Task agnostic embedding based labeling escalation on fly
AssigneeMicrosoft Technology Licensing, LLC
InventorsMohammadReza GHAEINI, Muhaimenul ADNAN
Life of this patent
Estimating the term…
Loading patent…
AssigneeMicrosoft Technology Licensing, LLC
InventorsMohammadReza GHAEINI, Muhaimenul ADNAN
Estimating the term…
Aspects of the disclosure include machine learning architectures with task agnostic embedding-based labeling escalation on fly. A method includes receiving a request corresponding to a task and generating, by a first pass system, a first decision. The first pass system includes a first pass model having a first complexity. The method includes generating, for the task, a task embedding in an embedding space, determining, in the embedding space, a top K subspace having K embeddings having K closest distances to the task embedding, and determining embedding labels for the K embeddings. The method includes determining to escalate the task to a second pass system having a second pass model having a second, higher complexity and, responsive to determining the embedding labels, generating, by the second pass system, a second decision for the task and returning, responsive to receiving the request, a response including the second decision.
A method for task agnostic embedding-based labeling escalation on fly, the method comprising:
A system comprising a memory, computer readable instructions, and one or more circuitry for executing the computer readable instructions, the computer readable instructions controlling the one or more circuitry to perform operations comprising:
A computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by one or more processors to cause the one or more processors to perform operations comprising:
Dependencies are inferred from the claim text.