Tech Center 2100 • Art Units: 2122 2147
This examiner grants 26% of resolved cases
Charles Jeffrey Jones operates within Tech Center 2100 and Art Unit 2122, where he has managed 23 resolved cases. His allowance rate of 26.1 percent suggests a rigorous examination process for applicants. This difficulty is further reflected in the median days to allowance, which stands at 1464 days, indicating a prolonged timeline for successful applications. The combination of a low allowance rate and high pendency suggests that standard written prosecution may be less efficient with this examiner.
Despite the low overall allowance rate, engaging in an interview appears highly effective. The data shows an interview lift of 36.7 percent, indicating that direct communication with the examiner significantly increases the probability of securing a patent compared to the 26.1 percent baseline. Practitioners should prioritize this strategy early in the process to mitigate the 1464-day pendency period and address examiner concerns directly. The volume of 23 resolved cases suggests that these trends may evolve as the examiner's portfolio grows, but the 36.7 percent lift remains a primary tactical consideration for those navigating Art Unit 2122.
| App # | Title | Status | Assignee |
|---|---|---|---|
| 17722858 | METHOD AND APPARATUS WITH DYNAMIC CONVOLUTION | Final Rejection | Samsung Electronics Co., Ltd. |
| 17471345 | Core Data Augmentation Methods For Developing Data Driven Based Petrophysical Interpretation Models | Final Rejection | Halliburton Energy Services, Inc. |
| 18526148 | Modular Training for Flexible Attention Based End-to-End ASR | Final Rejection | Google LLC |
| 18289173 | INCORPORATION OF DECISION TREES IN A NEURAL NETWORK | Non-Final OA | Google LLC |
| 18125027 | TRAINING OF NEURAL NETWORK WITH POLYNOMIAL SOLVER | Non-Final OA | QUALCOMM INCORPORATED |
| 17733874 | FAST-MULTIDIMENSIONAL GLOBAL POLYNOMIAL SOLVER (FM-GPS) | Non-Final OA | QUALCOMM INCORPORATED |
| 18091244 | ARTIFICIAL NEURAL NETWORK FOR DATA IMBALANCED REGRESSION AND METHOD FOR TRAINING SAME | Final Rejection | Royal Bank of Canada |
| 18368341 | METHOD AND SYSTEM FOR PERFORMING TIME SERIES IMPUTATION | Final Rejection | JPMorgan Chase Bank, N.A. |
| 18429182 | SYSTEMS AND METHODS FOR NEXT-BEST ACTION USING A MULTI-OBJECTIVE REWARD BASED SEQUENTIAL FRAMEWORK | Non-Final OA | Walmart Apollo, LLC |
| 18353243 | COMPUTER-READABLE RECORDING MEDIUM STORING SAMPLING PROGRAM, SAMPLING METHOD, AND INFORMATION PROCESSING APPARATUS | Non-Final OA | Fujitsu Limited |
| 18266021 | METHODS AND APPARATUSES FOR PROVIDING TRANSFER LEARNING OF A MACHINE LEARNING MODEL | Final Rejection | TELEFONAKTIEBOLAGET LM ERICSSON (PUBL) |
| 17846007 | Network Space Search for Pareto-Efficient Spaces | Non-Final OA | MediaTek Inc. |
| 18186101 | Method and Apparatus for Continuous Learning of Object Anomaly Detection and State Classification Model | Final Rejection | SK Planet Co., Ltd. |
| 17726724 | ANOMALY DETECTION IN UNKNOWN DOMAINS USING CONTENT-IRRELEVANT AND DOMAIN-IRRELEVANT COMPRESSED DATA | Non-Final OA | International Business Machines Corporation |
| 17551533 | FABRICATING DATA USING CONSTRAINTS TRANSLATED FROM TRAINED MACHINE LEARNING MODELS | Final Rejection | International Business Machines Corporation |
| 18146671 | DETERMINING OBJECT ASSOCIATIONS USING MACHINE LEARNING IN AUTONOMOUS SYSTEMS AND APPLICATIONS | Final Rejection | NVIDIA Corporation |
| 17520448 | NOVEL METHOD OF TRAINING A NEURAL NETWORK | Non-Final OA | NVIDIA Corporation |
| 18612257 | SEARCHING AN OPTIMAL COMBINATION OF HYPERPARAMETERS FOR A MACHINE LEARNING MODEL | Non-Final OA | STMicroelectronics International N. V. |
| 18519224 | PREDICTING SALIENCY VALUES WITH MACHINE LEARNED MODELS FOR MODEL EXPLANATION | Non-Final OA | Red Hat, Inc. |
IP Author analyzes examiner patterns and generates tailored response strategies with the highest chance of allowance.
Build Your Strategy