DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
The amendment filed 03/17/2026 has been entered. Claims 1-7, 9-16, and 18 are pending.
Response to Arguments
Applicant's arguments with respect to 35 U.S.C § 101 filed 03/17/2026 have been fully
considered but they are not persuasive.
Applicant argues that the claims limitations of forward and back propagation, and determining relative importance are not a mental process/mathematical calculations (pages 7-8 of applicant’s arguments). The examiner respectfully disagrees. According to MPEP 2106.04(a), a claim recites an abstract idea if a specific limitation(s) falls within the abstract idea grouping (mathematical concept, certain methods of organizing human activity, mental process). Paragraphs 22-29 of the applications published specification defines forward propagation as a series of calculations. Given the broadest reasonable interpretation, forward propagation is mathematical calculations/algorithm which can be performed by a human. Similar rationale applies to back propagation. Also, given a matrix of values a person could determine relative importance of the features represented in the matrix. Thus, determining relative importance is a mental process. Also, updating the accumulation matrix is a mathematical concept/mental process as computing the difference between matrices and adding the difference to another matrix is a series of calculations and could be performed by a human.
Applicant also argues that the claims are integrated into a practical application (page 8-9 of applicant’s arguments). Examiner respectfully disagrees. For the claims to be integrated into a practical application, the additional elements must show this. The additional elements are directed to inputting the data into the machine learning model, the structure of the model and storing the gradients. This amount to extra-solution activity and mere instructions to the judicial exception.
Finally applicant argues that the claim invention amounts to significantly more (page 10-11 of applicant’s arguments). Examiner respectfully disagrees. Applicant states that the present claims are similar to Example 48 in that the claims are showing an improvement in the functioning of a computer. According to MPEP 2106.05(a) the improvement cannot come from the judicial exception alone. The additional elements are about collecting/gathering data and using a generic machine learning model. It is unclear how these relate to improvements mentioned on pages 10 and 11 of applicant’s arguments. These do not amount to significantly more. Thus the 101 rejection is maintained.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-7, 9-16, and 18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
101 Subject Matter Eligibility analysis
Step 1: Claims 1-7, 9-16, and 18 are within the four statutory categories (a process, machine, manufacture or composition of matter.) Claims 1-7, 9 describe a process, and claims 10-16, 18 describe a machine.
With respect to claim 1:
Step 2A Prong 1: The claim recites an abstract idea enumerated in the 2019 PEG.
performing a forward propagation of the features,…, wherein the header matric preserves the dataset during the forward propagation such that an output of the header matrix corresponds to the dataset. (This is an abstract idea of a "Mental Process." The "performing" step under its broadest reasonable interpretation, covers concepts that can be practically performed by a human using a pen and paper. The specification describes forward propagation as a series of calculations and thus could be performed by a human.)
performing a back propagation of the features; (This is an abstract idea of a "Mental Process." The "performing" step under its broadest reasonable interpretation, covers concepts that can be practically performed by a human using a pen and paper. Similarly to forward propagation back propagation is a series of calculations and thus could be performed by a human.)
updating an accumulation matrix with the gradients from the header matrix for each of the training epochs, wherein updating the accumulation matrix comprises computing a difference between the header matrix after the back propagation and the identity matrix prior to the forward propagation and adding the difference to the accumulation matrix; (This is an abstract idea of a "Mental Process." The "computing" and “adding” steps under its broadest reasonable interpretation, covers concepts that can be practically performed by a human using a pen and paper.)
determining a relative importance for each of the features based on the values in the accumulation matrix (This is an abstract idea of a "Mental Process." The "determining" step under its broadest reasonable interpretation, covers concepts that can be practically performed in the human mind. The determining could be made manually by an individual.)
Step 2a Prong 2: The judicial exception is not integrated into a practical application
Additional elements:
inputting a dataset that includes data items into a machine learning model, wherein each of the data items includes features, wherein an input first layer of the machine learning model comprises a header matrix implemented as an identity matrix that is prepended to the model as the first layer of the machine learning model, and wherein the header matrix is rest to the identity matrix prior to each training epoch; (this limitation amounts to adding insignificant extra-solution activity to the judicial exception).
through the machine learning model; (This amounts to no more than mere instructions to “apply” the exception using a generic computer component.)
storing gradients generated by the back propagation in the header matrix; (this limitation amounts to adding insignificant extra-solution activity to the judicial exception).
Step 2B: the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
The additional elements of “inputting a dataset…”, “storing gradients…” adds insignificant extra-solution activity to the judicial exception and cannot provide an inventive concept.
As explained above the additional element “through the machine learning model” is recited in a generic level and they represent generic computer components to apply the abstract idea. Mere instructions to apply an exception cannot provide an inventive concept.
When considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which do not provide an inventive concept.
Therefore, claim 1 is ineligible
With respect to claim 2:
Step 2A Prong 1: claim 2, which incorporates the rejection of claim 1, recites an additional abstract idea:
the header matrix is an Identity matrix of order (n,n) where n corresponds to the number of features of the dataset; (this is an abstract idea of a “mathematical concept”. The recited “identity matrix” represents a mathematical matrix that would fall under the “mathematical concepts” grouping.)
Step 2a Prong 2: claim 2 does not recite any additional elements and thus cannot be integrated into a practical application.
Step 2B: claim 2 does not recite an additional element.
Therefore, claim 2 is ineligible.
With respect to claim 3:
Step 2A Prong 1: claim 3, which incorporates the rejection of claim 1, recites an additional abstract idea:
resetting includes subtracting the previous header matrix values from the identity matrix before each epoch; (This is an abstract idea of a "Mental Process." The "resetting" and “subtracting” step under its broadest reasonable interpretation, covers concepts that can be practically performed by a human using a pen and paper.)
Step 2a Prong 2: claim 3 does not recite any additional elements and thus cannot be integrated into a practical application.
Step 2B: claim 3 does not recite an additional element.
Therefore, claim 3 is ineligible.
With respect to claim 4:
Step 2A Prong 1: claim 4, which incorporates the rejection of claim 1, does not recite an abstract idea.
Step 2A Prong 2: The judicial exception is not integrated into a practical application.
The accumulation matrix has the same order as the header matrix (this limitation amounts to adding insignificant extra-solution activity to the judicial exception).
Step 2B: the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception
The additional element adds insignificant extra-solution activity to the judicial exception and cannot provide an inventive concept. Storing and retrieving information in memory is directed to a well understood routine conventional activity of data transmission (MPEP 2106.05(d)(II)(iv)).
Therefore, claim 4 is ineligible.
With respect to claim 5:
Step 2A Prong 1: claim 5, which incorporates the rejection of claim 4, does not recite an abstract idea.
Step 2a Prong 2: The judicial exception is not integrated into a practical application.
each row of the accumulation matrix corresponds to a feature of the dataset; (this limitation merely limits the judicial exception to a particular field of use.)
Step 2B: the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception
The additional element merely limits the judicial exception to a particular field of use and also cannot provide an inventive concept (MPEP 2106.05(h)).
Therefore, claim 5 is ineligible.
With respect to claim 6:
Step 2A Prong 1: claim 6, which incorporates the rejection of claim 5, recites an additional abstract idea:
summing or averaging the sum of each row of the dataset to generate an importance score for each of the rows, wherein the importance score corresponds to a relative importance of the corresponding feature; (this is an abstract idea of a “mathematical concept”. The recited “summing or averaging” represents a mathematical operation that would fall under the “mathematical concepts” grouping.)
Step 2a Prong 2: claim 6 does not recite any additional elements and thus cannot be integrated into a practical application.
Step 2B: claim 6 does not recite an additional element.
Therefore, claim 6 is ineligible.
With respect to claim 7:
Step 2A Prong 1: claim 7, which incorporates the rejection of claim 6, recites an additional abstract idea:
identifying a least important feature and a most important feature based on the importance scores; (This is an abstract idea of a "Mental Process." The "identifying" step under its broadest reasonable interpretation, covers concepts that can be practically performed in the human mind. The identifying could be made manually by an individual.)
Step 2a Prong 2: claim 7 does not recite any additional elements and thus cannot be integrated into a practical application.
Step 2B: claim 7 does not recite an additional element.
Therefore, claim 7 is ineligible.
With respect to claim 9:
Step 2A Prong 1: claim 9, which incorporates the rejection of claim 1, recites an additional abstract idea:
performing feature selection, machine learning introspection, dimensionality reduction, and/or drift detection based on the relative importance of each of the features (This is an abstract idea of a "Mental Process." These different operations under its broadest reasonable interpretation, covers concepts that can be practically performed in the human mind. The operations could be done manually by an individual.)
Step 2a Prong 2: claim 9 does not recite any additional elements and thus cannot be integrated into a practical application.
Step 2B: claim 9 does not recite an additional element.
Therefore, claim 9 is ineligible.
With respect to claim 10:
The claim recites similar limitations as corresponding to claim 1. Therefore, the same subject matter analysis that was utilized for claim 1, as described above, is equally applicable to claim 10. Therefore, claim 10 is ineligible.
With respect to claim 11:
The claim recites similar limitations as corresponding to claim 2. Therefore, the same subject matter analysis that was utilized for claim 2, as described above, is equally applicable to claim 11. Therefore, claim 11 is ineligible.
With respect to claim 12:
The claim recites similar limitations as corresponding to claim 3. Therefore, the same subject matter analysis that was utilized for claim 3, as described above, is equally applicable to claim 12. Therefore, claim 12 is ineligible.
With respect to claim 13:
The claim recites similar limitations as corresponding to claim 4. Therefore, the same subject matter analysis that was utilized for claim 4, as described above, is equally applicable to claim 13. Therefore, claim 13 is ineligible.
With respect to claim 14:
The claim recites similar limitations as corresponding to claim 5. Therefore, the same subject matter analysis that was utilized for claim 5, as described above, is equally applicable to claim 14. Therefore, claim 14 is ineligible.
With respect to claim 15:
The claim recites similar limitations as corresponding to claim 6. Therefore, the same subject matter analysis that was utilized for claim 6, as described above, is equally applicable to claim 15. Therefore, claim 15 is ineligible.
With respect to claim 16:
The claim recites similar limitations as corresponding to claim 7. Therefore, the same subject matter analysis that was utilized for claim 7, as described above, is equally applicable to claim 16. Therefore, claim 16 is ineligible.
With respect to claim 18:
The claim recites similar limitations as corresponding to claim 9. Therefore, the same subject matter analysis that was utilized for claim 9, as described above, is equally applicable to claim 18. Therefore, claim 18 is ineligible.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL P GRUSZKA whose telephone number is (571)272-5259. The examiner can normally be reached M-F 9:00 AM - 6:00 PM ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Li Zhen can be reached at (571) 272-3768. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DANIEL GRUSZKA/Examiner, Art Unit 2121
/Li B. Zhen/Supervisory Patent Examiner, Art Unit 2121
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