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 11/13/2023, 09/27/2024, 02/12/2025, 06/16/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Election/Restrictions
Applicant’s election without traverse of Group I (claims 1-15) in the reply filed on 01/09/2026 is acknowledged.
35 USC § 101
Claim 8 is directed to “a computer readable medium”, the specification filed on 11/13/2023 discloses in ¶ [0125] “A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire.” Therefore, the claim is considered eligible.
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.
Claim(s) 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The limitations, under their broadest reasonable interpretation, cover mental process (concept performed in a human mind, including as observation, evaluation, judgment, opinion, organizing human activity and mathematical concepts and calculations). This judicial exception is not integrated into a practical application because the steps do not add meaningful limitations to be considered specifically applied to a particular technological problem to be solved .The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the steps of the claimed invention are directed to Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations and d no additional features in the claims would preclude them from being performed as such except for the generic computer elements at high level of generality (i.e., processor, memory).
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that claims 1 and 9 are directed to an abstract idea as shown below:
STEP 1: Do the claims fall within one of the statutory categories?
YES
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?
YES
The claims are directed toward mathematical concepts, mathematical relationships, mathematical formulas or equations, mathematical calculations (i.e. abstract idea).
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
The independent claims comprise a mental process and/or mathematical concepts that can be practicably performed in the human mind (or generic computers or components configured to perform the method) and, therefore, an abstract idea.
Regarding Claim(s) 1 and 9: the claims recite the steps (functions) of:
generating a feature representation from existing sources of datasets; generating representation of metric distances of the existing sources to each other using energy distance measure from the feature representation; generating feature representation of a target dataset; and generating representation of the metric distances of each of the target dataset using the energy distance measure (mathematical concepts, mathematical relationships, mathematical formulas or equations, mathematical calculations).
These limitations, as drafted, is a simple process that, under their broadest reasonable interpretation, covers performance of the limitations in the mind or by a human. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that “can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same).
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
NO
The claims do not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
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;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
These limitations are recited at a high level of generality (i.e. as a general action or change being taken based on the results of the acquiring step) and amounts to mere post solution actions, which is a form of insignificant extra-solution activity. Further, the claims are claimed generically and are operating in their ordinary capacity such that they do not use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
No
The claims do not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
Thus, since Claim(s) 1 and 9 are: (a) directed toward an abstract idea, (b) do not recite additional elements that integrate the judicial exception into a practical application, and (c) do not recite additional elements that amount to significantly more than the judicial exception.
Regarding claims 2-8 and 10-15: the additional limitations do not integrate the mathematical concepts into practical application or add significantly more.
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 and 8-9 are rejected under 35 U.S.C. 103 as being unpatentable over Watson (US 20190354850) in view of Betthauser (“Discovering Distribution Shifts using Latent Space Representations” Feb, 17, 2022).
Regarding claim 1:
Watson discloses: a method for measuring similarities between sets of feature vectors (FIG. 11), comprising:
generating a feature representation from existing sources of datasets (¶ [0094] discloses generating respective representation characterizing one or more source data sets, and see ¶ [0051] – ¶ [0053]);
generating representation of metric distances of the existing sources to each other (¶ [0095] discloses using one or more distance computation techniques regarding the first vector representation and/or the second vector representation to assess one or more similarity metrics between the one or more source data sets and/or the one or more sample data sets, and ¶ [0054] discloses the distance computing techniques) ;
generating feature representation of a target dataset (¶ [0094] discloses generating respective representation characterizing one or more sample data sets, and see ¶ [0051] – ¶ [0053]); and
generating representation of the metric distances of each of the target dataset (¶ [0095] discloses using one or more distance computation techniques regarding the first vector representation and/or the second vector representation to assess one or more similarity metrics between the one or more source data sets and/or the one or more sample data sets, ¶ [0054] discloses the distance computing techniques, and ¶ [0051] discloses the equation representing the distance D on aggregated feature representation of target data set ti and source data set sj);
Watson does not use energy distance, it lists examples such as KL-divergence, L2 distance, cosine similarity, Manhattan distance, Minkowski distance, Jaccard similarity, chi-square distance, a combination thereof, and/or the like.
However, in a related field, Betthauser teaches the use of energy distance (page 3, “3 approach”; “We assume we are given two sets of embeddings, X and Y of dimension d, generated by the same model based on two datasets”; page 4, “3.2 Distribution Shift Tests” “we compute pairwise distances between reference subsamples to estimate the range of distances to be considered “in-distribution”, page 5, Algorithm 2 and “3.3 Distance Metrics”; “Energy Distance is a nonparametric distribution distance metric [17], and is an instance of Maximum Mean Discrepancy with kernel equal to the negative Euclidean norm between elements. The function requires no assumptions or explicit functional form, and can be easily evaluated over collections of high-dimensional data, such as two sets of embeddings, X and Y”).
Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Watson to incorporate the teachings of Betthauser by including: using energy distance in order to obtain an alternative way of quantifying similarity between source and target datasets.
Regarding claim 8: the claim limitations are similar to those of claim 1; therefore, rejected in the same manner as applied above. Watson further discloses a system in FIGS. 1 and 2 and a crm in ¶ [0032].
Regarding claim 9: the claim limitations are similar to those of claim 1; therefore, rejected in the same manner as applied above. Watson further discloses a system in FIGS. 1 and 2.
Claim(s) 2-5 and 10-13 are rejected under 35 U.S.C. 103 as being unpatentable over Watson (US 20190354850) in view of Betthauser (“Discovering Distribution Shifts using Latent Space Representations” Feb, 17, 2022) and Kender (“A Geometric Approach for Generating Pseudo-labels that Improve Transfer Learning” July 7, 2022).
Regarding claim 2:
Watson in view of Betthauser teaches the limitations of claim 1 as applied above.
Watson in view of Betthauser does not specifically teach: providing a choice of existing sources which further extremizes a geometric content of a hypervolume described by a pseudolabel sequence.
However, in a related field, Kender teaches: providing a choice of existing sources which further extremizes a geometric content of a hypervolume described by a pseudolabel sequence (abstract; “We generate pseudo-labels according to an efficient and extensible algorithm that is based on a classical result from the geometry of high dimensions, the Cayley-Menger determinant. This G2L (“geometry to label”) method incrementally builds up pseudo-labels using a greedy computation of hypervolume content”; “1 Introduction”; “…. Our method creates pseudo-labels for this data by determining their geometric relationships to the feature space of existing labeled data… pseudo-labels are then constructed for the incoming datapoints based on these distances, or, more accurately, based on “contents”, which is the high-dimensional generalization of distances, calculated using a geometric approach. Each pseudo-label then consists of a sequence of semantically descriptive names: for example, ⟨tool,plant⟩”).
Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Watson and Betthauser to incorporate the teachings of Kender by including: providing a choice of existing sources which further extremizes a geometric content of a hypervolume described by a pseudolabel sequence in order to generate richer pseudo-labels for transfer learning targets from known source datasets.
Regarding claim 3:
Watson in view of Betthauser and Kender teaches the limitations of claim 2 as applied above.
Kender further teaches: repeating the providing of the choice until an empirically-determined stopping criterion is performed (abstract “method incrementally builds up pseudo-labels using a greedy computation of hypervolume content.”; “4.4 Empirical Properties of Pseudo-labels” and “4.3 Pseudo-label Creation”; “After a stopping criteria, this sequence gives the pseudo-label.:… The full G2L algorithm is summarized in Algorithm 1. The algorithm requires a number of hyperparameters that are set by experiment”).
Regarding claims 4 and 5:
Watson in view of Betthauser and Kender teaches the limitations of claims 2 and 3 as applied above.
Kender further teaches: further comprising repeating the providing of the choice using differing extremizing criteria (“4.3 Pseudo-label Creation”; “…the process repeats, and at each step the sequence is extended with the name of the anchor point that best extremizes the content—the area, volume, hyper volume, etc.— of the evolving polytope formed by these selected points… Extremizing policies. The extrema decision sequence Pol, and its summarizing notation, are best explained by a walkthrough of the algo rithm… The four choices of extremizing policy at any dimension are therefore captured by the quaternary alphabet {c,f,C,F}. And in particular, the policy ⟨C⟩ is the special case already explored in prior work [8], which forms pseudo-labels consisting of the names of ⟨closest, farthest⟩ pairs.”).
Regarding claims 10-13: the claim limitations are similar to those of claims 2-5; therefore, rejected in the same manner as applied above.
Claim(s) 7 is rejected under 35 U.S.C. 103 as being unpatentable over Watson (US 20190354850) in view of Betthauser (“Discovering Distribution Shifts using Latent Space Representations” Feb, 17, 2022) and Kender (“A Geometric Approach for Generating Pseudo-labels that Improve Transfer Learning” July 7, 2022), and Watson2 (US 20200082210).
Regarding claim 7:
Watson in view of Betthauser and Kender teaches the limitations of claim 2 as applied above.
, Betthauser teaches the use of energy distance (page 3, “3 approach”; “We assume we are given two sets of embeddings, X and Y of dimension d, generated by the same model based on two datasets”; page 4, “3.2 Distribution Shift Tests” “we compute pairwise distances between reference subsamples to estimate the range of distances to be considered “in-distribution”, page 5, Algorithm 2 and “3.3 Distance Metrics”; “Energy Distance is a nonparametric distribution distance metric [17], and is an instance of Maximum Mean Discrepancy with kernel equal to the negative Euclidean norm between elements. The function requires no assumptions or explicit functional form, and can be easily evaluated over collections of high-dimensional data, such as two sets of embeddings, X and Y”).
Watson in view of Betthauser and Kender does not specifically teach: further comprising outputting pseudo labeling.
However, in a related field, Watson2 teaches: further comprising outputting pseudo labeling (abstract, “…assigns pseudo-labels to unlabeled examples of data using a similarity metric on an embedding space to produce pseudo-labeled examples”; ¶ [0058] “At block 620, pseudo labels generated and assigned to unlabeled data. For instance, the individual dissimilarity scores are placed in a new vector (formed to hold a plurality of dissimilarity scores for each unlabeled element). The combined new vector and scores therein is the pseudo label for the unlabeled element.”; ¶ [0061] “At block 630, a final model is outputted.”).
Therefore, it would have been obvious to a person of ordinary skill in the art prior to the effective filing date of the claimed invention to have modified Watson, Betthauser, and Kender to incorporate the teachings of Watson2 by including: outputting pseudo labeling in order to produce pseudo-labeled target examples from the computed energy-distance based similarity relationship by applying a predictable implementation.
Allowable Subject Matter
Claims 6 and 14-15 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 101, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WASSIM MAHROUKA whose telephone number is (571)272-2945. The examiner can normally be reached Monday-Thursday 8:00-5:00 EST.
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/WASSIM MAHROUKA/Primary Examiner, Art Unit 2665