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 .
Status of the Claims
Claims 1, 5, 12, 19, 22, 24, and 30-34 have been amended. Claims 1, 5-12, 16-17, 19, 22, 24-26, and 28-34 are currently pending and have been considered by the Examiner.
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.
Claims 1, 5-12, 16-17, 19, 22, 24-26, and 28-34 are 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.
In claim 1, lines 14-17 recite the hyperparameter tuning program selects a first candidate before it provides the selected first candidate to the user program. Claim 1 on page 3, lines 5-6 and 13-14 renders the claim indefinite because it is unclear whether the hyperparameter tuning program selects a second hyperparameter value before it provides the second hyperparameter to the user program. Examiner treats claim 1 to mean the hyperparameter tuning program selects a second hyperparameter value before it provides the second hyperparameter to the user program.
Claims 5-12, 16-17, 22, 25-26, 28, 31, and 33-34 are rejected for failing to cure the deficiencies of claim 1.
Claim 19 is directed to a product which recites the same indefinite limitations as the method of claim 1 and is therefore rejected for at least the same reasons.
Claims 24, 29, and 32 are rejected for failing to cure the deficiencies of claim 19.
Claim 30 is directed to a system which recites the same indefinite limitations as the method of claim 1 and is therefore rejected for at least the same reasons.
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, 5-12, 16-17, 19, 22, 24-26, and 28-34 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claims 1, 5-12, 16-17, 22, 25-26, 28, 31, 33-34 recite a method. Claims 19, 24, 29, 32 recite a hyperparameter tuning device comprising a processor (a product). Claim 30 recites a hyperparameter tuning system comprising a processor (a system). Each of a method, a product, and a system falls within one of the four statutory categories of patent eligible subject matter.
Claim 1
Step 2A Prong 1: Providing, by the user
Receiving, by the hyperparameter tuning [module]
Selecting, by the hyperparameter tuning [module]
Providing, by the hyperparameter tuning [module] people” includes a teacher teaching a student. The teacher may provide the first hyperparameter to the student.
Receiving, by the user
Providing, by the user
Receiving, by the hyperparameter tuning [module]
Providing, by the hyperparameter tuning [module] interactions between people” includes a teacher teaching a student. The teacher may provide the second hyperparameter to the student. The claim recites an abstract idea.
Step 2A Prong 2: One or more processors amounts to a generic computer component for applying the abstract ideas on a generic computer under MPEP 2106.05(f).
Generating, by a user program, a first hyperparameter obtaining request for a first hyperparameter according to a hyperparameter obtaining code written in the user program written by using a machine learning library for training a machine learning model, … the plurality of candidates being written in the hyperparameter obtaining code in the user program amounts to mere instructions for applying the abstract ideas on a generic computer under MPEP 2106.05(f) and a field of use and technological environment under MPEP 2106.05(h).
A hyperparameter tuning program amounts to mere instructions for applying the abstract ideas on a generic computer under MPEP 2106.05(f).
Generating, by the user program, a second hyperparameter obtaining request for a second hyperparameter, based on the selected first candidate for the first hyperparameter, according to the hyperparameter obtaining code amounts to mere instructions for applying the abstract ideas on a generic computer under MPEP 2106.05(f) and a field of use and technological environment under MPEP 2106.05(h).
Training, by the user program, the machine learning model by applying a set of the provided first hyperparameter and the provided second hyperparameter amounts to mere instructions for applying the abstract ideas on a generic computer under MPEP 2106.05(f).
The additional elements as disclosed above, alone or in combination, do not integrate the abstract ideas into a practical application as they are generic computer functions as disclosed in combination with a mere field of use that are implemented to perform the abstract ideas disclosed above. The claim is directed to an abstract idea. The additional elements as disclosed above, in combination with the abstract ideas, are not sufficient to amount to significantly more than the abstract ideas as they are generic computer functions as disclosed in combination with a mere field of use that are implemented to perform the abstract ideas disclosed above. The claim is not patent eligible.
Claim 5 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated. The first hyperparameter obtaining request requests a type of the machine learning and the second hyperparameter obtaining request requests a hyperparameter specific to the type of the machine learning model is a method of organizing human activity. The sub-grouping “managing personal behavior or relationships or interactions between people” includes a teacher teaching a student. The teacher may receive a first request and a second request from the student.
Step 2A Prong 2 and Step 2B: A control structure amounts to mere instructions to apply the abstract ideas on a generic computer under MPEP 2106.05(f). The claim is not patent eligible.
Claim 6 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated. Setting a hyperparameter that defines a structure of the machine learning model is a judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper.
Setting a hyperparameter that defines a training process of the machine learning model is a judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper.
A human mind can reasonably set a hyperparameter that defines a structure of a machine learning model and a hyperparameter that defines a training process of the machine learning model by recording them on paper. Specification paragraph [0010], lines 13-18 and Fig. 1 discloses setting a hyperparameter that defines a number of layers to 10 layers, and setting a hyperparameter that defines a learning rate to 0.001. Fig. 1 itself shows that one can set these hyperparameters by recording them on paper.
Step 2A Prong 2 and Step 2B: The hyperparameter obtaining code is modularized by sets of code amounts to mere instructions to apply the abstract ideas on a generic computer under MPEP 2106.05(f). The claim is not patent eligible.
Claim 7 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated. The providing of the second hyperparameter provides a hyperparameter is a method of organizing human activity. The sub-grouping “managing personal behavior or relationships or interactions between people” includes a teacher teaching a student. The teacher may provide the second hyperparameter to the student.
Selecting a hyperparameter based on a predetermined hyperparameter selection algorithm is a judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper. A human mind can reasonably select a hyperparameter based on the result of applying an algorithm.
Step 2A Prong 2 and Step 2B: The claim does not recite any additional element which, alone or in combination, do not integrate the abstract ideas into a practical application or which, in combination with the abstract ideas, would be sufficient to amount to significantly more than the abstract ideas. The claim is not patent eligible.
Claim 8 incorporates the rejection of claim 7.
Step 2A Prong 1: The abstract ideas of claim 7 are incorporated.
Step 2A Prong 2 and Step 2B: The predetermined hyperparameter selection algorithm is based on Bayesian optimization amounts to a field of use and technological environment under MPEP 2106.05(h). The claim is not patent eligible.
Claim 9 incorporates the rejection of claim 7.
Step 2A Prong 1: The abstract ideas of claim 7 are incorporated. The predetermined hyperparameter selection algorithm is based on a random search is a judgement mental process which can reasonably be performed in the human mind with the aid of pencil and paper. A human mind can reasonably perform a random search of hyperparameters by selecting hyperparameter values at random from a list of available values.
Step 2A Prong 2 and Step 2B: The claim does not recite any additional element which, alone or in combination, do not integrate the abstract ideas into a practical application or which, in combination with the abstract ideas, would be sufficient to amount to significantly more than the abstract ideas. The claim is not patent eligible.
Claim 10 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated.
Step 2A Prong 2 and Step 2B: Obtaining an evaluation result of the user program to which the set of the provided first hyperparameter and the provided second hyperparameter are applied amounts to mere instructions to apply the abstract ideas on a generic computer under MPEP 2106.05(f). The claim is not patent eligible.
Claim 11 incorporates the rejection of claim 10.
Step 2A Prong 1: The abstract ideas of claim 10 are incorporated.
Step 2A Prong 2 and Step 2B: The evaluation result of the user program includes accuracy of the machine learning model amounts to a field of use and technological environment under MPEP 2106.05(h). The claim is not patent eligible.
Claim 12 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated. Repeating the receiving of the second hyperparameter obtaining request and the providing of the second hyperparameter until a termination condition is satisfied is a method of organizing human activity. The sub-grouping “managing personal behavior or relationships or interactions between people” includes a teacher teaching a student. The teacher may receive the second request from the student, and the teacher may provide the second hyperparameter to the student.
Step 2A Prong 2 and Step 2B: The claim does not recite any additional element which, alone or in combination, do not integrate the abstract ideas into a practical application or which, in combination with the abstract ideas, would be sufficient to amount to significantly more than the abstract ideas. The claim is not patent eligible.
Claim 16 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated.
Step 2A Prong 2 and Step 2B: Generating a computer program using the hyperparameter tuning method as claimed in claim 1 amounts to mere instructions to apply the abstract ideas on a generic computer under MPEP 2106.05(f). The claim is not patent eligible.
Claim 17 incorporates the rejection of claim 16.
Step 2A Prong 1: The abstract ideas of claim 16 are incorporated.
Step 2A Prong 2 and Step 2B: The computer program is a machine learning model amounts to a field of use and technological environment under MPEP 2106.05(h). The claim is not patent eligible.
Claim 19 recites a hyperparameter tuning device comprising processors which implements the same features as the method of claim 1 and is therefore rejected for at least the same reasons.
In Step 2A Prong 2 and Step 2B, a hyperparameter tuning device comprising one or more processors amounts to generic computer components for applying the abstract ideas on a generic computer under MPEP 2106.05(f). The claim is not patent eligible.
Claim 22 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated. Examiner treats a “trial” as any period of time. The receiving the first hyperparameter obtaining request of the first hyperparameter, the providing the first hyperparameter, the receiving the second hyperparameter obtaining request of the second hyperparameter, and the providing the second hyperparameter being performed in a same trial is a method of organizing human activity. The sub-grouping “managing personal behavior or relationships or interactions between people” includes a teacher teaching a student. The teacher may receive the first request, provide the first hyperparameter, receive the second request, and provide the second hyperparameter in a same trial or period of time.
Step 2A Prong 2 and Step 2B: The claim does not recite any additional element which, alone or in combination, do not integrate the abstract ideas into a practical application or which, in combination with the abstract ideas, would be sufficient to amount to significantly more than the abstract ideas. The claim is not patent eligible.
Claim 24 recites a hyperparameter tuning device comprising processors which implements the same features as the method of claim 22 and is therefore rejected for at least the same reasons. The claim is not patent eligible.
Claim 25 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated.
Step 2A Prong 2 and Step 2B: The set of the provided first hyperparameter and the provided second hyperparameter are applied as at least a part of hyperparameters for a same trial of training of the machine learning model amounts to mere instructions to apply the abstract ideas on a generic computer under MPEP 2106.05(f). The claim is not patent eligible.
Claim 26 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated. Selecting, based on the type of the provided first hyperparameter, the second hyperparameter whose type is specific to the type of the provided first hyperparameter is a judgement and evaluation mental process which can reasonably be performed in the human mind with the aid of pencil and paper. The claim recites an abstract idea.
Step 2A Prong 2 and Step 2B: A control structure of the hyperparameter obtaining code includes a conditional branch amounts to mere instructions for applying the abstract ideas on a generic computer under MPEP 2106.05(f) and a field of use and technological environment under MPEP 2106.05(h). The claim is not patent eligible.
Claim 28 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated.
Step 2A Prong 2 and Step 2B: The type of the second hyperparameter and the type of the provided first hyperparameter are a number of layer nodes and a number of layers, respectively, amounts to a field of use and technological environment under MPEP 2106.05(h). The claim is not patent eligible.
Claim 29 recites a hyperparameter tuning device comprising processors which implements the same features as the method of claim 28 and is therefore rejected for at least the same reasons. The claim is not patent eligible.
Claim 30 recites a hyperparameter tuning system which implements the same features as the method of claim 1 and is therefore rejected for at least the same reasons.
In Step 2A Prong 2 and Step 2B, one or more memories and one or more processors amounts to generic computer components for applying the abstract ideas on a generic computer under MPEP 2106.05(f). The claim is not patent eligible.
Claim 31 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated. Defining at least a first type and a second type for the second hyperparameter corresponding respectively to the first candidate and the second candidate for the first hyperparameter and a range of a value for each of the first type and the second type for the second hyperparameter is a judgment mental process which can reasonably be performed in the human mind with the aid of pencil and paper.
Step 2A Prong 2 and Step 2B: A hyperparameter tuning program for the hyperparameter tuning method being executed by the one or more processors amounts to mere instructions to apply the abstract ideas on a generic computer under MPEP 2106.05(f).
The hyperparameter obtaining code amounts to mere instructions to apply the abstract ideas on a generic computer under MPEP 2106.05(f).
A control structure of the hyperparameter obtaining code causes the user program to generate the second request based on the first hyperparameter to send the generated request to the hyperparameter tuning program amounts to mere instructions to apply the abstract ideas on a generic computer under MPEP 2106.05(f) and a field of use and technological environment under MPEP 2106.05(h). The claim is not patent eligible.
Claim 32 recites a hyperparameter tuning device comprising processors which implements the same features as the method of claim 31 and is therefore rejected for at least the same reasons.
Claim 33 incorporates the rejection of claim 1.
Step 2A Prong 1: The abstract ideas of claim 1 are incorporated.
Step 2A Prong 2 and Step 2B: Providing, to the user
Receiving, from the user
Step 2A Prong 2 and Step 2B: The user program amounts to mere instructions to apply the abstract ideas on a generic computer under MPEP 2106.05(f).
The hyperparameter obtaining code written in the user program for training the machine learning model amounts to mere instructions to apply the abstract ideas on a generic computer under MPEP 2106.05(f) and a field of use and technological environment under MPEP 2106.05(h). The claim is not patent eligible.
Claim 34 incorporates the rejection of claim 33.
Step 2A Prong 1: The abstract ideas of claim 33 are incorporated. The user on receiving the second candidate as the first hyperparameter is a method of organizing human activity. The sub-grouping “managing personal behavior or relationships or interactions between people” includes a human teacher teaching a human student. The student may generate the second request to obtain the second hyperparameter from the teacher based on receiving, from the teacher, either the first candidate or the second candidate as the first hyperparameter.
Step 2A Prong 2 and Step 2B: A control structure of the hyperparameter obtaining code amounts to mere instructions to apply the abstract ideas on a generic computer under MPEP 2106.05(f) and a field of use and technological environment under MPEP 2106.05(h).
The user program amounts to mere instructions to apply the abstract ideas on a generic computer under MPEP 2106.05(f). The claim is not patent eligible.
Examiner’s Note
No prior art rejection has been provided for pending claims 1, 19, and 30. The features of a hyperparameter tuning method executed by one or more processors, comprising: generating, by a user program, a first hyperparameter obtaining request for a first hyperparameter according to a hyperparameter obtaining code written in the user program written by using a machine learning library for training a machine learning model, and providing, by the user program, the generated first hyperparameter obtaining request to a hyperparameter tuning program, the first hyperparameter obtaining request specifying a plurality of candidates for the first hyperparameter, the plurality of candidates being written in the hyperparameter obtaining code in the user program; receiving, by the hyperparameter tuning program, from the user program, the first hyperparameter obtaining request; selecting, by the hyperparameter tuning program, a first candidate from among the plurality of candidates included in the first hyperparameter obtaining request received from the user program, as the first hyperparameter to be provided to the user program; providing, by the hyperparameter tuning program, to the user program, the selected first candidate as the first hyperparameter; receiving, by the user program, the selected first candidate from the hyperparameter tuning program; generating, by the user program, a second hyperparameter obtaining request for a second hyperparameter, based on the selected first candidate for the first hyperparameter, according to the hyperparameter obtaining code, and providing, by the user program, the generated second hyperparameter obtaining request to the hyperparameter tuning program, a type of the second hyperparameter specified in the second hyperparameter obtaining request being different from a type of the first hyperparameter and being specific to the selected first candidate; receiving, by the hyperparameter tuning program, from the user program, the second hyperparameter obtaining request; providing, by the hyperparameter tuning program, the second hyperparameter specific to the selected first candidate to the user program; and training, by the user program, the machine learning model by applying a set of the provided first hyperparameter and the provided second hyperparameter, when taken in the context of the claim as a whole, were not uncovered in the prior art of record.
Response to Arguments
Below are Examiner’s responses to Applicant’s arguments filed 02/24/2026.
Applicant’s First Argument Under 35 U.S.C. 101: On pages 13-14, the Applicant argues the claimed invention is not merely an exchange of information; it is a specific software architecture where the user program itself contains the logic to dynamically generate subsequent requests based on the values returned by the hyperparameter tuning program. Therefore, claim 1 does not recite an abstract idea.
Examiner’s Response: Applicant's arguments have been fully considered but they are not persuasive. Claim 1 recites a method in which a user program sends candidates for a first hyperparameter for a hyperparameter tuning program to select, and based on the selected first hyperparameter, the user program sends candidates for a second hyperparameter for a hyperparameter tuning program to select. This is a method of organizing human activity. The sub-grouping “managing personal behavior or relationships or interactions between people” includes a teacher teaching a student. The “user” is analogous to a student and a “hyperparameter tuning” module is analogous to a teacher in the scenario of a teacher teaching a student.
The technical improvement of claim 1 appears to be logic to dynamically adjust a request based on the previously returned values by using conditional statements (e.g., “if-else” statements). A student can dynamically adjust a request for candidates for the second hyperparameter that are relevant to the first hyperparameters based on a teacher’s selection of the first hyperparameter. Following specification paragraphs [0010], [0041], types of machine learning models include “neural network” and “random forest”, a hyperparameter specific to a neural network includes a number of neural network layers, and a hyperparameter specific to a random forest includes a maximum depth (of trees). A student can request a teacher to select a type of machine learning model from the choices “neural network” and “random forest”. Based on the type of model the teacher selects, it is reasonable for a student to request hyperparameters specific to the selected machine learning model rather than the other machine learning model. If the teacher selects “neural network”, it is reasonable for the student to request the teacher to select a number of neural network layers rather than a maximum depth of trees because a neural network does not include trees. Thus, the student can dynamically adjust the type of request.
Providing the first request and the second request is a judicial exception. This feature alone cannot provide a technical improvement. MPEP 2106.05(a) states, “It is important to note, the judicial exception alone cannot provide the improvement.” MPEP 2106.05(a), II. states, “it is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology.”
Applicant’s Second Argument Under 35 U.S.C. 101: On pages 14-15, Applicant argues claim 1 enables dynamic hyperparameter tuning to be performed simply by writing the hyperparameter obtaining code in the user program, without the need for any modification to the hyperparameter tuning program. The additional elements provide a specific improvement in the program maintenance, and thus claim 1 as a whole integrates the alleged abstract idea into a practical application. Therefore, amended claim 1 is patent eligible.
Examiner’s Response: Applicant's arguments have been fully considered but they are not persuasive. Applicant appears to argue the hyperparameter tuning program is improved because the user program eliminates irrelevant hyperparameter candidate via conditional statements. Examiner respectfully disagrees that this provides a technical improvement. Generating code that comprises a conditional statement and executing the code to follow the conditional statement amounts to mere instructions for applying the abstract ideas on a generic computer under MPEP 2106.05(f).
Specifically, the feature of generating, by a user program, a first hyperparameter obtaining request for a first hyperparameter according to a hyperparameter obtaining code written in the user program written by using a machine learning library for training a machine learning model, … the plurality of candidates being written in the hyperparameter obtaining code in the user program amounts to mere instructions for applying the abstract ideas on a generic computer under MPEP 2106.05(f) and a field of use and technological environment under MPEP 2106.05(h).
A hyperparameter tuning program amounts to mere instructions for applying the abstract ideas on a generic computer under MPEP 2106.05(f).
Generating, by the user program, a second hyperparameter obtaining request for a second hyperparameter, based on the selected first candidate for the first hyperparameter, according to the hyperparameter obtaining code amounts to mere instructions for applying the abstract ideas on a generic computer under MPEP 2106.05(f) and a field of use and technological environment under MPEP 2106.05(h).
The additional elements as disclosed above, alone or in combination, do not integrate the abstract ideas into a practical application as they are generic computer functions as disclosed in combination with a mere field of use that are implemented to perform the abstract ideas disclosed above. The claim is directed to an abstract idea. The additional elements as disclosed above, in combination with the abstract ideas, are not sufficient to amount to significantly more than the abstract ideas as they are generic computer functions as disclosed in combination with a mere field of use that are implemented to perform the abstract ideas disclosed above. The claim is not patent eligible.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Asher H. Jablon whose telephone number is (571)270-7648. The examiner can normally be reached Monday - Friday, 9:00 am - 6:00 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Abdullah Al Kawsar can be reached at (571)270-3169. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/A.H.J./Examiner, Art Unit 2127
/ABDULLAH AL KAWSAR/Supervisory Patent Examiner, Art Unit 2127
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