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1. 发明申请

US20190251399A1 NETWORK CONSTRUCTION APPARATUS AND NETWORK CONSTRUCTION METHOD 审中-公开
公开(公告)号：US20190251399A1
公开(公告)日：2019-08-15
申请号：US16333390
申请日：2016-10-03
申请人： Mitsubishi Electric Corporation
发明人： Toshisada MARIYAMA , Kunihiko FUKUSHIMA , Wataru MATSUMOTO
IPC分类号： G06K9/62 , G06N3/08 , G06N3/04 , G06N7/00
CPC分类号： G06K9/6264 , G06N3/04 , G06N3/08 , G06N7/00
摘要： An element construction unit compares output values of one or more elements included in an intermediate layer calculated by an output value calculating unit with a threshold value, and the number of elements included in the intermediate layer is maintained when any of the output values out of the output values of the one or more elements included in the intermediate layer is greater than the threshold value, and the number of elements included in the intermediate layer is increased when all of the output values of the one or more elements included in the intermediate layer are equal to or less than the threshold value.

2. 发明申请

US20190243872A1 ANOMALY DETECTING DEVICE, ANOMALY DETECTING METHOD, AND RECORDING MEDIUM 审中-公开
公开(公告)号：US20190243872A1
公开(公告)日：2019-08-08
申请号：US16329794
申请日：2017-09-05
申请人： NEC Corporation
发明人： Tatsuya KOMATSU , Reishi KONDO
IPC分类号： G06F17/18 , G06N7/00
CPC分类号： G06F17/18 , G05B23/02 , G06N7/00
摘要： An anomaly detecting device according to the present invention includes: a memory; and at least one processor coupled to the memory. The processor performs operations. The operations includes: when first series data are input, extracting a series feature amount being a feature amount of a signal included in the first series data; calculating a series probability distribution being a probability distribution which the series feature amount follows; storing a reference probability distribution being a probability distribution designated as a reference for the series feature amount in the first series data; calculating a state feature amount representing a fluctuation condition of the series probability distribution with respect to the reference probability distribution; and detecting an anomaly of the first series data, based on a plurality of the state feature amounts calculated from the first series data.

3. 发明申请

US20190236472A1 MANUFACTURING ASSISTANCE APPARATUS 审中-公开
公开(公告)号：US20190236472A1
公开(公告)日：2019-08-01
申请号：US16209743
申请日：2018-12-04
申请人： SUBARU CORPORATION
发明人： Toshimasa KOBAYASHI , Marosuke KIKUCHI , Yoichi SATO , Yuki MATSUDA , Toshimichi OGISU , Daisuke HIRABAYASHI , Kei SUZUKI , Toru ONISHI , Haruka MIYANISHI
IPC分类号： G06N7/00 , G06N20/00 , B64F5/10 , G06F17/11
CPC分类号： G06N7/00 , B64F5/10 , G05B19/41805 , G05B2219/45071 , G06F17/11 , G06N20/00
摘要： A manufacturing assistance apparatus includes a learning unit and an estimator. The learning unit is configured to load a plurality of pieces of actual measurement data in each of which a gap and a plurality of parameters are associated with each other, and construct an estimation model on the basis of machine learning in which the plurality of pieces of actual measurement data serve as teacher data. The gap is provided between a first workpiece and a second workpiece that eventually structure an airframe of an aircraft and that are eventually fastened to each other. The estimation model estimates the gap from the plurality of parameters. The estimator is configured to derive an estimation value of a length of the gap on which measurement has not yet been performed, on the basis of the estimation model constructed by the learning unit and the plurality of parameters.

4. 发明申请

US20190214124A1 ESTIMATION OF INSULIN BASED ON REINFORCEMENT LEARNING 审中-公开
公开(公告)号：US20190214124A1
公开(公告)日：2019-07-11
申请号：US16318015
申请日：2017-07-14
申请人： UNIVERSITÄT BERN
发明人： Stavroula MOUGIAKAKOU , Eleni DASKALAKI , Peter DIEM
IPC分类号： G16H20/17 , A61B5/145 , A61B5/00 , G06N20/00 , G06N7/00
CPC分类号： G16H20/17 , A61B5/14532 , A61B5/7282 , G06N7/00 , G06N20/00 , G16H50/20 , G16H50/50
摘要： The optimal insulin to be delivered by an insulin infusion pump is determined by using a reinforcement learning algorithm aiming to the personalized glucose regulation. The algorithm optimizes the daily basal insulin rate and insulin: carbohydrate ratio for each patient, on the basis of his/her measured glucose profile. The proposed algorithm is able to learn in real-time patient-specific characteristics captured in the daily glucose profile and provide individualised insulin treatment. An automatic and personalised tuning method contributes in the optimisation of the algorithm's performance.

5. 发明申请

US20190205779A1 Universal Functions Originator 审中-公开
公开(公告)号：US20190205779A1
公开(公告)日：2019-07-04
申请号：US16278070
申请日：2019-02-16
申请人： Ali Ridha Ali
发明人： Ali Ridha Ali
IPC分类号： G06N7/00 , G06F17/18 , G06F17/11
CPC分类号： G06N7/00 , G06F17/11 , G06F17/18
摘要： Nowadays, many computing systems are used to perform many applications, such as: pattern classification, function approximation, categorization/clustering, control, forecasting/prediction, and optimization. Such these tools are linear regression (LR), nonlinear regression (NLR), artificial neural networks (ANNs), and support vector machines (SVMs). LR is used for simple data where the relation between its predictor and response vectors is linear, while NLR is used when that relation is not linear. ANNs and SVMs are more efficient and they can be used for complicated applications. However, each one of these approaches has its own strengths and weaknesses. This invention proposes a new computing system called universal functions originator (UFO). This system can generate highly complicated mathematical models, as well as simplifying them, automatically through two optimization stages. The four arithmetic operators (addition, subtraction, multiplication, and division) and all known mathematical functions (exponential, logarithmic, trigonometric, hyperbolic, etc.) can be included in the search space.

6. 发明申请

US20190188603A1 WEAKLY-SUPERVISED FRAUD DETECTION FOR TRANSPORTATION SYSTEMS VIA MACHINE LEARNING 审中-公开
公开(公告)号：US20190188603A1
公开(公告)日：2019-06-20
申请号：US15842686
申请日：2017-12-14
申请人： Uber Technologies, Inc.
发明人： Fahrettin Olcay Cirit
IPC分类号： G06N99/00 , G06N5/04 , G06N7/00
CPC分类号： G06N20/00 , G06N5/046 , G06N7/00 , G06Q50/30
摘要： Example methods and systems disclosed herein train an accurate machine-learned model that detects fraud within an electronic transportation system. A first model is trained on a first (comparatively small) set of trip data items representing trips taken, or requested, in the electronic transportation system. The first set of trip data items have been manually labeled by human analysts to determine whether the trips were or were not fraudulent. The first model is used to generate weak labels for a second (comparatively larger) set of trip data items that lack manual labels. The weak labels are used along with the second set of trip data items to train a second model that is more accurate than the first model for detecting fraud.

7. 发明申请

US20180357915A1 SYSTEM AND METHOD FOR CUSTOMIZING LEARNING INTERACTIONS BASED ON A USER MODEL 审中-公开
公开(公告)号：US20180357915A1
公开(公告)日：2018-12-13
申请号：US15977950
申请日：2018-05-11
申请人： CEREGO, LLC.
发明人： Iain M. HARLOW , Andrew SMITH LEWIS , Paul T. MUMMA
IPC分类号： G09B7/06 , G06F17/18 , G06N7/00
CPC分类号： G09B7/06 , G06F17/18 , G06N7/00
摘要： A method for predictively updating one or more user parameters associated with a user of a learning system includes predicting, based on the one or more user parameters, a predicted activity of the user, receiving an actual activity of the user, comparing the predicted activity to the actual activity, and updating the one or more user parameters in response to determining that the predicted activity does not match the actual activity. The method may further include scheduling one or more learning interactions based on the one or more updated learning parameters, where the scheduling includes selecting at least one of a timing of the one or more learning interactions or a type of the one or more learning interactions.

8. 发明申请

US20180314964A1 APPARATUS, METHOD, AND PROGRAM FOR SELECTING EXPLANATORY VARIABLES 审中-公开
公开(公告)号：US20180314964A1
公开(公告)日：2018-11-01
申请号：US15771599
申请日：2016-10-20
申请人： MIZUHO-DL FINANCIAL TECHNOLOGY CO., LTD.
发明人： Yasushi Takano , Ryuichi Sato , Tatsuro Ishijima , Kazuyoshi Yoshino
IPC分类号： G06N7/00 , G06F17/17 , G06K9/62
CPC分类号： G06N7/00 , G06F17/17 , G06F17/18 , G06K9/6231 , G06N5/045 , G06N7/005 , G06Q40/02
摘要： Provided is an apparatus which selects desired explanatory variables from a plurality of candidate explanatory variables in a statistical model that expresses, by a predetermined function, a relationship between a linear predictor and an expectation value of a response variable or a probability of the response variable having certain values, by using a variable selecting model that expresses the linear predictor as a sum of a constant and a linear combination of the candidate explanatory variables and their corresponding coefficients, the apparatus including a sign condition acquisition unit for acquiring sign conditions for at least one of the coefficients; an estimator for calculating an estimate of the respective coefficients and an estimate of the constant under the sign conditions, using plural data; and a selection unit for selecting, as the desired explanatory variable, the candidate explanatory variable corresponding to the coefficient of which the estimate is calculated to be non-zero.

9. 发明申请

US20180285685A1 DIMENSION GROUPING AND REDUCTION FOR MODEL GENERATION, TESTING, AND DOCUMENTATION 审中-公开
公开(公告)号：US20180285685A1
公开(公告)日：2018-10-04
申请号：US15806265
申请日：2017-11-07
申请人： Ayasdi, Inc.
发明人： Gurjeet Singh , Noah Horton , Bryce Eakin
IPC分类号： G06K9/62 , G06N7/00 , G06F17/15 , G06F17/30 , G06Q10/06
CPC分类号： G06K9/623 , G06F16/254 , G06F16/9024 , G06F16/9038 , G06F17/153 , G06N7/00 , G06Q10/06375
摘要： An example method includes receiving analysis data and output indicator, mapping data points from a transposition of the analysis data to a reference space, generating a cover of the reference space, clustering the data points mapped to the reference space using the cover and a metric function to determine each node of a plurality of nodes, for each node, identifying data points that are members to identify similar features, grouping features as being similar to each other based on node(s), for each feature, determining correlation with at least some data associated with the output indicator and generate a correlation score, displaying at least groupings of similar features and displaying the correlation scores, receiving a selection of features, generating a set of models based on selection, determining fit of each generated model to output data and generate a model score, and generating a model recommendation report.

10. 发明申请

US20180268005A1 DATA PROCESSING METHOD AND APPARATUS 审中-公开
公开(公告)号：US20180268005A1
公开(公告)日：2018-09-20
申请号：US15985938
申请日：2018-05-22
申请人： HUAWEI TECHNOLOGIES CO., LTD.
发明人： Qingyu CHEN , Weiguo TAN
IPC分类号： G06F17/30 , G06N7/00
CPC分类号： G06F16/212 , G06F16/00 , G06F16/35 , G06F2216/03 , G06N7/00
摘要： Embodiments of the present invention provide a data processing method. A data processing apparatus obtains a first dataset, and determines a change of a data feature of the first dataset relative to a data feature of a second dataset, where the second dataset is a dataset that is received before the data processing apparatus obtains the first dataset; determines a hyperparameter according to the data feature of the first dataset when the change of the data feature of the first dataset relative to the data feature of the second dataset is greater than or equal to a preset data feature threshold; determines a first data model according to the determined hyperparameter and the first dataset; and processes data according to the determined first data model, to improve efficiency of determining the first data model, thereby improving efficiency of processing data.

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