US Patent Application 17715863. Split a Tensor for Shuffling in Outsourcing Computation Tasks simplified abstract
Contents
Split a Tensor for Shuffling in Outsourcing Computation Tasks
Organization Name
Inventor(s)
Andre Xian Ming Chang of Bellevue WA (US)
Split a Tensor for Shuffling in Outsourcing Computation Tasks - A simplified explanation of the abstract
- This abstract for appeared for US patent application number 17715863 Titled 'Split a Tensor for Shuffling in Outsourcing Computation Tasks'
Simplified Explanation
The abstract discusses a method for protecting access to a tensor in deep learning computations when outsourcing the computations to external entities. The tensor is a data structure used in artificial neural networks, and it is arranged in rows and columns. The method involves dividing the tensor into smaller tasks and shuffling them with other tasks before outsourcing them. The results obtained from the external entities are then used to compute the final result of the tensor in the neural network. This partitioning and shuffling process helps prevent the external entities from accessing or reconstructing the original tensor.
Original Abstract Submitted
Protection of access to a tensor in outsourcing deep learning computations via shuffling. For example, the tensor in the computation of an artificial neural network can have elements arranged in a first dimension of rows and a second dimension of columns. The tensor can be partitioned along the first dimension and the second dimension to generate computing tasks that are shuffled and/or mixed with other tasks for outsourcing to external entities. Computing results returned from the external entities can be used to generate a computing result of the tensor in the computation of the artificial neural network. The partitioning and shuffling can prevent the external entities from accessing and/or reconstructing the tensor.
