DETAILED ACTION
Status of the Claims
Original claims 1-20 are pending.
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
The following title is suggested: INFLUENCE-BASED HYPERPARAMETER DETERMINATION FOR IMAGE PROCESSING MACHINE LEARNING MODELS.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
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Claims 1-20 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of copending Application No. 18/821,829 in view of ‘Schioppa’ (“Scaling Up Influence Functions,” 2022). This is a provisional nonstatutory double patenting rejection.
Claims 1-20 of the instant application are substantially the same as claims 1-20, respectively, of the co-pending application. The claims of both applications describe determining an influence of a reference dataset on a loss for updating a model, determining a hyperparameter based on the influence, and updating the model based on the hyperparameter, the loss, and the reference dataset. The only difference is that the instant application uses the hyperparameter determination for updating an image model, while the co-pending application updates a language model. The image model of the instant application is trained with reference samples that are images and performs image processing tasks such as image classification, image analysis, image enhancement, image segmentation, object detection, image style conversion, and/or image generation. The language model of the co-pending application is trained with reference samples that are text and performs language processing tasks such as content rewriting, content analysis, text summarization, translation, question answering, text style conversion, sentiment analysis, and/or text classification.
Like the claimed inventions of the instant application and the co-pending application, Schioppa teaches techniques for determining an influence of a reference dataset on a loss for updating a model (e.g., Equation 1 and supporting text describe the basic influence formulation). The techniques that Schioppa uses to calculate the influence are at least similar to the techniques described in the claimed invention, such as determination of the influence (Eqn. 1,
I
H
) based on an eigenvalue related to a reference matrix (Eqn. 1, Hessian matrix
H
is a reference matrix that is inverted to find the influence
I
H
; e.g., Section 1, 3rd paragraph, “we use Arnoldi iteration (Arnoldi 1951) to find the dominant (in absolute value) eigenvalues of
H
… and then cheaply invert the diagonalized
H
”) (claims 2).
Schioppa further teaches that its influence determination techniques are not specific to only image models or text/language models, but rather that they can be applied more generally to both types of models. Specifically, Sections 5.1 and 5.3 describe experiments successfully applying influence determination to image models, while Section 5.2 describes experiments successfully applying influence determination to text/language models.
Schioppa’s teachings would have suggested to one of ordinary skill in the art that the influence-based hyperparameter determination described in the claims of the co-pending application would also be applicable to other types of machine learning models, such as image models, and that application to image models would have a reasonable expectation of success.
Therefore, claims 1-20 of the instant application are obvious variants of claims 1-20, respectively, of the co-pending application.
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, 10, 11, 19, and 20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by ‘Lee’ (US 2020/0125945 A1).
Regarding claim 1, Lee discloses a method for image processing (e.g., Fig. 1), comprising:
obtaining a reference dataset that comprises a plurality of reference samples (e.g., [0033], Fig. 1, set of user images 100,110 and corresponding truth data 102,112), a reference sample in the plurality of reference samples comprising: a reference image (i.e., one of images 100,110) and a reference label corresponding to the reference image (i.e., one of truth data 102,112), the reference label indicating a processing result of the image processing (i.e., a true output of processing the corresponding image);
determining an influence of the reference dataset on a loss for updating an image model associated with the image processing based on the plurality reference samples ([0037]-[0038], Fig. 2, deep quantifiers 210 quantify model matching closeness – i.e., the influence of the reference dataset on a loss such as “the standard error rates estimated between the initial truth data 102 and the model applied images 204”; I.e., the reference dataset influences the loss to be higher when the reference dataset doesn’t closely match the training images for the reference model, and vice versa), the image model representing an association relationship between an image and a processing result of the image processing (i.e., an image is the input of the model and a processing result is the output of the model);
determining a hyperparameter for updating the image model based on the influence of the reference dataset (e.g., [0039], Fig. 2, salient hyper-parameter prediction 214 is performed using initial deep quantifiers 210); and
updating the image model based on the hyperparameter, the loss, and the plurality of reference samples (e.g., [0039]-[0040], [0033], Fig. 1).
Regarding claim 10, Lee discloses the method of claim 1, wherein the image processing comprises any of: image classification, image analysis, image enhancement, image segmentation, object detection, image style conversation, and image generation ([0034]).
Regarding claim 11, Examiner notes that the claim recites an electronic device, comprising a computer processor coupled to a computer-readable memory unit, the memory unit comprising instructions that when executed by the computer processor implements a method that is substantially the same as the method of claim 1.
Lee discloses the method of claim 1 (see above).
Lee further discloses implementing its method as an electronic device, comprising a computer processor coupled to a computer-readable memory unit, the memory unit comprising instructions that when executed by the computer processor implements the method (e.g., [0033]).
Accordingly, claim 11 is also rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lee for substantially the same reasons as claim 1.
Regarding claim 19, Examiner notes that the claim recites limitations that are substantially the same as limitations of claim 10. Lee discloses the invention of claim 10 (see above). Accordingly, claim 19 is also rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lee for substantially the same reasons as claim 10.
Regarding claim 20, Examiner notes that the claim recites non-transitory computer program product, the non-transitory computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by an electronic device to cause the electronic device to perform a method that is substantially the same as the method of claim 1.
Lee discloses the method of claim 1 (see above).
Lee further discloses implementing its method as non-transitory computer program product, the non-transitory computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by an electronic device to cause the electronic device to perform the method (e.g., [0033]).
Accordingly, claim 20 is also rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lee for substantially the same reasons as claim 1.
Allowable Subject Matter
Claims 2-9 and 12-18 are not rejected over prior art. However, they are rejected for double patenting and thus are not in condition for allowance at this time. Note that even though the double patenting rejection is provisional, it will be maintained until it is overcome. See MPEP 804, Subsection I.B.1.(b).(ii).
Conclusion
The following prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
‘Cheng’ (Influence Function Based Second-Order Channel Pruning: Evaluating True Loss Changes for Pruning is Possible Without Retraining,” 18 June 2024)
Determines influence of each channel on loss function and uses this to prune less-influential channels, the number of channels being a type of hyperparameter
‘Anonymous’ (“Gradient-based Hyperparameter Optimization without Validation Data for Learning from Limited Labels,” 2021)
Optimizes hyperparameters by maximizing a marginal likelihood
p
D
|
ϕ
, with
D
being a reference dataset and
ϕ
being the hyperparameters
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/GEOFFREY E SUMMERS/Examiner, Art Unit 2669
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