DETAILED ACTION
This Action is responsive to claims filed 08/16/2022.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Status of the Claims
Claims 1-17 are pending.
Specification
The disclosure is objected to because of the following informalities:
Page 15, first paragraph: “Evert time a local parameter…” should be “Every”
Page 20, first sentence: “second counting result 95 form the second…” should be “from”
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 1-17 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The single reference to the value of the variable “T” in the Specification indicates it begins at the number 2, rather than 0 or 1. One of ordinary skill in the art may not immediately ascertain a counting variable should start at 2, rather than 0 or 1, from the claimed language.
It is unclear from the claims how one “acquires” a T-th global parameter by “using” the number of local parameters. It is also unclear from this verbiage if one is to use the parameters themselves, or the count of the parameters in this acquisition.
It is unclear from the claims what a “sign” is and subsequently, what a “sign value” represents. While one of ordinary skill in the art may reasonably interpret a “sign” to mean a positive or negative value, a “sign value” does not properly point out or distinctly claim a 0 or 1 bit representing a value as positive or negative as the Specification details.
In the “acquiring” and subsequent ”updating” step, it is unclear from the independent claims whether one should be acquiring both the T-th and (T-1)-th global parameters in order to for a comparison to take place.
Claim 6 and claim 14 are unclear on what it means for the reference value to “include” “a half of a total number of parameters.” It is unclear from this verbiage if half of the total parameters is a starting value, intermediate value, or a factor of the reference value,
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.
Claim 1-17 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; and because the claims as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than the abstract idea, see Alice Corporation Pty. Ltd. v. CLS Bank International, et al, 573 U.S. (2014). In determining whether the claims are subject matter eligible, the Examiner applies the 2019 USPTO Patent Eligibility Guidelines. (2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, Jan. 7, 2019.)
Step 1:
Claims 1-8 recite a method for determining a number of local parameters, which falls under the statutory category of a process. Claims 9-16 recite an apparatus for determining a number of local parameters, which falls under the statutory category of a machine. Claim 17 recites a learning processing system, which falls under the statutory category of a machine.
Step 2A – Prong 1:
Claim 1 recites an abstract idea, law of nature, or natural phenomenon. The limitations of “…determining a number of local parameters…”, “acquiring a T-th global parameter using the number of local parameters less than or equal to the number of local parameters to be aggregated;”, and “updating or maintaining the number of local parameters to be aggregated depending on whether signs are different between a (T-1)-th global parameter and the T-th global parameter.” under the broadest reasonable interpretation, cover a mental process including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper.
Determining a number of parameters is practically performed within the human mind or with the aid of pen and paper. “Acquiring,” as recited generally, a global parameter “using,” as recited generally, local parameters is practically performed within the human mind or with the aid of pen and paper. Updating or maintaining a number of parameters is practically performed within the human mind or with the aid of pen and paper.
Step 2A – Prong 2:
The additional elements of claim 1 do not integrate the abstract idea into a judicial exception. The claim recites the additional elements “local parameters”, “distributed learning processing apparatus “, and “global parameters” are recognized as non-generic computer components, but are recited at a high level of generality and are found to generally link the abstract idea to a particular technological environment or field of use (See MPEP 2106.05(h)).
The additional elements recited in the limitation “receiving a number of local parameters less than or equal to a number of local parameters to be aggregated from at least one distributed learning processing apparatus;” is recognized as mere pre- or post-extra-solution activity (See MPEP 2106.05(g)).
Step 2B:
The additional elements of claim 1 do not integrate the abstract idea into a judicial exception. The claim recites the additional elements “local parameters”, “distributed learning processing apparatus “, and “global parameters” are recognized as non-generic computer components, but are recited at a high level of generality and are found to generally link the abstract idea to a particular technological environment or field of use (See MPEP 2106.05(h)).
The additional elements recited in the limitation “receiving a number of local parameters less than or equal to a number of local parameters to be aggregated from at least one distributed learning processing apparatus;” is recognized as well-understood, routine, or conventional activity (See MPEP 2106.05(d)(II)(i) first list).
Taken alone or in ordered combination, these additional elements do not amount to significantly more than the above-identified abstract idea. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation.
For the reasons above, claim 1 is rejected as being directed to non-patentable subject matter under §101. This rejection applies equally to independent claims 9 and 17.
Claim 9 recites similar limitations to claim 1, with the exception of “An apparatus for determining a number of local parameters, the apparatus comprising: a communicator” and “a processor” The additional elements recited in the aforementioned limitations have been evaluated under Step 2A – Prong 2 and reevaluated under Step 2B. These elements are recognized as generic computer components recited at a high level of generality. Although they have and execute instructions to perform the abstract idea itself, this also does not serve to integrate the abstract idea into a practical application as it merely amounts to instructions to "apply it." (See MPEP 2106.04(d)(2) indicating mere instructions to apply an abstract idea does not amount to integrating the abstract idea into a practical application). These elements are insufficient to transform a judicial exception to a patentable invention because the recited elements are considered insignificant extra-solution activity (generic computer system, processing resources, links the judicial exception to a particular, respective, technological environment). The claim thus recites computing components only at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components; mere instructions to apply an exception using a generic computer component cannot provide an inventive concept (see MPEP 2106.05(f)).
Claim 17 recites similar to claim 1, with the exception of “A learning processing system comprising: at least one distributed learning processing apparatus configured to perform learning; and a number-of-local-parameters determination apparatus” The additional elements recited in the aforementioned limitations have been evaluated under Step 2A – Prong 2 and reevaluated under Step 2B. The elements not previously recognized to generally link the abstract idea to a particular technology or field of use are recognized as generic computer components recited at a high level of generality. Although they have and execute instructions to perform the abstract idea itself, this also does not serve to integrate the abstract idea into a practical application as it merely amounts to instructions to "apply it." (See MPEP 2106.04(d)(2) indicating mere instructions to apply an abstract idea does not amount to integrating the abstract idea into a practical application). These elements are insufficient to transform a judicial exception to a patentable invention because the recited elements are considered insignificant extra-solution activity (generic computer system, processing resources, links the judicial exception to a particular, respective, technological environment). The claim thus recites computing components only at a high-level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components; mere instructions to apply an exception using a generic computer component cannot provide an inventive concept (see MPEP 2106.05(f)).
Dependent Claims:
Claim 2 (Claim 10) recites abstract idea mental process steps “acquiring a first counting result by counting a number of cases in which the signs are different between the T-th global parameter and (T-1)-th global parameter; and comparing the first counting result and a first reference value and updating or maintaining the number of local parameters to be aggregated according to a comparison result.” Acquiring a value by counting values is practically performed within the human mind or with the aid of pen and paper. Comparing values is practically performed within the human mind or with the aid of pen and paper.
Claim 3 (Claim 11) recites abstract idea mental process steps “updating a second counting result when the first counting result exceeds the first reference value; and increasing and thereby updating the number of local parameters to be aggregated when the updated second counting result exceeds a predefined second reference value.” Updating a value is practically performed within the human mind or with the aid of pen and paper. Increasing and thereby updating a value is practically performed within the human mind or with the aid of pen and paper.
Claim 4 (Claim 12) recites refinements to the abstract idea mental process steps of Claims 1 and 2.
Claim 5 (Claim 13) recites an abstract idea mental process step “initializing the updated second counting result when the updated second counting result exceeds the predefined second reference value.” The initializing of a value is practically performed within the human mind or with the aid of pen and paper.
Claim 6 (Claim 14) recites refinements to the additional elements or data.
Claim 7 (Claim 15) recites abstract idea mental process steps “performing an exclusive OR (XOR) operation between a sign value of the T-th global parameter and a sign value of the (T-1)-th global parameter; and acquiring the first counting result by summing results of the XOR operation or by counting a number of results with a value of 1 among the results of the XOR operation.” Performing an XOR operation is practically performed within the human mind or with the aid of pen and paper. Acquiring a value by summation is practically performed within the human mind or with the aid of pen and paper.
Claim 8 (Claim 16) recites pre- or post-extra-solution/WURC activity “delivering the T-th global parameter to the at least one distributed learning processing apparatus.”
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-2, 6-10, and 14-17 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Wang et al. (CMFL: Mitigating Communication Overhead for Federated Learning, 2019), hereinafter Wang.
In regards to claim 1: The present invention claims: “A method of determining a number of local parameters, the method comprising:” Wang seeks to reduce the number of redundant communication rounds in federated learning by ignoring local parameters that do not meet a significance threshold (Page 958, Section A).
“receiving a number of local parameters less than or equal to a number of local parameters to be aggregated from at least one distributed learning processing apparatus; acquiring a T-th global parameter using the number of local parameters less than or equal to the number of local parameters to be aggregated;” Wang teaches a federated learning system that aggregates local models and parameters into a global model or global set of parameters (Page 956, Section A; Page 958, Section A; Page 959, Aggregation at the…) (Examiner’s Note: Given the broadness of these two limitations, the Examiner is interpreting them generally as fairly typical federated learning steps (aggregation of parameters, generating a global parameter set based on the aggregation) that would have been known by one of ordinary skill in the art at the time of the Applicant’s filing).
“and updating or maintaining the number of local parameters to be aggregated depending on whether signs are different between a (T-1)-th global parameter and the T-th global parameter.” Wang teaches “we use the global update made in the previous iteration to estimate that in the current iteration. Our insight is: given that model training usually converges steadily and smoothly, the difference between two sequential global updates should be small.“ (Page 958, left column) and “Given the (estimated) global update in the current iteration, we need to choose an appropriate metric to measure the relevance of a local update. As a training update is essentially a gradient vector of model parameters, we compare the two updates—local and global—parameter-wise. We compute how many parameters are of the same sign in the two updates, and normalize the result by the total number of parameters. This gives the percentage of same-sign parameters in the two updates. We shall use this percentage to measure the relevance of a local update.” (Examiner’s Note: Given the broadness of this claim limitation, the Examiner is interpreting comparing the sign values of a local update (which may be the one and only local update parameters being sent to the server, and therefore the global update) against the (t-1)-th global parameter set based on the signs of the parameters).
In regards to claim 2: The present invention claims: “acquiring a first counting result by counting a number of cases in which the signs are different between the T-th global parameter and (T-1)-th global parameter;” Wang teaches “We compute how many parameters are of the same sign in the two updates, and normalize the result by the total number of parameters. This gives the percentage of same-sign parameters in the two updates.” (Page 958, right column).
“and comparing the first counting result and a first reference value and updating or maintaining the number of local parameters to be aggregated according to a comparison result.” Wang teaches “Following this idea, our solution dynamically identifies relevant local updates and excludes those irrelevant from being updated. An update is considered irrelevant if its relevance measure (9) is smaller than a predefined threshold.” (Page 958, right column).
In regards to claim 6: The present invention claims: “wherein the first reference value includes a half of a total number of parameters.” Under the BRI of Claim 6, Wang reads on “the first reference value includes a half of a total number of parameters” because the threshold value of Wang is tunable (Page 958) and may be tuned to a value being equal to or less than or greater than half of the total number of parameters.
In regards to claim 7: The present invention claims: “performing an exclusive OR (XOR) operation between a sign value of the T-th global parameter and a sign value of the (T-1)-th global parameter;” See Wang Equation 9 (Page 958) for where a comparison equaling 1 indicates signs are the same, while 0 indicates signs are different.
“and acquiring the first counting result by summing results of the XOR operation or by counting a number of results with a value of 1 among the results of the XOR operation.” See Wang Equation 9 (Page 958) for the results of the aforementioned comparisons being summed before comparison to a threshold value to determine a local parameter’s relevance.
In regards to claim 8: The present invention claims: “delivering the T-th global parameter to the at least one distributed learning processing apparatus.” Wang teaches a federated learning system that aggregates local models and parameters into a global model or global set of parameters that is sent back to local models (Page 956, Section A; Page 958, Section A; Page 959, Aggregation at the…) (Examiner’s Note: Given the broadness of Claim 8, the Examiner is interpreting it generally as fairly typical federated learning behavior (aggregation of parameters, generating a global parameter set based on the aggregation, sending global parameters back to local models) that would have been known by one of ordinary skill in the art at the time of the Applicant’s filing).
In regards to claims 9-10 and 14-16: The limitations of claims 9-10 and 14-16 are similar to those of claims 1-2 and 6-8, with the exception of “An apparatus for determining a number of local parameters, the apparatus comprising: a communicator configured…” of claim 9. “A communicator” is broadly interpretable as a processing device. Therefore, both sets of claims are similarly rejected.
In regards to claim 17: The limitations of claims 17 are similar to those of claims 1, with the exception of “A learning processing system comprising: at least one distributed learning processing apparatus configured to perform learning; and a number-of-local-parameters determination apparatus…” of claim 17. “A number-of-local-parameters determination apparatus” is broadly interpretable as a processing device. Therefore, both sets of claims are similarly rejected.
Allowable Subject Matter
Claims 3-5 and 11-13 are allowable over the prior art, but are objected to as being dependent upon a rejected base claim. The claims would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims, should the outstanding 112(b) and 101 Rejections be overcome.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GRIFFIN T BEAN whose telephone number is (703)756-1473. The examiner can normally be reached M - F 7:30 - 4:30.
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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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/GRIFFIN TANNER BEAN/Examiner, Art Unit 2121
/Li B. Zhen/Supervisory Patent Examiner, Art Unit 2121