DETAILED ACTION
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 7/26/2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 claims at issue 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); and 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 a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO internet Web site contains terminal disclaimer forms which may be used. Please visit http://www.uspto.gov/forms/. The filing date of the application will determine what form should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1, 3-5, 9, and 17 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over Claims 1-4 and 19 of U.S. Patent 11,030,523. Although the claims at issue are not identical, they are not patentably distinct from each other because aside from a few minor differences, these claims contain the same limitations and perform the same functions.
Allowable Subject Matter
Claims 1-20 would be in condition for allowance if the Double Patenting rejection was obviated for Claims 1, 3-5, 9, and 17.
The following is an examiner’s statement of reasons for allowance:
Regarding Claims 1, 9, and 17, the closest prior art of record, Andreas ("Learning to Compose Neural Networks for Question Answering", https://arxiv.org/pdf/1601.01705v3.pdf, arXiv: 1601.01605v4 [cs.CL] 7 June 2016, pp. 1-10) (Year: 2016), Young et al ("Optimizing Deep Learning Hyper-Parameters Through an Evolutionary Algorithm", MLH PC2015, November 15-20, 2015, Austin, Tx, pp. 2-15) (Year: 2015), He et al. ("identity Mappings in Deep Residual Networks", https://arxiv.org/abs/1603.05027, arXiv:1603.05027v3 [cs.CV] 25 July 2016, pp. 1-15 (Year: 2016), and Jozefowicz et al ("An Empirical Exploration of Recurrent Network, Architectures", 32nd International Conference on Machine Learning, Lille France, 6-11 July, 2015, pp. 1-9) (Year: 2015) teaches A method performed by one or more computers, comprising: determining, using a controller, a plurality of respective architectures of a child neural network that is configured to perform a particular neural network task; for each respective architecture in the plurality of respective architectures: to perform the particular neural network task; and after the training, determining, based on evaluating a performance of the trained instance of the child neural network, a performance metric for the trained instance of the child neural network on the particular neural network task; and using the performance metrics for the trained instances of the child neural network to adjust the controller.
However, the references do not explicitly teach nor suggest in detail, training an instance of the child neural network having the respective architecture on training data that includes a plurality of training inputs each associated with a respective target training output using validation data that includes one or more different training inputs than the training data in view of other limitations of the intervening claims.
Thus the prior arts of record taking singly or in combination do not teach or suggest the above-stated limitations taking wholly in combination with all the elements of each independent claim.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANDREW J STEINLE whose telephone number is (571)272-9923. The examiner can normally be reached M-F 10am-6pm CT.
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/ANDREW J STEINLE/Primary Examiner, Art Unit 2497