International Business Machines Corporation

Nirmit V Desai

Dinesh C Verma

Theodoros Salonidis

Shahrokh Daijavad

Bong Jun Ko

Dawei Li

Mudhakar Srivatsa

Catherine Helen Crawford

Rahul Urgaonkar

Raghu Kiran Ganti

Ramya Raghavendra

Heather D Achilles

Swati Rallapalli

Jorge J Ortiz

Wendy Chong

John Maxwell Cohn

Supriyo Chakraborty

Yixin Diao

Tova Roth

Gargi Banerjee Dasgupta

Martin G Kienzle

Aliza Rivka Heching

Shiqiang Wang

Scott Douglas Lekuch

Steven Edward Millman

Dhiraj Joshi

Carmelo I Uria

Jenny S Li

Douglas Morgan Freimuth

Seraphin Bernard Calo

Nancy Anne Greco

Pietro Mazzoleni

Kamal Bhattacharya

Bijan Davari

Ting He

Mitchell Adam Cohen

Lior Limonad

Jae-Wook Ahn

Michele Merler

Marc Ph Stoecklin

Luis Angel Bathen

Pranita Sharad Dewan

Stefan Tai

Jakka Sairamesh

Steven A Waite

Liang Ma

Wei-Han Lee

Gwilym Benjamin Lee Newton

Madhusudhan R Ramidi

Sebastien Gilbert

Sujoy Kumar Roy Chowdhury

Chaitanya Kumar

Laura Wynter

Prakriti Pritmani

Virendra K Varshneya

Joe Latone

Aakash Praliya

Dean Haber

Ashafaaq Minhas

Satish Rajani

Shiva G

Kay Murphy

Jonathan Muehlstein

Arun Yashwant Ingale

Kelvin Kakugwa

Apurv Gupta

Shilpa Shenai

Shyama Prosad Chowdhury

Peter F Mycue

Chidansh Amitkumar Bhatt

Roger Hollander

Raghu Ramaswamy

Anshu Kak

Ajjay Ratnakar

Richa Gupta

Adam E Grant

Pawan Kumar

Randy M Fussell

Shruti P Kumar

Christopher P Huff

Aasish Behera

Kelvin Kakugawa

A computer-implemented method, a computer system and a computer program product route meeting sessions through a venue based on device availability. The method includes identifying a plurality of sessions in a venue network, where each session in the plurality of sessions comprises session data that is associated with a network slice. The network slice includes connection requirements. The method also includes receiving a connection request from a user, where the connection request includes a session in the plurality of sessions. The method further includes determining an available device to receive the session data, where the available device satisfies the connection requirements of the network slice. Lastly, the method includes associating the available device with the network slice, where the session data is transmitted to the available device.

Flexible orchestration of session content in venue networks

Methods and systems for emulating an application include generating a log template to match one or more patterns in a set of application logs collected from an original application. Semantic state representations are learned for the original application from the log template. A classifier is trained to predict a next action template based on a sequence of prior action templates. A regressor is trained to generate a parameter value for a template based on a sequence of prior action templates and a particular semantic state of the original application.

Machine learning to emulate software applications

Described are techniques for oblique image rectification. The techniques include receiving an original image depicting an oblique view of a circular object and pre-processing the original image into an edge image. The techniques further include generating, by a machine learning model based on the edge image, a heatmap including an ellipse formed by the oblique view of the circular object. The techniques further include computing ellipse parameters describing the ellipse of the heatmap. The techniques further include performing, using the ellipse parameters, an affine transformation on the original image to generate a rectified image, where the rectified image converts the ellipse to a circle.

Oblique image rectification

Dynamically adjusting, using artificial intelligence (AI), sensors and models of an autonomous roaming robotic device, which includes receiving data regarding an asset at a computer of a roaming robotic device from sensors on the robotic device. The robotic device identifies an asset at a location using the sensors, and the robotic device has instructions, received from a control system, to inspect the location or items at the location. The data is analyzed using the computer of the robotic device, and the analysis includes using historical data for the asset. An AI model is loaded using the computer of the robotic device, based on the identification of the asset. A sensor is selected using the computer of the robotic device, for conducting an inspection of the asset based on the analysis of the data and the AI model.

Dynamic use of artificial intelligence (AI) models on an autonomous AI enabled robotic device

A data mining method, system, and non-transitory computer readable medium include obtaining a subset of public records of data in a public domain and performing data mining, via private domain data, within the subset of the public records of data to find data in the public domain corresponding to a particular individual.

System, method, and recording medium for data mining between private and public domains

Personalization with on-device privacy preservation is provided by receiving, at a user device, a generalized recommendation from a remote provider backend, which include a plurality of candidate items responsive to a request from an application running on the user device; generating a plurality of candidate vectors corresponding to the plurality of candidate items representing a corresponding candidate item in a binary format across a plurality of metrics associated with the plurality of candidate items; generating a user vector based on personal data stored on the user device, the user vector representing a user in a binary format across one or more metrics associated with the personal data; determining interaction propensities based on the user vector and the plurality of candidate vectors according to a global model run on the user device; and displaying, on the user device, the plurality of candidate items according to the interaction propensities.

On-device privacy-preservation and personalization

Embodiments are disclosed for a method for a wearable secure data device. The method includes setting an operational mode for the wearable secure data device that stores a plurality of secure data items. The method also includes receiving a request for at least one of the secure data items from a client device that is communicating with a third-party device. Additionally, the method includes determining if the operational mode is associated with allowing access to the secure data items. Further, the method includes providing a response based on the determination.

Wearable secure data device

A method of determining a range between two devices, which can for instance be wireless devices, such as handheld devices. The method performs a double-sided two-way ranging protocol at the two devices. This protocol causes the two devices to transmit and receive signals, with a view to determining the range between the two devices, using a two-way ranging methods, where each of the signals is a composite tone generated as a composition of two waveforms that are timewise separated by a gap to form a bipolar waveform. The gap is a zero or low-amplitude signal, contrasting with the two waveforms. The particular pattern in the correlation footprint eases the determination of the time of flight. The method can be used to measure social distancing.

Double-sided two-way ranging protocol based on composite, ultrasonic tones

A data mining method, system, and non-transitory computer readable medium, include defining a set of filter constraints as a filter function for clustering users' private records of data of a private domain, selecting a subset of users' public records of data from a filtered set of data from a public domain that is common with the users' private records of data, and creating a data file including the matched user of the private domain to the public records of the user of the private domain, where the set of the filter constraints comprises a function that captures the subset of the users' public records of data who are of interest to the private domain, and only performs data mining with that set of information from the public domain.

Examples of techniques for interactive generation of labeled data and training instances are provided. According to one or more embodiments of the present invention, a computer-implemented method for interactive generation of labeled data and training instances includes presenting, by the processing device, control labeling options to a user. The method further includes selecting, by a user, one or more of the presented control labeling options. The method further includes selecting, by a processing device, a representative set of unlabeled data samples based at least in part on the control labeling options selected by the user. The method further includes generating, by a processing device, a set of suggested labels for each of the unlabeled data samples.

Edge-based adaptive machine learning for object recognition

Aspects of the invention include methods of performing beam management in a base station of a cellular network. A method includes obtaining, at the base station, information indicating whether one or more terminals of the cellular network have data to transmit, and determining, using the base station, during a sweep by the base station if an upcoming terminal has data to transmit based on the information. The sweep by the base station is a sequential movement of the beam over a coverage area. The method also includes foregoing, by the base station, any communication with the upcoming terminal during the sweep based on the information indicating that the upcoming terminal has no data to transmit, and communicating, using the base station, with the upcoming terminal during the sweep based on the information indicating that the upcoming terminal has data to transmit.

Base station beam management based on terminal transmit data indication

Examples of techniques for adaptive model training are provided. According to one or more embodiments of the present invention, a computer-implemented method for adaptive model training includes generating, by a processing system, a training instance based at least in part on a plurality of images that match a contextual specification of a target visual domain. The method further includes extracting, by the processing system, objects from one of the plurality of images. The method further includes for each extracted object, generating, by the processing system, a plurality of machine learning model features and label recommendations for a user.

A computer-implemented method for delivering network connectivity includes receiving, by an edge server, a set of communication packets from a communication device. The method further includes storing, by the edge server, the set of communication packets as part of outbound data. The method further includes determining, by the edge server, that a mobile access point is within a communicable range of the edge server. The mobile access point travels back and forth between the edge server and a base station. The method further includes transmitting, by the edge server, the outbound data to the mobile access point that is within the communicable range.

Cost effective delivery of network connectivity to remote areas

A notification message is received by a communication device The notification message includes a message identifier and a digital signature generated by an original sender of the notification message. That an integrity of message content in the notification message and an original sender of the notification message is verified is determined using the digital signature. Responsive to determining that the notification message is verified, the notification message is forwarded by the communication device using a peer-to-peer communication channel over a mesh network.

Delivering messages to offline devices using peer-to-peer communication

Growing community of inventors

Yorktown Heights, NY, United States of America

Nirmit V Desai