1 code implementation • 15 Jun 2022 • Ali Davody, David Ifeoluwa Adelani, Thomas Kleinbauer, Dietrich Klakow
Transferring knowledge from one domain to another is of practical importance for many tasks in natural language processing, especially when the amount of available data in the target domain is limited.
1 code implementation • 19 Jun 2020 • Ali Davody, David Ifeoluwa Adelani, Thomas Kleinbauer, Dietrich Klakow
Differentially private stochastic gradient descent (DPSGD) is a variation of stochastic gradient descent based on the Differential Privacy (DP) paradigm, which can mitigate privacy threats that arise from the presence of sensitive information in training data.
1 code implementation • 7 Aug 2020 • David Ifeoluwa Adelani, Ali Davody, Thomas Kleinbauer, Dietrich Klakow
Machine Learning approaches to Natural Language Processing tasks benefit from a comprehensive collection of real-life user data.
no code implementations • 7 Dec 2020 • Ali Davody, Mahmoud Safari, Răzvan V. Florian
We propose a new method of program learning in a Domain Specific Language (DSL) which is based on gradient descent with no direct search.
1 code implementation • EMNLP 2021 • David Ifeoluwa Adelani, Miaoran Zhang, Xiaoyu Shen, Ali Davody, Thomas Kleinbauer, Dietrich Klakow
Documents as short as a single sentence may inadvertently reveal sensitive information about their authors, including e. g. their gender or ethnicity.