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 .
This action is responsive to the application filed on February 29th, 2024. Claims 1-20 are pending in the case. Claims 1, 9, and 11 are independent claims.
The preliminary amendment filed March 27th, 2024, has been accepted and the amendments to the Abstract, Specification, and Claims have been entered.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on January 9th, 2025 and January 8th, 2026 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
Claim Objections
Claims 1 and 11 are objected to because of the following informalities: “in first duration” should be “in a first duration”. Appropriate correction is required.
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 2 and 17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 2:
Step 1: Claim 2 is directed to a method, therefore it falls under the statuary category of a process.
.Step 2A Prong 1: The claim recites, in part:
“discarding the N pieces of first information of the N local models, or skipping using the N pieces of first information of the N local models to update the global model” This limitation is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion), in this case observations and evaluation. See MPEP § 2106.04(a)(2)(III).
Step 2A Prong 2: The judicial exception is not integrated into a practical application; the remaining limitations of the claim are as follows:
“receiving M pieces of first information of M local models from M terminal devices, wherein the M terminal devices one-to-one correspond to the M local models, the M local models one-to-one correspond to the M pieces of first information, the M pieces of first information of the M local models are information received in first duration, and M is a positive integer” (claim 1), “sending first information of a global model to K terminal devices, wherein K is a positive integer, the first information of the global model is information obtained after the global model is updated, and the M pieces of first information of the M local models are used to update the global model” (claim 1), “receiving N pieces of first information of N local models, wherein the N pieces of first information of the N local models are information received beyond the first duration, and N is a positive integer” the limitation is an additional element that amounts to adding insignificant extra-solution activity to the judicial exception. See MPEP § 2106.05(g).
Step 2B: The additional elements, taken individually and in combination, do not provide an inventive concept of significantly more than the abstract idea itself for the reasons set forth in step 2A prong 2 above. Further, “receiving M pieces of first information of M local models from M terminal devices, wherein the M terminal devices one-to-one correspond to the M local models, the M local models one-to-one correspond to the M pieces of first information, the M pieces of first information of the M local models are information received in first duration, and M is a positive integer” (claim 1), “sending first information of a global model to K terminal devices, wherein K is a positive integer, the first information of the global model is information obtained after the global model is updated, and the M pieces of first information of the M local models are used to update the global model” (claim 1), “receiving N pieces of first information of N local models, wherein the N pieces of first information of the N local models are information received beyond the first duration, and N is a positive integer” the limitation is an additional element that amounts to adding insignificant extra-solution activity to the judicial exception. See MPEP § 2106.05(g).
Furthermore the additional element is directed to receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d. Therefore, the claim is ineligible.
Regarding claim 17:
Step 1: Claim 17 is directed to a method, therefore it falls under the statuary category of a process.
Step 2A Prong 1: The claim recites, in part:
“determining that a value of a fourth parameter falls within a first range, wherein the first range corresponds to the global model; determining that a difference between the value of the fourth parameter and a first value is less than or equal to a first threshold, wherein the first value corresponds to the global model; or determining, based on a classification network, that a first terminal device belongs to a first class, wherein the first class is applicable to the global model.” This limitation is the abstract idea of a mental process that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper (including an observation, evaluation, judgment, opinion), in this case observations and evaluation. See MPEP § 2106.04(a)(2)(III).
Step 2A Prong 2: The judicial exception is not integrated into a practical application; the remaining limitations of the claim are as follows:
“receiving M pieces of first information of M local models from M terminal devices, wherein the M terminal devices one-to-one correspond to the M local models, the M local models one-to-one correspond to the M pieces of first information, the M pieces of first information of the M local models are information received in first duration, and M is a positive integer” (claim 1), “sending first information of a global model to K terminal devices, wherein K is a positive integer, the first information of the global model is information obtained after the global model is updated, and the M pieces of first information of the M local models are used to update the global model” (claim 1), the limitation is an additional element that amounts to adding insignificant extra-solution activity to the judicial exception. See MPEP § 2106.05(g).
Step 2B: The additional elements, taken individually and in combination, do not provide an inventive concept of significantly more than the abstract idea itself for the reasons set forth in step 2A prong 2 above. Further, “receiving M pieces of first information of M local models from M terminal devices, wherein the M terminal devices one-to-one correspond to the M local models, the M local models one-to-one correspond to the M pieces of first information, the M pieces of first information of the M local models are information received in first duration, and M is a positive integer” (claim 1), “sending first information of a global model to K terminal devices, wherein K is a positive integer, the first information of the global model is information obtained after the global model is updated, and the M pieces of first information of the M local models are used to update the global model” (claim 1), the limitation is an additional element that amounts to adding insignificant extra-solution activity to the judicial exception. See MPEP § 2106.05(g).
Furthermore the additional element is directed to receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d. Therefore, the claim is ineligible.
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.
Claims 1, 3-8, 11-16 and 18-19 are rejected under 35 U.S.C. § 102(a)(1) as being anticipated by Zhang et al. (CN 107944566 B) (as cited in the IDS, hereinafter “Zhang”).
Regarding claim 1:
Zhang teaches [a] method, comprising:
receiving M pieces of first information of M local models from M terminal devices, wherein the M terminal devices one-to-one correspond to the M local models, the M local models one-to-one correspond to the M pieces of first information (Zhang, ¶83 “After receiving the training sub-results from each worker node participating in the parameter training process, the master node updates the global parameters based on the obtained training sub-results.” Here, each worker node corresponds one-to-one with each local model which corresponds one-to-one with the uploaded training sub-results), the M pieces of first information of the M local models are information received in first duration (Zhang, ¶121 “If training is not completed before the end time, it ends at the end time, obtains a training sub-result, and feeds the training sub-result back to the master node.” Here, the time before the end time can be considered the first duration), and M is a positive integer (Zhang, ¶83 “After receiving the training sub-results from each worker node participating in the parameter training process, the master node updates the global parameters based on the obtained training sub-results.” Here, M, the number of worker nodes, models and model information, is inherently a positive integer); and
sending first information of a global model to K terminal devices, wherein K is a positive integer (Zhang, ¶133 “The master node determines the first difference between the first global parameter and the global parameter based on the first identification information and the second identification information of the global parameter stored locally, and sends the first difference to the working node;”), the first information of the global model is information obtained after the global model is updated (Zhang, ¶26 “Read the latest global model parameters from the parameter server as the initial local model parameters…” here, the latest global model parameters can be considered obtained after the global model is updated ), and the M pieces of first information of the M local models are used to update the global model (Zhang, ¶131 “After receiving the training sub-results from each worker node participating in the parameter training process, the master node updates the global parameters based on the obtained training sub-results.”).
Regarding claim 3:
Zhang teaches [t]he method according to claim 1, wherein a start moment of the first duration is the H1th time unit after a time unit in which second information of the global model is sent last time starts or a time unit in which training of the global model starts, a length of the first duration is H2 time units, H1 is greater than or equal to 0, and H2 is greater than 0 (Zhang, ¶172 “Then, the master node starts a parameter training process at fixed intervals, waiting for worker nodes to join and train.” Here, each fixed interval can be considered a time duration, and each time interval is an interval greater than 0).
Regarding claim 4:
Zhang teaches [t]he method according to claim 3, wherein H1 or H2 is predefined or preconfigured Zhang, ¶172 “Then, the master node starts a parameter training process at fixed intervals, waiting for worker nodes to join and train.” Here, the fixed intervals can be considered the predefined H1 or H2).
Regarding claim 5:
Zhang teaches [t]he method according to claim 1, wherein first information of a first local model in the M pieces of first information of the M local models is from a first terminal device in the M terminal devices, wherein the first information of the first local model indicates parameter information of the first local model; or the first information of the first local model indicates a difference between the parameter information of the first local model and first parameter information, and the first parameter information is parameter information that is of the global model and that is indicated to the first terminal device last time or parameter information of the global model before the global model is updated (Zhang, ¶18 “Based on the first identification information and the second identification information of the locally stored global parameters, a first difference portion between the first global parameters and the global parameters is determined;” It is noted the claim recites alternative language, and Zhang teaches at least one of the alternatives.).
Regarding claim 6:
Zhang teaches [t]he method according to claim 1, wherein the first information of the global model indicates parameter information of the global model; or the first information of the global model indicates a difference between current parameter information of the global model and the first parameter information, and the first parameter information is parameter information that is of the global model and that is indicated last time or parameter information of the global model before the global model is updated (Zhang, ¶85 “The master node determines the first difference between the first global parameter and the global parameter based on the first identification information and the second identification information of the global parameter stored locally, and sends the first difference to the working node;” It is noted the claim recites alternative language, and Zhang teaches at least one of the alternatives.).
Regarding claim 7:
Zhang teaches [t]he method according to claim 1, wherein the K terminal devices are comprised in one terminal device group (Zhang, ¶46 “The first determining module is used to start the parameter training process and determine the working nodes to be added to the parameter training process.” Here the working nodes in the training process can be considered a one terminal device group).
Regarding claim 8:
Zhang teaches [t]he method according to claim 7, wherein values of fourth parameters corresponding to terminal devices comprised in the terminal device group all fall within a first range, and the first range corresponds to the global model; or a difference between a value of a fourth parameter corresponding to a terminal device comprised in the terminal device group and a first value is less than or equal to a first threshold, and the first value corresponds to the global model (Zhang, ¶139 “The master node allows worker nodes to join the parameter training process under the default condition that the memory usage of the worker nodes must be less than 30%.” Here, the memory usage of each worker node can be considered the fourth parameter, and less than 30% usage can be considered a difference between the resources usage of the model on the worker node, and that of the global model. It is noted the claim recites alternative language, and Zhang teaches at least one of the alternatives.).
Regarding claim 11:
Zhang teaches [a] method, comprising:
performing training by using a global model, to obtain first information of a first local model (Zhang, “Parameter training is performed based on the global parameters to obtain the training result parameters;”);
sending the first information of the first local model to an access network device in first duration (Zhang, ¶47 “A sending module is used to send time information corresponding to the parameter training process to the working node, wherein the time information includes the end time of the parameter training process, so that the working node sends the training sub-results to the master node before the end time;” here, the training sub-results can be considered the first information, and sending the results before the end time can be considered sending the information within a first duration);
and
receiving first information of the global model from the access network device, wherein the first information of the global model is information obtained after the global model is updated (Zhang, ¶130 “The system receives a first difference portion sent by the master node, and restores the global parameters based on the first difference portion and the first global parameters.” here, the first difference portion can be considered the first information, and they can be considered obtained after the global model is updated because they’re the difference between the currently stored global model and the updated global model).
Regarding claims 12-16:
Claims 12-16 are rejected under the same rationale as claims 3-6 and 8, respectively.
Regarding claim 18:
Zhang teaches [t]he method according to claim 1, wherein first information of a first local model in the M pieces of first information of the M local models is from a first terminal device in the M terminal devices, the first information of the first local model indicates a difference between the parameter information of the first local model and first parameter information, and the first parameter information is parameter information of the global model that indicates to the first terminal device a last time or parameter information of the global model before the global model is updated (Zhang, ¶18 “Based on the first identification information and the second identification information of the locally stored global parameters, a first difference portion between the first global parameters and the global parameters is determined;”).
Regarding claim 19:
Zhang teaches [t]he method according to claim 1, wherein the first information of the global model indicates a difference between current parameter information of the global model and the first parameter information, and the first parameter information is parameter information of the global model that indicates to the first terminal device a last time or parameter information of the global model before the global model is updated (ref 1, ¶134 “The version number of the first global parameter saved by worker node A is V810, indicating 07-07-2026 - Page 60 that the version of the global parameter saved in worker node A is not much different from the version of the global parameter saved by the master node. The master node determines the difference DA between the global parameter in version V811 and the global parameter in version V810, and sends the difference DA to worker node A. Worker node A can restore the latest version of the global parameter in the master node, namely the global parameter in version V811, based on the global parameter in version V810 stored locally and the difference DA.”).
Claims 9 and 10 are rejected under 35 U.S.C. § 102(a)(1) as being anticipated by Yu et al. (CN 111444021 B) (as cited in the IDS, hereinafter “Yu”).
Regarding claim 9:
Yu teaches [a] method comprising:
receiving M pieces of first information of M local models from M terminal devices, wherein the M terminal devices one-to-one correspond to the M local models, the M local models one-to-one correspond to the M pieces of first information (Yu, “In step A2, global model parameters are sent to the computing servers of all participating institutions, and model updates output by the computing servers using the synchronous training method for computing servers are received.” Here, the computing servers can be considered the terminal devices which correspond one-to-one with the local models and model information), first information of each local model corresponds to a first counter, and a value of each first counter matches a value of a second counter (Yu, ¶64 “Then, the global training round number of the current computing server and the timestamp of the last local update are updated in the state database using the node status in the received status report message;” here, the two round numbers can be considered the matching counters); and
sending first information of a global model to K terminal devices, wherein K is a positive integer, the first information of the global model is information obtained after the global model is updated, the M pieces of first information of the M local models are used to update the global model (Yu, “In step A2, global model parameters are sent to the computing servers of all participating institutions, and model updates output by the computing servers using the synchronous training method for computing servers are received.” here, the global model parameters can be considered the first information of the M models obtained after the global model is updated, and are used to update the model), and the second counter is a counter corresponding to the global model (Yu, ¶64 “Then, the global training round number of the current computing server and the timestamp of the last local update are updated in the state database using the node status in the received status report message;”).
Regarding claim 10:
Yu teaches [t]he method according to claim 9, wherein the first information of the global model indicates parameter information of the global model; or the first information of the global model indicates a difference between second parameter information of the global model and first parameter information, and the first parameter information is parameter information that is of the global model and that is indicated last time or parameter information of the global model before the global model is updated (Yu, “In step A2, global model parameters are sent to the computing servers of all participating institutions, and model updates output by the computing servers using the synchronous training method for computing servers are received.” It is noted the claim recites alternative language, and Yu teaches at least one of the alternatives.).
Claim Rejections - 35 USC § 103
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 2 is rejected under 35 U.S.C. § 103 as being unpatentable over Zhang in view of Nishio et al. ("Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge", Nishio et al., 30 Oct 2018) (hereinafter "Nishio").
Regarding claim 2:
Zhang teaches [t]he method according to claim 1, further comprising:
Zhang does not teach "receiving N pieces of first information of N local models, wherein the N pieces of first information of the N local models are information received beyond the first duration, and N is a positive integer; and discarding the N pieces of first information of the N local models, or skipping using the N pieces of first information of the N local models to update the global model"
However, Nishio teaches receiving N pieces of first information of N local models, wherein the N pieces of first information of the N local models are information received beyond the first duration, and N is a positive integer; and discarding the N pieces of first information of the N local models, or skipping using the N pieces of first information of the N local models to update the global model (Nishio, page, section D, col 1 “The updates completed after the deadline were just discarded and not aggregated.” Here, the updates completed after the deadline can be considered the N pieces of local information of the N models that is discarded after being received beyond a first duration. It is noted the claim recites alternative language, and Zhang in view of Nishio teaches at least one of the alternatives.).
Zhang and Nishio are analogous art because both references concern methods for federated learning. Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Zhang’s federated learning system to incorporate the discarded updates taught by Nishio. The motivation for doing so would have been to achieve more clients per round with higher accuracy and efficiency as stated in Nishio, page 6, section E, col 1-2, ¶1 “We also found that FedCS achieved a higher classification accuracy than FedLim after the final deadline (“Accuracy” column in the table) than FedLim especially on CIFAR-10. These results indicate the improved efficiency of FedCS over FedLim in terms of the training progress. One reason for the improvement is because FedCS was able to incorporate much more clients into each training round: 7.7 clients for each FedCS while only 3.3 clients for FedLim, on average when Tround=3.”.
Claims 17 and 20 are rejected under 35 U.S.C. § 103 as being unpatentable over Zhang in view of Wu et al. ("SAFA: ASemi-Asynchronous Protocol for Fast Federated Learning With Low Overhead", Wu et al., 7 Apr. 2021) (hereinafter "Wu").
Regarding claim 17:
Zhang teaches [t]he method according to claim 1, further comprising:
Zhang does not teach "receiving N pieces of first information of N local models, wherein the N pieces of first information of the N local models are information received beyond the first duration, and N is a positive integer; and using the N pieces of first information of the N local models to update the global model"
However, Wu teaches receiving N pieces of first information of N local models, wherein the N pieces of first information of the N local models are information received beyond the first duration, and N is a positive integer; and using the N pieces of first information of the N local models to update the global model (Wu, page 4, col 2, ¶3 “The results of undrafted clients will not be merged into the global model in the upcoming aggregation step, but may take effect in future rounds via a bypass structure (squares with dashed lines) that saves these updates temporarily.”).
Zhang and Wu are analogous art because both references concern methods for federated learning. Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Zhang’s federated learning system to incorporate the updating in a future round taught by Wu. The motivation for doing so would have been to achieve faster federated learning as stating in Wu, pages 3-4, col 2-1, section 3.1, ¶2 “The key idea is to develop a better way to get the stragglers (i.e., clients with stale models) involved in the model aggregation and leverage their progress for faster federated learning.”.
Regarding claim 20:
Zhang teaches [t]he method according to claim 7,
Zhang does not teach "wherein a difference between a value of a fourth parameter corresponding to a terminal device comprised in the terminal device group and a first value is less than or equal to a first threshold and the first value corresponds to the global model"
However, Wu teaches wherein a difference between a value of a fourth parameter corresponding to a terminal device comprised in the terminal device group and a first value is less than or equal to a first threshold and the first value corresponds to the global model (Wu, page 4, col 2, ¶4 “To decide whether a local update should be accepted, here we adopt a simple criterion based on the difference between the versions of the global model and the local model, which is called lag tolerance.” Here, the lag tolerance can be considered the first threshold).
Zhang and Wu are analogous art because both references concern methods for federated learning. Accordingly, it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to modify Zhang’s federated learning system to incorporate the updating in a future round taught by Wu. The motivation for doing so would have been to achieve faster federated learning as stating in Wu, pages 3-4, col 2-1, section 3.1, ¶2 “The key idea is to develop a better way to get the stragglers (i.e., clients with stale models) involved in the model aggregation and leverage their progress for faster federated learning.”.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Wang et al. ("A Novel Reputation-aware Client Selection Scheme for Federated Learning within Mobile Environments", Wang et al., 2020) discloses an alternate strategy that builds on the Federated Learning (FL) concept, to keep the training data on distributed mobile devices, and trains a shared model by aggregating updated local models using an optimal user selection method for the federated learning environment based on reputation scores.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JACOB Z SUSSMAN MOSS whose telephone number is (571) 272-1579. The examiner can normally be reached Monday - Friday, 9 a.m. - 5 p.m. ET.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kakali Chaki can be reached on (571) 272-3719. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/J.S.M./Examiner, Art Unit 2122
/KAKALI CHAKI/Supervisory Patent Examiner, Art Unit 2122
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