Privacy-Preserving Natural Language Processing - Big Science - Module 1

For more details about this project see: https://ai.science/l/f0c69d9b-143c-4a... Join our community to participate in this project (message Suhas Pai): https://join.slack.com/t/aisc-to/shar... Join Our Global Effort: This project is a collaboration between Aggregate Intellect, Ontocord, Lighttag, Private AI, and Masakhane as part of Big Science. The aim of this project is to build robust detectors of personally identifiable information (PII). We will focus on building NER (Named Entity Recognition) systems for several low-resource languages and curating datasets in various domains that contain PII. The project as currently envisioned is broken down into 4 Modules. Module 1: Creating gold datasets for multilingual PII detection Module 2: PII detectors for low-resource languages Module 3: Advanced NER detectors Module 4: Combined model training if you have any questions, contact us at [email protected]

Privacy-Preserving Natural Language Processing - Big Science - Module 1

Privacy-Preserving Natural Language Processing - Big Science for Large Language Models

The Latest Advances in Privacy Preserving NLP

Privacy-Preserving Models for Legal Natural Language Processing (NLLP @ EMNLP 2022)

Privacy Preserving Machine Learning with Patricia Thaine

OM PriCon2020 Tutorial: SyferText 0.1.0: Privacy-preserving NLP Over PyGrid - Alan Aboudib

Privacy Preserving AI - 1 I 3rd May 2021 I 5th Session

Sarah Diot-Girard: Privacy-preserving Machine Learning for text processing | PyData Berlin 2019

Catherine Nelson - Practical Privacy-preserving Machine Learning

Doing More with Less: Detecting Malicious Activity through Responsible and Privacy-Preserving AI

NLLP Talks #5: Breaking Down Walls of Text: How Can NLP Benefit Consumer Privacy?

Privacy-preserving Analytics and Machine Learning with Differential Privacy

Accurate, Interpretable, and Privacy-preserving AI for Healthcare | Dr Xiaoxiao Li, Princeton

HCAIM Webinar - Privacy Preserving Machine Learning (PPML) and Explainable AI (XAI)

EMNLP'21: When differential privacy meets NLP

Devfest Algiers 2020 - Privacy-Preserving Machine Learning.

430 - Adaptive Privacy Preserving Deep Learning Algorithms for Medical Data

[MASTERCLASS] Privacy in ML

[3B] Privacy-Preserving Approximate k-Nearest-Neighbors Search that Hides Access, Query and...

OM PriCon2020 Tutorial: Privacy-preserving Medical Imaging Analysis with OpenMined PriMIA