DETAILED ACTION
This correspondence is responsive to the application and preliminary amendment filed on March 9, 2023. Claims 1-20 are pending in the case, with claims 1, 19 and 20 in independent form.
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
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Summary of Detailed Action
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1, 10, 19, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Storm et al. in view of Waller et al.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) subject matter at a general, high-level for method for parameter adjusting method, comprising performing classification processing on input data, performing reduction processing on the classification prediction values, performing normalization processing on the classification prediction values subjected to the reduction processing to obtain a normalization result of the classification prediction values; and updating a parameter according to the normalization result of the classification prediction values, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I). This judicial exception is not integrated into a practical application and the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Claims 1-20 recite one of the four statutory categories of patent able subject matter and belong to the statutory class(es) of a process (method claims 1-18), a machine (system/apparatus claims 19), and an article of manufacture (non-transitory computer readable media claims 20).
Claim 1 recites a method, thus a process and one of the four statutory categories of patentable subject matter. However, claim 1 further recites for a parameter adjusting method, comprising: performing classification processing on input data, performing reduction processing on the classification prediction values; performing normalization processing on the classification prediction values subjected to the reduction processing to obtain a normalization result of the classification prediction values; and updating a parameter according to the normalization result of the classification prediction values, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I). Additionally, these recitations for a parameter adjusting method, comprising: performing classification processing on input data, performing reduction processing on the classification prediction values; performing normalization processing on the classification prediction values subjected to the reduction processing to obtain a normalization result of the classification prediction values; and updating a parameter according to the normalization result of the classification prediction values are also mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper. MPEP 210604(a)(2)(III).
The claim does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
A model (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f).) Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)).
by using a classification model obtained through training based on secure multi-party computing, to obtain classification prediction values of the classification model (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f). Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)). This is also an additional element of extra-solution activity that courts have identified is well understood, routine and conventional activity for receiving (obtaining) or transmitting data over a network, e.g., using the internet to gather data. See also, MPEP 2106.05(d)(II), MPEP 2106.05(g), 2019 Guidance, 84 FR 50 at 55, 2019 Guidance, 84 FR 50, footnote 31.).
Thus, the claim is directed to the abstract idea.
Further, the additional elements, alone or in combination, do not provide significantly more than the abstract idea itself, because implementation on a computer (MPEP 2106.05(f)) cannot provide significantly more, and generally linking the use of the judicial exception to a particular technological field of use does not meaningfully limit the claims (MPEP 2106.04(d)), and transmitting data over a network is well-understood, routine and conventional (MPEP 2106.05(d), and the combination of additional elements does not provide an inventive concept. Thus, the claim is ineligible.
Claim 2, dependent on claim 1, recites only additional abstract ideas for wherein the performing the reduction processing on the classification prediction values comprises: determining a maximum value in the classification prediction values; and dividing a respective classification prediction value by the maximum value, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I). Additionally, these recitations for wherein the performing the reduction processing on the classification prediction values comprises: determining a maximum value in the classification prediction values; and dividing a respective classification prediction value by the maximum value are also mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper. MPEP 210604(a)(2)(III).
Claim 3, dependent on claim 2, recites only additional abstract ideas for wherein the dividing the respective classification prediction value by the maximum value comprises: taking the respective classification prediction value and the maximum value as a first variable and a second variable, respectively, wherein a number of significant bits of the second variable is greater than or equal to a number of significant bits of the first variable; comparing whether the first variable is greater than or equal to the second variable; determining a value of a current bit of a quotient and updating the first variable and the second variable according to a compare result; comparing the updated first variable and second variable, and determining a value of a following bit of the quotient according to a compare result until a number of bits of the quotient reaches a preset length of significant bits, wherein the obtained quotient is a result of dividing the respective classification prediction value by the maximum value, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I).
Claim 4, dependent on claim 3, recites only additional abstract ideas for wherein the determining the value of the current bit of the quotient according to the compare result comprises: adding 1 or 0 to the end of the quotient according to the compare result, wherein 1 is added to the end of the quotient when the first variable is greater than or equal to the second variable, and 0 is added to the end of the quotient when the first variable is smaller than the second variable, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I).
Claim 5, dependent on claim 4, recites only additional abstract ideas for wherein the adding 1 or 0 to the end of the quotient according to the compare result, wherein 1 is added to the end of the quotient when the first variable is greater than or equal to the second variable, and 0 is added to the end of the quotient when the first variable is smaller than the second variable, comprises: adding 0 to the end of the quotient; and performing an XOR operation on the quotient with 0 added to the end thereof and the compare result, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I).
Claim 6, dependent on claim 3, recites only additional abstract ideas for wherein updating the first variable according to the compare result comprises: performing first update processing on the first variable to obtain a first update result, wherein the first update processing is update processing on the first variable when the first variable is greater than or equal to the second variable; performing second update processing on the first variable to obtain a second update result, wherein the second update processing is update processing on the first variable when the first variable is smaller than the second variable; calculating a first product of the compare result and the first update result, and a second product of a NOT operation result of the compare result and the second update result; and taking a sum of the first product and the second product as the updated first variable, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I).
Claim 7, dependent on claim 3, recites only additional abstract ideas for wherein the updating the second variable according to the compare result comprises: performing third update processing on the second variable to obtain a third update result, wherein the third update processing is update processing on the second variable when the first variable is greater than or equal to the second variable; calculating a third product of the compare result and the third update result, and a fourth product of a NOT operation result of the compare result and the second variable; and taking a sum of the third product and the fourth product as the updated second variable, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I).
Claim 8, dependent on claim 1, recites additional abstract ideas for wherein the performing the normalization processing on the classification prediction values subjected to the reduction processing to obtain the normalization result of the classification prediction values comprises: setting a value of a function parameter n in an exponential function to be the parameter threshold and calculating an exponential function value of a respective classification prediction value subjected to the reduction processing; and determining, according to the respective exponential function value and a sum of all exponential function values, the normalization result of the respective classification prediction value subjected to the reduction processing, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I).
Claim 8, does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
acquiring a parameter threshold (An additional element of extra-solution activity that courts have identified is well understood, routine and conventional activity for receiving or transmitting data over a network, e.g., using the internet to gather data. See also, MPEP 2106.05(d)(II), MPEP 2106.05(g), 2019 Guidance, 84 FR 50 at 55, 2019 Guidance, 84 FR 50, footnote 31.).
Claim 9, dependent on claim 8, recites only additional abstract ideas for wherein the setting the value of the function parameter n in the exponential function to be the parameter threshold and the calculating the exponential function value of the respective classification prediction value subjected to the reduction processing comprise: for the respective classification prediction value subjected to the reduction processing, calculating the exponential function value of the classification prediction value subjected to the reduction processing, through the following equation:
PNG
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48
148
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Greyscale
wherein e is a natural constant, x is the classification prediction value subjected to the reduction processing,
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26
28
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Greyscale
is the exponential function value of the classification prediction value subjected to the reduction processing, M is the parameter threshold,
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media_image3.png
32
30
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Greyscale
is the reciprocal of the parameter threshold, and M is a constant, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I).
Claim 10, dependent on claim 1, recites additional abstract ideas for wherein the updating the parameter according to the normalization result of the classification prediction values comprises: determining a classification result according to the normalization result of the classification prediction values; and updating the parameter according to the classification result, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I). Additionally, these recitations for wherein the updating the parameter according to the normalization result of the classification prediction values comprises: determining a classification result according to the normalization result of the classification prediction values; and updating the parameter according to the classification result are also mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper. MPEP 210604(a)(2)(III).
Claim 10, does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
of the classification model (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f).) Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)).
Claim 11, dependent on claim 4, recites only additional abstract ideas for wherein updating the first variable according to the compare result comprises: performing first update processing on the first variable to obtain a first update result, wherein the first update processing is update processing on the first variable when the first variable is greater than or equal to the second variable; performing second update processing on the first variable to obtain a second update result, wherein the second update processing is update processing on the first variable when the first variable is smaller than the second variable; calculating a first product of the compare result and the first update result, and a second product of a NOT operation result of the compare result and the second update result; and taking a sum of the first product and the second product as the updated first variable, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I).
Claim 12, dependent on claim 5, recites only additional abstract ideas for wherein updating the first variable according to the compare result comprises: performing first update processing on the first variable to obtain a first update result, wherein the first update processing is update processing on the first variable when the first variable is greater than or equal to the second variable; performing second update processing on the first variable to obtain a second update result, wherein the second update processing is update processing on the first variable when the first variable is smaller than the second variable; calculating a first product of the compare result and the first update result, and a second product of a NOT operation result of the compare result and the second update result; and taking a sum of the first product and the second product as the updated first variable, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I).
Claim 13, dependent on claim 4, recites only additional abstract ideas for wherein the updating the second variable according to the compare result comprises: performing third update processing on the second variable to obtain a third update result, wherein the third update processing is update processing on the second variable when the first variable is greater than or equal to the second variable; calculating a third product of the compare result and the third update result, and a fourth product of a NOT operation result of the compare result and the second variable; and taking a sum of the third product and the fourth product as the updated second variable, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I).
Claim 14, dependent on claim 5, recites only additional abstract ideas for wherein the updating the second variable according to the compare result comprises: performing third update processing on the second variable to obtain a third update result, wherein the third update processing is update processing on the second variable when the first variable is greater than or equal to the second variable; calculating a third product of the compare result and the third update result, and a fourth product of a NOT operation result of the compare result and the second variable; and taking a sum of the third product and the fourth product as the updated second variable, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I).
Claim 15, dependent on claim 6, recites only additional abstract ideas for wherein the updating the second variable according to the compare result comprises: performing third update processing on the second variable to obtain a third update result, wherein the third update processing is update processing on the second variable when the first variable is greater than or equal to the second variable; calculating a third product of the compare result and the third update result, and a fourth product of a NOT operation result of the compare result and the second variable; and taking a sum of the third product and the fourth product as the updated second variable, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I).
Claim 16, dependent on claim 2, recites additional abstract ideas for wherein the updating the parameter according to the normalization result of the classification prediction values comprises: determining a classification result according to the normalization result of the classification prediction values; and updating the parameter according to the classification result, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I). Additionally, these recitations for wherein the updating the parameter according to the normalization result of the classification prediction values comprises: determining a classification result according to the normalization result of the classification prediction values; and updating the parameter according to the classification result are also mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper. MPEP 210604(a)(2)(III).
Claim 16, does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
of the classification model (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f).) Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)).
Claim 17, dependent on claim 3, recites additional abstract ideas for wherein the updating the parameter according to the normalization result of the classification prediction values comprises: determining a classification result according to the normalization result of the classification prediction values; and updating the parameter according to the classification result, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I). Additionally, these recitations for wherein the updating the parameter according to the normalization result of the classification prediction values comprises: determining a classification result according to the normalization result of the classification prediction values; and updating the parameter according to the classification result are also mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper. MPEP 210604(a)(2)(III).
Claim 17, does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
of the classification model (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f).) Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)).
Claim 18, dependent on claim 4, recites additional abstract ideas for
wherein the updating the parameter according to the normalization result of the classification prediction values comprises: determining a classification result according to the normalization result of the classification prediction values; and updating the parameter according to the classification result, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I). Additionally, these recitations for wherein the updating the parameter according to the normalization result of the classification prediction values comprises: determining a classification result according to the normalization result of the classification prediction values; and updating the parameter according to the classification result are also mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper. MPEP 210604(a)(2)(III).
Claim 18, does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
of the classification model (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f).) Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)).
Claim 19 recites a device, thus a machine and one of the four statutory categories of patentable subject matter. However, claim 19 further recites for performing classification processing on input data, performing reduction processing on the classification prediction values; performing normalization processing on the classification prediction values subjected to the reduction processing to obtain a normalization result of the classification prediction values; and updating a parameter according to the normalization result of the classification prediction values, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I). Additionally, these recitations for performing classification processing on input data, performing reduction processing on the classification prediction values; performing normalization processing on the classification prediction values subjected to the reduction processing to obtain a normalization result of the classification prediction values; and updating a parameter according to the normalization result of the classification prediction values are also mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper. MPEP 210604(a)(2)(III).
The claim does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
An electronic device, comprising: at least one processor, and a memory communicatively connected with the at least one processor; wherein the memory has stored thereon instructions executable by the at least one processor, and the instructions, when executed by the at least one processor, enable the at least one processor to implement the steps of (an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See also, MPEP 2106.05(f), MPEP 2106.04(d), 2019 Guidance, 84 FR 50 at 55, footnote 30.).
by using a classification model obtained through training based on secure multi-party computing, to obtain classification prediction values of the classification model (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f). Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)). This is also an additional element of extra-solution activity that courts have identified is well understood, routine and conventional activity for receiving (obtaining) or transmitting data over a network, e.g., using the internet to gather data. See also, MPEP 2106.05(d)(II), MPEP 2106.05(g), 2019 Guidance, 84 FR 50 at 55, 2019 Guidance, 84 FR 50, footnote 31.).
of the classification model (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f).) Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)).
Thus, the claim is directed to the abstract idea.
Further, the additional elements, alone or in combination, do not provide significantly more than the abstract idea itself, because implementation on a computer (MPEP 2106.05(f)) cannot provide significantly more, and generally linking the use of the judicial exception to a particular technological field of use does not meaningfully limit the claims (MPEP 2106.04(d)), and transmitting data over a network is well-understood, routine and conventional (MPEP 2106.05(d), and the combination of additional elements does not provide an inventive concept. Thus, the claim is ineligible.
Claim 20 recites A non-transitory computer-readable storage medium, thus an article of manufacture and one of the four statutory categories of patentable subject matter. However, claim 20 further recites for performing classification processing on input data, performing reduction processing on the classification prediction values; performing normalization processing on the classification prediction values subjected to the reduction processing to obtain a normalization result of the classification prediction values; and updating a parameter according to the normalization result of the classification prediction values, which are mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I). Additionally, these recitations for performing classification processing on input data, performing reduction processing on the classification prediction values; performing normalization processing on the classification prediction values subjected to the reduction processing to obtain a normalization result of the classification prediction values; and updating a parameter according to the normalization result of the classification prediction values are also mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper. MPEP 210604(a)(2)(III).
The claim does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
A non-transitory computer-readable storage medium on which computer instructions are stored, wherein the computer instructions are configured to enable the computer to execute the steps of (an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See also, MPEP 2106.05(f), MPEP 2106.04(d), 2019 Guidance, 84 FR 50 at 55, footnote 30.).
by using a classification model obtained through training based on secure multi-party computing, to obtain classification prediction values of the classification model (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f). Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)). This is also an additional element of extra-solution activity that courts have identified is well understood, routine and conventional activity for receiving (obtaining) or transmitting data over a network, e.g., using the internet to gather data. See also, MPEP 2106.05(d)(II), MPEP 2106.05(g), 2019 Guidance, 84 FR 50 at 55, 2019 Guidance, 84 FR 50, footnote 31.).
of the classification model (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f).) Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)).
Thus, the claim is directed to the abstract idea.
Further, the additional elements, alone or in combination, do not provide significantly more than the abstract idea itself, because implementation on a computer (MPEP 2106.05(f)) cannot provide significantly more, and generally linking the use of the judicial exception to a particular technological field of use does not meaningfully limit the claims (MPEP 2106.04(d)), and transmitting data over a network is well-understood, routine and conventional (MPEP 2106.05(d), and the combination of additional elements does not provide an inventive concept. Thus, the claim is ineligible.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1, 10, 19, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Storm in view of Waller et al. (GB 2594453 A, filed April 4, 2020) hereinafter Waller. The Examiner notes that Storm is cited on Applicant’s Information Disclosure Statement filed March 9, 2023.
Regarding claim 1, Storm teaches:
A model parameter adjusting method, comprising:
Storm teaches that The final convolution can involves backpropagation to more accurately weight the end product at the output layer 1006 (A model parameter adjusting (backpropagation model parameter adjusting) method). Mathematically, the “convolution” can include applying a sliding dot product or cross-correlation. Strom, Figs 10, 11, para 134.
performing classification processing on input data by using a classification model obtained through training based on secure multi-party computing, to obtain classification prediction values of the classification model (i.e., );
Storm teaches that, A description of an example multiparty computing environment, as illustrated in FIG. 1, and a description of example methods and techniques for achieving privacy for both data and an algorithm that operates on the data is provided, as illustrated in FIGS. 2 through 9B, will then follow. FIGS. 9C-12 provide further illustrations of embodiments disclosed herein, including convolutional neural networks and flow diagrams of various methods related to achieving privacy both for algorithms and data in an efficient manner (performing classification processing on input data by using a classification model obtained through training (performing classification processing, classification, obtained through training, para 138, 166, Figures 10-11) based on secure multi-party computing, to obtain classification prediction values of the classification model (classification values of the classification model, para 138, 166, Figures 10-11)). Storm, Fig 11, para 45, 7, 134, 138, 166. The fully connected layers 1104C connect every neuron in one layer to every neuron in another layer. This layer is similar to the traditional multi-layer perceptron neural network (MLP). The flattened matrix goes through a fully connected layer to classify the images. A flatten layer is a rearrangement of the data which can involves rearranging shares. The output image 1110 can then be classified. For example, the output may identify the image as a park, or a city, and so forth. Sharma, Fig 11, para 138, 166, 45. The input of the neural network can include an image and the output of the neural network can include at least one of an indication of one or more features detected in the image and/or a classification of one or more features in the image. Storm, Figs 10-11, para 166, 138, 134, 45.
performing normalization processing on the classification prediction values
Storm teaches that, An activation function, or a Re-LU layer, is subsequently followed by additional convolutions such as pooling layers, fully connected layers and normalization layers , referred to as hidden layers 1004A, 1004B, 1004C. Storm Figs 10-11, para 134, 142, 164-166, 136, 138, 7, 45, 166. [0142] The system proceeds to process data layer by layer by layer applying these kinds of operations. The last layer can be a softmax layer. The approach outputs the same softmax layer even though the system performs complicated math to hide it. The softmax layer is what reveals the output of the neural network (performing normalization processing on the classification prediction values (performing softmax normalization on the classification prediction values) the softmax normalization result) of the classification prediction values). One technical benefit of this process is that it obtains results in fewer network hops. Storm Figs 10-11, para 142, 134, 164-166, 136, 138, 7, 45, 166.
updating a parameter of the classification model according to the normalization result of the classification prediction values.
Storm teaches that, The final convolution can involves backpropagation to more accurately weight the end product at the output layer 1006 (updating a parameter of the classification model according to the normalization result of the classification prediction values). Mathematically, the “convolution” can include applying a sliding dot product or cross-correlation. Strom, Figs 10, 11, para 134.
As discussed above, Storm teaches A model parameter adjusting method, comprising: performing classification processing on input data by using a classification model obtained through training based on secure multi-party computing, to obtain classification prediction values of the classification model, performing normalization processing on the classification prediction values to obtain a normalization result of the classification prediction values, and updating a parameter of the classification model according to the normalization result of the classification prediction values.
Storm does not specifically disclose “performing reduction processing on the classification prediction value;” performing normalization processing on the classification prediction values “subjected to the reduction processing.”
However, Waller teaches in the field related to methods and systems for training of a machine learning model. Waller, page 1-2. Waller, which is analogous to the claimed invention because Waller is directed to training machine learning, privacy and classification, teaches that, Figure 1 shows a schematic of steps carried out according to an embodiment. Here, a user 101 has a model (machine learning algorithm) for performing a particular task such as classifying images, for example. Waller, page 6.When modifying the Softmax layer, training errors may occur due to integer overflow errors; the application of weights in a neuron may cause the result to be too big for the HE scheme to handle, since HE schemes have a fixed maximum plaintext value once their parameters have been set. Applying a Batch Normalisation layer before the HE-compatible Softmax layer can help to fix this problem (performing reduction processing (performing batch normalization reduction processing) on the classification prediction value (classification prediction value, page 6), performing normalization processing (performing softmax normalization) on the classification prediction values (classification prediction value, page 6) subjected to the reduction processing (subjected to the batch normalization reduction processing)) by ensuring that inputs to approximations are in the right interval at which the approximation functions best approximate the original functions. Batch Normalisation layers may also be used before other layers in a HE-compatible CNN in order to prevent integer overflow errors occurring in other layers. Waller, page 8, 6.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present application to implement the model parameter adjusting method of Storm using the feature for performing reduction processing on the classification prediction value, performing normalization processing on the classification prediction values subjected to the reduction processing of Waller, with a reasonable expectation of success, in order to provide for handling and processing the encrypted data in the classification phase in the same way as in the training phase and to prevent integer overflow errors occurring in other layers. Waller, pages 3, 2, 8, 6. This would have provided the advantages of training and updating the model and normalizing results while preventing overflow errors.
Regarding claim 10, which depends from claim 1 and recites:
wherein the updating the parameter of the classification model according to the normalization result of the classification prediction values comprises:
determining a classification result of the classification model according to the normalization result of the classification prediction values; and updating the parameter of the classification model according to the classification result.
Storm in view of Waller teaches the method of claim 1 from which claim 10 depends, including updating the parameter of the classification model according to the normalization result of the classification prediction values. As similarly discussed above, Storm teaches that, An activation function, or a Re-LU layer, is subsequently followed by additional convolutions such as pooling layers, fully connected layers and normalization layers , referred to as hidden layers 1004A, 1004B, 1004C. Storm Figs 10-11, para 134, 142, 164-166, 136, 138, 7, 45, 166. [0142] The system proceeds to process data layer by layer by layer applying these kinds of operations. The last layer can be a softmax layer. The approach outputs the same softmax layer even though the system performs complicated math to hide it. The softmax layer is what reveals the output of the neural network (determining a classification result of the classification model according to the normalization (softmax normalization) result of the classification prediction values). One technical benefit of this process is that it obtains results in fewer network hops. Storm Figs 10-11, para 142, 134, 164-166, 136, 138, 7, 45, 166. Storm teaches that, The final convolution can involves backpropagation to more accurately weight the end product at the output layer 1006 (updating the parameter of the classification model according to the classification result). Mathematically, the “convolution” can include applying a sliding dot product or cross-correlation. Strom, Figs 10, 11, para 134.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the present application to implement the model parameter adjusting method of Storm using the feature for performing reduction processing on the classification prediction value, performing normalization processing on the classification prediction values subjected to the reduction processing of Waller, with a reasonable expectation of success, in order to provide for handling and processing the encrypted data in the classification phase in the same way as in the training phase and to prevent integer overflow errors occurring in other layers. Waller, pages 3, 2, 8, 6. This would have provided the advantages of training and updating the model and normalizing results while preventing overflow errors.
Claim 19 recites an electronic device that parallels the method of claim 1. Therefore, the analysis discussed above with respect to claim 1 also applies to claim 19. Accordingly, claim 19 is rejected based on substantially the same rationale as set forth above with respect to claim 1. More specifically regarding, An electronic device, comprising: at least one processor, and a memory communicatively connected with the at least one processor; wherein the memory has stored thereon instructions executable by the at least one processor, and the instructions, when executed by the at least one processor, enable the at least one processor to implement the steps of (i.e., Storm, Fig 13, para 169-173, claim 10).
Claim 20 recites a non-transitory computer-readable storage medium that parallels the method of claim 1. Therefore, the analysis discussed above with respect to claim 1 also applies to claim 20. Accordingly, claim 20 is rejected based on substantially the same rationale as set forth above with respect to claim 1. More specifically regarding, A non-transitory computer-readable storage medium on which computer instructions are stored, wherein the computer instructions are configured to enable the computer to execute the steps of (i.e., Storm, Fig 13, para 174- 175, 169-173, claim 19).
Allowable Subject Matter
Claims 2-9, 11-18 would be allowable if the rejections of the claims under 35 U.S.C. 101 as being directed to an abstract idea without significantly more are overcome.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US-20200164517-A1, US-20190378210-A1, US-20210279635-A1,
US-20180114028-A1.
MISHINA, Ibuki et al. CN 114245917 Secret Normalization Index Function Calculating System, Secret Normalization Index Function Calculating Method, A Secret Neural Network Calculating System, A Secret Neural Network Learning System, Program, English Translation, Filed August 14, 2019.
SHARMA, Shantanu et al. WO 2023/132791 A2, Priority January 4, 2022, Method and System for Variable On-Demand Privacy- Preserving Federated Learning Using Multiparty Computation. 2022.
JING, Xiao-dong CN 119094101A, Data Analysis Method and Device Based on Multi-party Security Calculation, Filed September 4, 2024.
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/BARBARA M LEVEL/ Examiner, Art Unit 2142
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