Methods, system, and apparatus for inference using probability information
OwnerHuazi Zhang, Yiqun Ge +2inventors
InventorsHuazi Zhang, Yiqun Ge, Jianglei Ma, Wen Tong
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Abstract
Input data for inference processes are often highly correlated and interdependent. These correlations provide an inherent redundancy in the input data which can be used to refine inference results and thus improve inference performance. In some embodiments, probability information is used to refine results from an inference process. The probability information indicates, for each of a plurality of potential results obtainable from the inference process, a probability of obtaining the respective potential result and another potential result from the plurality of potential results.
Claims20
A method comprising:
- receiving, from a network device, an input for a component inference process that forms part of a distributed inference process representative of a machine learning process;
- performing the component inference process on the input to obtain a first inference result;
- and
- transmitting, to the network device, a second inference result based on the first inference result and probability information, wherein the probability information indicates, for each potential result of a plurality of potential results obtainable from the component inference process, a respective probability of obtaining a respective potential result and another potential result from the plurality of potential results.
A method performed by a network device, the method comprising:
- transmitting, to each of a plurality of processing apparatuses, a respective first input in a plurality of first inputs, the respective first input being for a respective component inference process as part of a distributed inference process representative of a machine learning process;
- and
- receiving, from the plurality of processing apparatuses, first inference results obtained based on probability information and the plurality of first inputs, wherein the probability information indicates, for each potential result of a plurality of potential results obtainable from the respective component inference process, a respective probability of obtaining a respective potential result and another potential result from the plurality of potential results.
An apparatus comprising:
- at least one processor;
- and
- a memory storing instructions which, when executed by the at least one processor, cause the apparatus to:
- receive, from a network device, an input for a component inference process that forms part of a distributed inference process representative of a machine learning process;
- perform the component inference process on the input to obtain a first inference result;
- and
- transmit, to the network device, a second inference result based on the first inference result and probability information, wherein the probability information indicates, for each potential result of a plurality of potential results obtainable from the component inference process, a respective probability of obtaining a respective potential result and another potential result from the plurality of potential results.
A network device comprising:
- at least one processor;
- and
- a memory storing instructions which, when executed by the at least one processor, cause the network device to:
- transmit, to each of a plurality of processing apparatuses, a respective first input in a plurality of first inputs, the respective first input being for a respective component inference process as part of a distributed inference process representative of a machine learning process;
- and
- receive, from the plurality of processing apparatuses, first inference results obtained based on probability information and the plurality of first inputs, wherein the probability information indicates, for each potential result of a plurality of potential results obtainable from the respective component inference process, a respective probability of obtaining a respective potential result and another potential result from the plurality of potential results.
Dependencies are inferred from the claim text.