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公开(公告)号:US20240160939A1
公开(公告)日:2024-05-16
申请号:US17987518
申请日:2022-11-15
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor: SATISH KUMAR MOPUR , KRISHNAPRASAD LINGADAHALLI SHASTRY , SATHYANARAYANAN MANAMOHAN , RAVI SARVESWARA , GUNALAN PERUMAL VIJAYAN
IPC: G06N3/08
CPC classification number: G06N3/088
Abstract: Anomalies and drift detection in decentralized learning environments. The method includes deploying at a first node, (1) a local unsupervised autoencoder, trained at the first node, along with a local training data reference baseline for the first node, and (2) a global unsupervised autoencoder trained across a plurality of nodes, along with a corresponding global training data reference baseline. Production data at the first node is processed with local and global ML models deployed by a user. At least one of local and global anomaly data regarding anomalous production data or local and global drift data regarding drifting production data is derived based on the local and global training data reference baselines, respectively. At least one of the local anomaly data is compared with the global anomaly data or the local drift data with the global drift data for assessing impact of anomalies/drift on the ML models.
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公开(公告)号:US20240028417A1
公开(公告)日:2024-01-25
申请号:US17868587
申请日:2022-07-19
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor: SATHYANARAYANAN MANAMOHAN , SATISH KUMAR MOPUR , KRISHNAPRASAD LINGADAHALLI SHASTRY , RAVI SARVESWARA
CPC classification number: G06F9/5077 , H04L9/50 , G06F9/45558 , G06N20/20
Abstract: Systems and methods provide for a federated workflow solution to orchestrate entire machine learning (ML) workflows comprising multiple tasks, across silos. In other words, one or more sets/pluralities of tasks making up an ML workflow, can be executed across multiple resource partitions or domains. Federated workflow state can be maintained and shared through some form of distributed database/ledger, such as a blockchain. Agents that are locally deployed locally at the silos may orchestrate an ML workflow at a particular resource domains, each such agent having access, via the blockchain (acting as a globally visible/consistent state store), to the aforementioned workflow state. Such systems are capable of operating regardless of the existence of heterogeneous resources/aspects of a silo.
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公开(公告)号:US20240256525A1
公开(公告)日:2024-08-01
申请号:US18160704
申请日:2023-01-27
Applicant: Hewlett Packard Enterprise Development LP
Inventor: SATHYANARAYANAN MANAMOHAN , KRISHNAPRASAD LINGADAHALLI SHASTRY , RAVI SARVESWARA , SAIKAT MUKHERJEE
CPC classification number: G06F16/2379 , G06F16/273 , G06F21/6218
Abstract: Systems and methods are disclosed for providing decentralized policy-based transactional object management for systems employing federated workflows. Various disclosed components may be added to one or more nodes of a decentralized network, wherein the disclosed components perform registration, replication, and read/write access interfacing functions. These functions result in the storage of objects on the decentralized network in a way which allows for decentralized, policy-based, and transactional management of the objects.
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公开(公告)号:US20190332702A1
公开(公告)日:2019-10-31
申请号:US16171288
申请日:2018-10-25
Applicant: Hewlett Packard Enterprise Development LP
Inventor: SATHYANARAYANAN MANAMOHAN , KRISHNAPRASAD LINGADAHALLI SHASTRY , AVINASH CHANDRA PANDEY , RAVI SARVESWARA
Abstract: The disclosure relates to decentralized management of nodes in a blockchain network. Participants may agree to a consensus rules and implement them as smart contracts. For example, one rule may specify that a node will accept a change proposal only when its local policies and/or data allow it to implement the change. A smart contract may implement this rule and deploy it across the blockchain network for each node to follow. Other participants, through their nodes, may propose changes to the blockchain network, and each node may consult its copy of the smart contract to determine whether to vote to approve the change request and apply the change request locally.
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