities for position and velocity of the vehicles approaching each intersection in a future timestep; determining a action for the one or more intersections by performing a tree search on the plurality of possibilities and selecting the possibility with a highest action value; and outputting the action to the traffic network for implementation as a traffic control action at the one or more intersections.
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公开(公告)号：US11526586B2
公开(公告)日：2022-12-13
申请号：US16593874
申请日：2019-10-04
申请人： BroadbandTV, Corp.
发明人： Ruishen Lyu , Jiaqi Sheng , Mehrdad Fatourechi
摘要： The herein disclosed technology provides methods and systems that utilize machine learning solutions to identify web-based channels that are sources pirated copyright material, such as by using a machine learning classifier that is trained on historical copyright piracy data and channel features that may be determined and analyzed for each of a collection of channels without analyzing video or audio content of the channel.
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公开(公告)号：US11526383B2
公开(公告)日：2022-12-13
申请号：US15931168
申请日：2020-05-13
IPC分类号： G06F9/50 , G06N20/00 , G06N5/00 , G06N7/00 , G06Q10/06 , G06Q10/10 , G06Q50/22 , G16H40/20 , G16H50/20
摘要： There is a need for more effective and efficient constrained-optimization-based operational load balancing. In one example, a method comprises determining constraint-satisfying operator-unit mapping arrangements that satisfy an operator unity constraint and an operator capacity constraint; for each constraint-satisfying operator-unit mapping arrangement, determining an arrangement utility measure; processing each arrangement utility measure using an optimization-based ensemble machine learning model that is configured to determine an optimal operator-unit mapping arrangement of the plurality of constraint-satisfying operator-unit mapping arrangements; and performing one or more operational load balancing operations based on the optimal operator-unit mapping arrangement.
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公开(公告)号：US20220391784A1
公开(公告)日：2022-12-08
申请号：US17303718
申请日：2021-06-06
摘要： A multi-objective scheduling advisor for generating a multi-stop visitation schedule includes generating, by a computer, a road network map corresponding to a predetermined area including a plurality of tasks locations. A task to be performed is assigned to each of the plurality of task locations. The computer calculates a business value for each task location using at least one of a calculation, a selected business rule applied to a delay duration, and an input value received from a client. A duration of a respective task is calculated using historical data on task durations associated with a staff of operators over different predetermined areas to determine an average task duration for every operator in the staff. Finally, using a metaheuristic binary optimization algorithm, the computer chooses different candidate tasks for the multi-stop visitation schedule to visit multiple assets in a single trip within the predetermined area.
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公开(公告)号：US11521069B2
公开(公告)日：2022-12-06
申请号：US15450933
申请日：2017-03-06
摘要： Embodiments employ an inference method for neural networks that enforces deterministic constraints on outputs without performing post-processing or expensive discrete search over the feasible space. Instead, for each input, the continuous weights are nudged until the network's unconstrained inference procedure generates an output that satisfies the constraints. This is achieved by expressing the hard constraints as an optimization problem over the continuous weights and employing backpropagation to change the weights of the network. Embodiments optimize over the energy of the violating outputs; since the weights directly determine the output through the energy, embodiments are able to manipulate the unconstrained inference procedure to produce outputs that conform to global constraints.
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公开(公告)号：US20220385675A1
公开(公告)日：2022-12-01
申请号：US17332803
申请日：2021-05-27
摘要： Detection and identification of malware adversaries and campaigns comprises code which executes in a computer system. An artifact having a bytestream from a source is received and analyzed to extract indicators of comprise (IOCs). The extracted IOCs are correlated with data sets of an intelligence database that stores data regarding malware adversaries and campaigns. A normalized data set pertaining to the artifact, the extracted IOCs, and data received from the intelligence database is generated based on the correlating step. A trained machine learning algorithm executes to evaluate a measurement of a probability as to whether the analyzed artifact is attributable to a particular threat actor and a particular campaign. A system is also disclosed in which a processor defines modules to implement the application described herein.
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