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公开(公告)号：US12288237B2
公开(公告)日：2025-04-29
申请号：US17743360
申请日：2022-05-12
Applicant: Adobe Inc.
Inventor： Ryan A. Rossi , Aravind Reddy Talla , Zhao Song , Anup Rao , Tung Mai , Nedim Lipka , Gang Wu , Eunyee Koh
IPC: G06Q30/0601
Abstract: Embodiments provide systems, methods, and computer storage media for a Nonsymmetric Determinantal Point Process (NDPPs) for compatible set recommendations in a setting where data representing entities (e.g., items) arrives in a stream. A stream representing compatible sets of entities is received and used to update a latent representation of the entities and a compatibility distribution indicating likelihood of compatibility of subsets of the entities. The probability distribution is accessed in a single sequential pass to predict a compatible complete set of entities that completes an incomplete set of entities. The predicted complete compatible set is provided a recommendation for entities that complete the incomplete set of entities.
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公开(公告)号：US20240273378A1
公开(公告)日：2024-08-15
申请号：US18163624
申请日：2023-02-02
Applicant: ADOBE INC.
Inventor： Saayan Mitra , Arash Givchi , Xiang Chen , Somdeb Sarkhel , Ryan A. Rossi , Zhao Song
Abstract: Systems and methods for distributed machine learning are provided. According to one aspect, a method for distributed machine learning includes obtaining, by an edge device, a static machine learning model from a hub device, computing, by the edge device, an objective function for a dynamic machine learning model based on a relationship between the dynamic machine learning model and the static machine learning model, and updating, by the edge device, the dynamic machine learning model based on the objective function.
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公开(公告)号：US20240134918A1
公开(公告)日：2024-04-25
申请号：US18049069
申请日：2022-10-23
Applicant: ADOBE INC.
Inventor： Nathan Ng , Tung Mai , Thomas Greger , Kelly Quinn Nicholes , Antonio Cuevas , Saayan Mitra , Somdeb Sarkhel , Anup Bandigadi Rao , Ryan A. Rossi , Viswanathan Swaminathan , Shivakumar Vaithyanathan
IPC: G06F16/9535 , G06F16/906 , G06F16/9538 , H04L67/306
CPC classification number: G06F16/9535 , G06F16/906 , G06F16/9538 , H04L67/306
Abstract: Systems and methods for dynamic user profile projection are provided. One or more aspects of the systems and methods includes computing, by a prediction component, a predicted number of lookups for a future time period based on a lookup history of a user profile using a lookup prediction model; comparing, by the prediction component, the predicted number of lookups to a lookup threshold; and transmitting, by a projection component, the user profile to an edge server based on the comparison.
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4.发明公开公开(公告)号：US20230289696A1
公开(公告)日：2023-09-14
申请号：US17693778
申请日：2022-03-14
Applicant: ADOBE INC.
Inventor： Arpit Ajay Narechania , Fan Du , Atanu R. Sinha , Ryan A. Rossi , Jane Elizabeth Hoffswell , Shunan Guo , Eunyee Koh , John Anderson , Sonali Surange , Saurabh Mahapatra , Vasanthi Holtcamp
IPC: G06Q10/06
CPC classification number: G06Q10/06393 , G06F3/0482
Abstract: Embodiments provide systems, methods, and computer storage media for management, assessment, navigation, and/or discovery of data based on data quality, consumption, and/or utility metrics. Data may be assessed using attribute-level and/or record-level metrics that quantify data: “quality”—the condition of data (e.g., presence of incorrect or incomplete values), its “consumption”—the tracked usage of data in downstream applications (e.g., utilization of attributes in dashboard widgets or customer segmentation rules), and/or its “utility”—a quantifiable impact resulting from the consumption of data (e.g., revenue or number of visits resulting from marketing campaigns that use particular datasets, storage costs of data). This data assessment may be performed at different stages of a data intake, preparation, and/or modeling lifecycle. For example, an interactive tree view may visually represent a nested attribute schema and attribute quality or consumption metrics to facilitate discovery of bad data before ingesting into a data lake.
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公开(公告)号：US20230206171A1
公开(公告)日：2023-06-29
申请号：US18117586
申请日：2023-03-06
Applicant: Adobe Inc.
Inventor： Kirankumar Shiragur , Tung Thanh Mai , Anup Bandigadi Rao , Ryan A. Rossi , Georgios Theocharous , Michele Saad
IPC: G06Q10/0835 , G06F17/11 , G06Q10/087 , G06Q10/047
CPC classification number: G06Q10/08355 , G06F17/11 , G06Q10/087 , G06Q10/047
Abstract: In implementations of item transfer control systems, a computing device implements a transfer system to receive input data describing types of requested items and corresponding quantities of the types of requested items to receive at each of a plurality of destination sites and types of available items and corresponding quantities of the types of available items that are available at each of a plurality of source sites. The transfer system constructs a flow network having a source node for each of the plurality of the source sites and a destination node for each of the plurality of the destination sites. An integral approximate solution is generated that transfers the corresponding quantities of the types of requested items to each of the plurality of the destination sites using a maximum flow solver and the flow network. The transfer system causes transferences of the corresponding quantities of the types of requested items to each of the plurality of the destination sites based on the integral approximate solution.
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Patent Agency Ranking
公开(公告)号：US11636423B2
公开(公告)日：2023-04-25
申请号：US17394707
申请日：2021-08-05
Applicant: Adobe Inc.
Inventor： Kirankumar Shiragur , Tung Thanh Mai , Anup Bandigadi Rao , Ryan A. Rossi , Georgios Theocharous , Michele Saad
IPC: G06Q10/0835 , G06F17/11 , G06Q10/087 , G06Q10/047
Abstract: In implementations of item transfer control systems, a computing device implements a transfer system to receive input data describing types of requested items and corresponding quantities of the types of requested items to receive at each of a plurality of destination sites and types of available items and corresponding quantities of the types of available items that are available at each of a plurality of source sites. The transfer system constructs a flow network having a source node for each of the plurality of the source sites and a destination node for each of the plurality of the destination sites. An integral approximate solution is generated that transfers the corresponding quantities of the types of requested items to each of the plurality of the destination sites using a maximum flow solver and the flow network. The transfer system causes transferences of the corresponding quantities of the types of requested items to each of the plurality of the destination sites based on the integral approximate solution.
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公开(公告)号：US20220138557A1
公开(公告)日：2022-05-05
申请号：US17089157
申请日：2020-11-04
Applicant: Adobe Inc.
Inventor： Ryan A. Rossi , Hongjie Chen , Kanak Vivek Mahadik , Sungchul Kim
IPC: G06N3/08 , G06N3/04 , G06F16/2458
Abstract: In implementations of deep hybrid graph-based forecasting systems, a computing device implements a forecast system to receive time-series data describing historic computing metric values for a plurality of processing devices. The forecast system determines dependency relationships between processing devices of the plurality of processing devices based on time-series data of the processing devices. Time-series data of each processing device is represented as a node of a graph and the nodes are connected based on the dependency relationships. The forecast system generates an indication of a future computing metric value for a particular processing device by processing a first set of the time-series data using a relational global model and processing a second set of the time-series data using a relational local model. The first and second sets of the time-series data are determined based on a structure of the graph.
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公开(公告)号：US20210357255A1
公开(公告)日：2021-11-18
申请号：US16867104
申请日：2020-05-05
Applicant: ADOBE INC.
Inventor： Kanak Vivek Mahadik , Ryan A. Rossi , Sana Malik Lee , Georgios Theocharous , Handong Zhao , Gang Wu , Youngsuk Park
Abstract: A system and method for automatically adjusting computing resources provisioned for a computer service or application by applying historical resource usage data to a predictive model to generate predictive resource usage. The predictive resource usage is then simulated for various service configurations, determining scaling requirements and resource wastage for each configuration. A cost value is generated based on the scaling requirement and resource wastage, with the cost value for each service configuration used to automatically select a configuration to apply to the service. Alternatively, the method for automatically adjusting computer resources provisioned for a service may include receiving resource usage data of the service, applying it to a linear quadratic regulator (LQR) to find an optimal stationary policy (treating the resource usage data as states and resource-provisioning variables as actions), and providing instructions for configuring the service based on the optimal stationary policy.
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公开(公告)号：US11163803B2
公开(公告)日：2021-11-02
申请号：US16397839
申请日：2019-04-29
Applicant: Adobe Inc.
Inventor： Ryan A. Rossi , Eunyee Koh , Anup Bandigadi Rao , Aldo Gael Carranza
Abstract: In implementations of higher-order graph clustering and embedding, a computing device receives a heterogeneous graph representing a network. The heterogeneous graph includes nodes that each represent a network entity and edges that each represent an association between two of the nodes in the heterogeneous graph. To preserve node-type and edge-type information, a typed graphlet is implemented to capture a connectivity pattern and the types of the nodes and edges. The computing device determines a frequency of the typed graphlet in the graph and derives a weighted typed graphlet matrix to sort graph nodes. Sorted nodes are subsequently analyzed to identify node clusters having a minimum typed graphlet conductance score. The computing device is further implemented to determine a higher-order network embedding for each of the nodes in the graph using the typed graphlet matrix, which can then be concatenated into a matrix representation of the network.
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公开(公告)号：US20210142425A1
公开(公告)日：2021-05-13
申请号：US16677007
申请日：2019-11-07
Applicant: Adobe Inc.
Inventor： Ryan A. Rossi
Abstract: In implementations of multi-item influence maximization, a computing device can obtain updates to a user association graph that indicates social correspondence between users, and obtain updates to a user-item graph that indicates user correspondence with one or more items. The computing device includes an influence maximization module that can update an item association graph that indicates item correspondence of each item with one or more other items, where the item association graph can be updated based on the user-item graph that indicates the user correspondence with one or more of the items. The influence maximization module can then iteratively determine a resource allocation for each of the users to maximize user influence of multiple items that are associated in the item association graph and based on the social correspondence between the users, as well as assign a variable portion of the resource allocation to any number of the users.
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