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1.发明申请公开(公告)号：US20220065981A1
公开(公告)日：2022-03-03
申请号：US17461516
申请日：2021-08-30
摘要： Certain aspects of the present disclosure provide techniques for machine learning using basis decomposition, comprising receiving a first runtime record, where the first runtime record includes RF signal data collected in a physical space; processing the first runtime record using a plurality of basis machine learning (ML) models to generate a plurality of inferences; aggregating the plurality of inferences to generate a prediction comprising a plurality of coordinates; and outputting the prediction, where the plurality of coordinates indicate a location of a physical element in a physical space.
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公开(公告)号：US20210219282A1
公开(公告)日：2021-07-15
申请号：US17216386
申请日：2021-03-29
发明人： Krishna Kiran MUKKAVILLI , Jing JIANG , Tingfang JI , Jamie Menjay LIN , Joseph Binamira SORIAGA , John Edward SMEE
IPC分类号： H04W72/04 , H04W72/10 , H04B7/0452 , H04L5/00 , H04W72/12
摘要： An apparatus may utilize an air interface to transmit and/or receive a transmission during a first TTI that includes a second set of data overriding a first set of data scheduled for transmission during the first TTI. The air interface may further be utilized to transmit and/or receive a transmission during one or more additional TTIs that includes a third set of data in a data portion of a subframe, and an override indicator that is at least partially embedded in the data portion. The override indicator may be configured to indicate that the first set of data scheduled for transmission during the first TTI is overridden by the second set of data having the higher priority. The override indicator may be transmitted after the second set of data is transmitted. The one or more additional TTIs may be after the first TTI.
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公开(公告)号：US20230085880A1
公开(公告)日：2023-03-23
申请号：US17483434
申请日：2021-09-23
摘要： Certain aspects of the present disclosure provide techniques for domain adaptation. An input tensor comprising channel state information (CSI) for a wireless signal is determined, where each channel in the input tensor corresponds to a respective degree of freedom (DoF) in the wireless signal. A domain-adapted tensor is generated by processing the input tensor using a domain-adaptation network comprising, for each respective DoF in the wireless signal, a respective convolution path. The domain-adapted tensor is provided to a neural network trained for position estimation.
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公开(公告)号：US20220300788A1
公开(公告)日：2022-09-22
申请号：US17207406
申请日：2021-03-19
摘要： Certain aspects of the present disclosure provide a method for compressing an activation function, comprising: determining a plurality of difference values based on a difference between a target activation function and a reference activation function over a range of input values; determining a difference function based on the plurality of difference values; and performing an activation on input data using the reference activation function and a difference value based on the difference function.
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公开(公告)号：US20220261648A1
公开(公告)日：2022-08-18
申请号：US17175487
申请日：2021-02-12
发明人： Yash Sanjay BHALGAT , Jin Won LEE , Jamie Menjay LIN , Fatih Murat PORIKLI , Chirag Sureshbhai PATEL
摘要： Certain aspects of the present disclosure provide techniques for improved machine learning using gradient pruning, comprising computing, using a first batch of training data, a first gradient tensor comprising a gradient for each parameter of a parameter tensor for a machine learning model; identifying a first subset of gradients in the first gradient tensor based on a first gradient criteria; and updating a first subset of parameters in the parameter tensor based on the first subset of gradients in the first gradient tensor.
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公开(公告)号：US20220156946A1
公开(公告)日：2022-05-19
申请号：US17510763
申请日：2021-10-26
摘要： Systems and techniques are described for performing supervised learning (e.g., semi-supervised learning, self-supervised learning, and/or mixed supervision learning) for optical flow estimation. For example, a method can include obtaining an image associated with a sequence of images and generating an occluded image. The occluded image can include at least one of the image with an occlusion applied to the image and a different image of the sequence of images with the occlusion applied. The method can include determining a matching map based at least on matching areas of the image and the occluded image and, based on the matching map, determining a loss term associated with an optical flow loss prediction associated with the image and the occluded image. The loss term may include a matched loss and/or other loss. Based on the loss term, the method can include training a network configured to determine an optical flow between images.
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公开(公告)号：US20210081765A1
公开(公告)日：2021-03-18
申请号：US16571760
申请日：2019-09-16
发明人： Jamie Menjay LIN , Yang YANG , Jilei HOU
摘要： Embodiments described herein relate to a method, comprising: receiving input data at a convolutional neural network (CNN) model; generating a factorized computation network comprising a plurality of connections between a first layer of the CNN model and a second layer of the CNN model, wherein: the factorized computation network comprises N inputs, the factorized computation network comprises M outputs, and the factorized computation network comprises at least one path from every input of the N inputs to every output of the M outputs; setting a connection weight for a plurality of connections in the factorized computation network to 1 so that a weight density for the factorized computation network is
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公开(公告)号：US20190268129A1
公开(公告)日：2019-08-29
申请号：US16298834
申请日：2019-03-11
摘要： The disclosure provides for an apparatus for wireless communications using carrier aggregation comprised of multiple carrier components. The apparatus can include a processor configured to generate one or more instances of a codeword from a data payload. In an aspect, the apparatus also includes a modulator configured to modulate the one or more instances of the codeword onto the multiple carrier components for transmission. In an aspect, the apparatus also includes a resource manager configured to provide the processor with a virtual carrier space comprising a logical carrier having a contiguous bandwidth equivalent to the aggregated bandwidth of the multiple carrier components. In an aspect, the process may be further configured to interleave at least one of the codeword instances across the multiple carrier components. In an aspect, the modulator may be configured to modulate the codeword instance onto the multiple carrier components in accordance to the interleaving.
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公开(公告)号：US20170085356A1
公开(公告)日：2017-03-23
申请号：US15081773
申请日：2016-03-25
CPC分类号： H04L5/023 , H04L1/0041 , H04L1/04
摘要： The disclosure provides for an apparatus for wireless communications using carrier aggregation comprised of multiple carrier components. The apparatus can include a processor configured to generate one or more instances of a codeword from a data payload. In an aspect, the apparatus also includes a modulator configured to modulate the one or more instances of the codeword onto the multiple carrier components for transmission. In an aspect, the apparatus also includes a resource manager configured to provide the processor with a virtual carrier space comprising a logical carrier having a contiguous bandwidth equivalent to the aggregated bandwidth of the multiple carrier components. In an aspect, the process may be further configured to interleave at least one of the codeword instances across the multiple carrier components. In an aspect, the modulator may be configured to modulate the codeword instance onto the multiple carrier components in accordance to the interleaving.
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公开(公告)号：US20240103119A1
公开(公告)日：2024-03-28
申请号：US17934598
申请日：2022-09-23
发明人： Jamie Menjay LIN , Tong TANG
CPC分类号： G01S5/0278 , G06N3/0472 , G06N3/08
摘要： Certain aspects of the present disclosure provide techniques for training and using machine learning models to predict locations of stationary and non-stationary objects in a spatial environment. An example method generally includes measuring, by a device, a plurality of signals within a spatial environment. Timing information is extracted from the measured plurality of signals. Based on a machine learning model, the measured plurality of signals within the spatial environment, and the extracted timing information, locations of stationary reflection points and locations of non-stationary reflection points in the spatial environment are predicted. One or more actions are taken by the device based on predicting the locations of stationary reflection points and non-stationary reflection points in the spatial environment.
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