Agenda
Agenda
Venue: Virtual
Date: June 11, 2021
Timezone: PST – Pacific Standard Time
08:00 - 08:10 Welcome
Sepideh Ghanavati
08:10 - 09:10 Invited Talk
Adam Dziedzic (Vector Institute)
09:10 - 09:30 Break
Morning break
09:30 - 09:50 Research Paper
An Investigation towards Differentially Private Sequence Tagging in a Federated Framework
Abhik Jana and Chris Biemann
09:50 - 10:10 Research Paper
A Privacy-Preserving Approach to Extraction of Personal Information through Automatic Annotation and Federated Learning
Rajitha Hathurusinghe, Isar Nejadgholi and Miodrag Bolic
10:10 - 10:30 Research Paper
Understanding Unintended Memorization in Language Models Under Federated Learning
Om Dipakbhai Thakkar, Swaroop Ramaswamy, Rajiv Mathews and Francoise Beaufays
10:30 - 10:45 Break
Short break
10:45 - 11:45 Invited Talk
Travis Breaux (Carnegie Mellon University)
11:45 - 12:30 Break
Lunch break
12:30 - 12:50 Research Paper
Learning and Evaluating a Differentially Private Pre-trained Language Model
Shlomo Hoory, Amir Feder, Avichai Tendler, Alon Cohen, Sofia Erell, Itay Laish, Hootan Nakhost, Uri Stemmer, Ayelet Benjamini, Avinatan Hassidim and Yossi Matias
12:50 - 13:10 Research Paper
Anonymisation Models for Text Data: State of the art, Challenges and Future Directions
Pierre Lison, Ildikó Pilán, David Sánchez, Montserrat Batet and Lilja Øvrelid
13:10 - 13:20 Break
Short break
13:20 - 13:40 Research Paper
Using Confidential Data for Domain Adaptation of Neural Machine Translation
Sohyung Kim, Arianna Bisazza and Fatih Turkmen
13:40 - 14:00 Research Paper
Private Text Classification with Convolutional Neural Networks
Samuel Adams, David Melanson and Martine De Cock
14:00 - 14:20 Research Paper
On a Utilitarian Approach to Privacy Preserving Text Generation
Zekun Xu, Abhinav Aggarwal, Oluwaseyi Feyisetan and Nathanael Teissier
14:20 - 14:50 Community discussion / Informal panel
Patricia Thaine
14:50 - 15:00 Closing remarks
Oluwaseyi Feyisetan