A method of operating a neural network includes determining a complexity, such as a number) of separable filters approximating a filter. The method further includes selectively applying a decomposed convolution to the filter based on the determined number of separable filters.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method of operating a neural network, comprising: determining a complexity of separable filters approximating a filter in the neural network; and selectively applying a decomposed convolution to the filter based at least in part on the determining. 2. The method of claim 1, in which the determining is based at least in part on a rank of the filter. 3. The method of claim 1, further comprising: replacing the filter with a low rank approximation based at least in part on a performance metric. 4. The method of claim 1, in which the determining is based at least in part on a singular value decomposition (SVD) of the filter. 5. The method of claim 4, further comprising: replacing the filter with a low rank approximation based at least in part on singular values obtained via the singular value decomposition. 6. The method of claim 1, in which the determined complexity comprises a number of separable filters sufficient to approximate the filter. 7. An apparatus for operating a neural network, comprising: a memory; and at least one processor coupled to the memory, the at least one processor being configured: to determine a complexity of separable filters approximating a filter in the neural network; and to selectively apply a decomposed convolution to the filter based at least in part on the determined complexity of separable filters. 8. The apparatus of claim 7, in which the at least one processor is further configured to determine the complexity of separable filters based at least in part on a rank of the filter. 9. The apparatus of claim 7, in which the at least one processor is further configured to replace the filter with a low rank approximation based at least in part on a performance metric. 10. The apparatus of claim 7, the at least one processor is further configured to determine the complexity of separable filters based at least in part on a singular value decomposition (SVD) of the filter. 11. The apparatus of claim 10, in which the at least one processor is further configured to replace the filter with a low rank approximation based at least in part on singular values obtained via the singular value decomposition. 12. The apparatus of claim 7, in which the determined complexity comprises a number of separable filters sufficient to approximate the filter. 13. An apparatus for operating a neural network, comprising: means for determining a complexity of separable filters approximating a filter in the neural network; and means for selectively applying a decomposed convolution to the filter based at least in part on the determined complexity of separable filters. 14. The apparatus of claim 13, in which the determined complexity of separable filters is based at least in part on a rank of the filter. 15. The apparatus of claim 13, further comprising: means for replacing the filter with a low rank approximation based at least in part on a performance metric. 16. The apparatus of claim 13, in which the determined complexity of separable filters is based at least in part on a singular value decomposition (SVD) of the filter. 17. The apparatus of claim 16, further comprising: means for replacing the filter with a low rank approximation based at least in part on singular values obtained via the singular value decomposition. 18. A computer program product for operating a neural network, comprising: a non-transitory computer readable medium having encoded thereon program code, the program code comprising: program code to determine a complexity of separable filters approximating a filter in the neural network; and program code to selectively apply a decomposed convolution to the filter based at least in part on the determined complexity of separable filters. 19. The computer program product of claim 18, further comprising program code to determine the complexity of separable filters based at least in part on a rank of the filter. 20. The computer program product of claim 18, further comprising program code to replace the filter with a low rank approximation based at least in part on a performance metric. 21. The computer program product of claim 18, further comprising program code to determine the complexity of separable filters based at least in part on a singular value decomposition (SVD) of the filter. 22. The computer program product of claim 21, further comprising program code to replace the filter with a low rank approximation based at least in part on singular values obtained via the singular value decomposition.