International Business Machines Corporation

Maplebear Inc.

Christian Makaya

Dinesh C Verma

Douglas Morgan Freimuth

Erich Miles Nahum

Seraphin Bernard Calo

Keith William Grueneberg

Jorge J Ortiz

Xiping Wang

Swati Rallapalli

Jonathan Lenchner

Theodoros Salonidis

Sharad C Sundararajan

Thai Franck Le

Satya Venkata Nitta

Bongjun Ko

Jason L Crawford

Thai V Le

Supriyo Chakraborty

Rahul Urgaonkar

Young Min Lee

Jayant R Kalagnanam

Bong Jun Ko

Maroun Touma

Nam H Nguyen

Kyong Min Yeo

Edward John Pring

Hui Qi

Dilip Dinkar Kandlur

Dhaval Patel

Shiqiang Wang

Dhavalkumar C Patel

Tiffany Tuor

Eric Nahum

Franck T Le

A method for targeted advertisement includes transmitting a pre-filter to the user device, responsive to contextual information from a user device, to determine, using a processor, one or more inferences based on physical browsing information, collected at the user device, in compliance with one or more privacy policies of the user. The method also includes receiving one or more inferences determined by the pre-filter from the user device and transmitting one or more targeted advertisements to the user device based on one or more inferences.

Recommendations based on private data using a dynamically deployed pre-filter

A meeting summarization method, system, and computer program product, include compiling notes from a meeting between a plurality of users and providing a single document that summarizes the meeting based on the compiled notes.

Summarization method for recorded audio

A provenance method, system, and non-transitory computer readable medium for a plurality of eidetic systems having logs, include crawling the logs of each node of a plurality of nodes of the eidetic systems to cluster segments across the logs of temporally correlated events into clustered segments and analyzing the correlated segments to interleave an order of processes in the logs and assign a probability to the order of the processes occurring.

System, method, and recording medium for distributed probabilistic eidetic querying, rollback, and replay

A network function optimization method, system, and computer program product include optimizing network function chain components of a software by modifying a structure of the network function chain components by removing a function of the network function chain components.

System, method and computer program product for network function optimization based on locality and function type

A training process of a machine learning model is executed at the edge node for a number of iterations to generate a model parameter based at least in part on a local dataset and a global model parameter. A resource parameter set indicative of resources available at the edge node is estimated. The model parameter and the resource parameter set are sent to a synchronization node. Updates to the global model parameter and the number of iterations are received from the synchronization node based at least in part on the model parameter and the resource parameter set of edge nodes. The training process of the machine learning model is repeated at the edge node to determine an update to the model parameter based at least in part on the local dataset and updates to the global model parameter and the number of iterations from the synchronization node.

Distributed machine learning at edge nodes

A meeting summarization method, system, and computer program product, include capturing notes of a user including a time stamp from the user associated with a meeting, synchronizing an agenda of the meeting and the notes of the user based on a correlation between a time stamp of a topic on the agenda and a time stamp of the notes of the user, and analyzing the synchronized topic and the notes to determine highlights of the meeting based on a co-occurrence of the time stamp of the notes of the user and the time stamp of the topic on the agenda.

A provenance method, system, and non-transitory computer readable medium for a plurality of eidetic systems having logs, include a log-segment clustering circuit configured to crawl the logs of each of the eidetic systems to cluster segments across the logs of temporally correlated events into clustered segments, a probabilistic interleaving circuit configured to analyze the correlated segments to interleave an order of processes in the logs and assign a probability to the order of the processes occurring, and a probabilistic linearization circuit configured to create a probability tree which includes a total probability that a process in the clustered segments causes a next process in the clustered segments until an end of the temporal event of the clustered segments for each of the interleaved order of processes interleaved by the probabilistic interleaving circuit.

A network function optimization method, system, and computer program product, include optimizing network function chain components by modifying a structure of the network function chain components by removing one of the functions of the network function chain components in response to a constraint according to a policy requirement.

Based on at least one manufacturing process characteristics associated with a manufacturing process, a prediction time at which to execute a selected machine learning model selected from multiple trained machine learning models is determined, and at the prediction time, the selected machine learning model is executed. Executing the selected machine learning model predicts a control set point for future values of state variables of the manufacturing process, for controlling the manufacturing process. Based on at least one of the manufacturing process characteristics, a learning time at which to train a machine learning model is determined, and at the learning time, the machine learning model is trained based on historical process data associated with the manufacturing process.

Orchestration of learning and execution of model predictive control tool for manufacturing processes

A computer program product is provided for fault diagnostics and recovery of network service chains. The product includes a computer readable storage medium having program instructions embodied therewith. The program instructions are executable by a computer to cause the computer to perform a method. The method includes identifying intersecting ones of components of the network service chains in a network graph indicative of a commonality therebetween. The method further includes selectively repairing one or more of the components of at least one of the network service chains up to an entirety thereof based on a component repair sequence that maintains service continuity of the network service chains and that is determined and selectively reordered based on the commonality. The network graph includes a plurality of graphs, each (i) including one or more Virtualized Network Functions, and (ii) corresponding to a respective one of the network service chains.

Mechanism for fault diagnosis and recovery of network service chains

A computer-implemented method is provided for fault diagnostics and recovery of network service chains. The method includes identifying, by a processor, intersecting ones of components of the network service chains in a network graph indicative of a commonality therebetween. The network graph represents the components of the network service chains. The method further includes selectively repairing, by the processor, one or more of the components of at least one of the network service chains up to an entirety thereof based on a component repair sequence that maintains service continuity of the network service chains and that is determined and selectively reordered based on the commonality. The network graph includes a plurality of graphs, each (i) including one or more Virtualized Network Functions, and (ii) corresponding to a respective one of the network service chains.

A network function modification method, system, and computer program product, include terminating the connection-oriented session between a client and a server via at least two proxies, running a multipath connection-oriented session between the at least two proxies, if an insertion request is received, establishing a first multipath subflow with the new multipath subflow traversing the network function of the insertion request, and if a removal request is received, establishing a second multipath subflow with the new multipath subflow not traversing the network function of the removal request.

Growing community of inventors

Summit, NJ, United States of America

Christian Makaya