Prosecution Insights
Prosecution Insights
Tech Center 2100 • Art Units: 2127
This examiner grants 50% of resolved cases
Gisel Gabriela Faccenda is an examiner in Tech Center 2100, specifically Art Unit 2127. Based on 24 resolved cases, the examiner has an allowance rate of 50.0 percent. This rate suggests that applications processed by this examiner result in a grant at the frequency indicated by the 50.0 percent allowance rate, while others reach abandonment or different resolutions.
The interview lift is 51.4 percent. This 51.4 percent increase in allowance probability suggests that interviews are a critical component of prosecution for the 24 cases analyzed. Engaging the examiner directly appears to be a factor in overcoming rejections and moving toward an allowance in Art Unit 2127. Practitioners should consider the 51.4 percent lift as a primary tool for improving prosecution outcomes.
The median time to allowance for this examiner is 1473 days. This 1473-day period defines the length of the prosecution process from filing to issuance. Given the 50.0 percent allowance rate, practitioners should prepare for an extended engagement while prioritizing interviews to take advantage of the lift observed in Tech Center 2100. The 1473-day duration is a key metric for long-term planning.
| App # | Title | Status | Assignee |
|---|---|---|---|
| 18268664 | LEARNING DEVICE, LEARNING METHOD, AND LEARNING PROGRAM | Non-Final OA | NEC Corporation |
| 17669872 | Domain Adapting Framework for Anomalous Detection | Non-Final OA | Robert Bosch GmbH |
| 17173460 | SYSTEMS AND METHODS FOR REINFORCED HYBRID ATTENTION FOR MOTION FORECASTING | Final Rejection | Honda Motor Co., Ltd. |
| 18739788 | DATA GENERATION METHOD, MACHINE LEARNING METHOD, INFORMATION PROCESSING APPARATUS, NON-TRANSITORY COMPUTER-READABLE RECORDING MEDIUM STORING DATA GENERATION PROGRAM, AND NON-TRANSITORY COMPUTER-READABLE RECORDING MEDIUM STORING MACHINE LEARNING PROGRAM | Non-Final OA | Fujitsu Limited |
| 17590249 | Method, System, and Computer Program Product for Multi-Task Learning in Deep Neural Networks | Non-Final OA | Visa International Service Association |
| 18718409 | MACHINE-LEARNING APPARATUS AND METHOD FOR IMPLEMENTING ARTIFICIAL INTELLIGENCE EDGE DEVICE BY USING RESISTIVE ELEMENTS, AND ANALYSIS APPARATUS AND METHOD USING SAME | Non-Final OA | POSTECH ACADEMY-INDUSTRY FOUNDATION |
| 18176985 | MACHINE LEARNING MODEL DEVELOPMENT AND OPTIMIZATION PROCESS THAT ENSURES PERFORMANCE VALIDATION AND DATA SUFFICIENCY FOR REGULATORY APPROVAL | Non-Final OA | GE Precision Healthcare LLC |
| 17951587 | TRAINING NEURAL NETWORKS WITH CONVERGENCE TO A GLOBAL MINIMUM | Final Rejection | International Business Machines Corporation |
| 17543149 | AUTOMATED FAIRNESS-DRIVEN GRAPH NODE LABEL CLASSIFICATION | Non-Final OA | International Business Machines Corporation |
| 17351628 | MODEL-AWARE DATA TRANSFER AND STORAGE | Non-Final OA | INTERNATIONAL BUSINESS MACHINES CORPORATION |
| 17552050 | MACHINE LEARNING VIA DIFFERENTIABLE SIMULATION | Non-Final OA | NVIDIA Corporation |
| 17192515 | MACHINE LEARNING TECHNIQUES FOR GENERATING ENJOYMENT SIGNALS FOR WEIGHTING TRAINING DATA | Final Rejection | NETFLIX, INC. |
| 17658070 | MACHINE LEARNING TECHNIQUES FOR EXTRACTING INTERPRETABILITY DATA AND ENTITY-VALUE PAIRS | Final Rejection | Optum, Inc. |
| 17969804 | METHOD FOR SEGMENTING NEURAL NETWORK, ELECTRONIC DEVICE, AND STORAGE MEDIUM | Non-Final OA | HON HAI PRECISION INDUSTRY CO., LTD. |
| 17523567 | SYSTEMS AND METHODS FOR PREDICTING BUILDING FAULTS USING MACHINE LEARNING | Final Rejection | Johnson Controls Tyco IP Holdings LLP |
| 17162601 | FAULT CRITICALITY ASSESSMENT USING GRAPH CONVOLUTIONAL NETWORKS | Final Rejection | Duke University |
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