no code implementations • 6 Apr 2021 • Jae Ro, Mingqing Chen, Rajiv Mathews, Mehryar Mohri, Ananda Theertha Suresh
We propose a communication-efficient distributed algorithm called Agnostic Federated Averaging (or AgnosticFedAvg) to minimize the domain-agnostic objective proposed in Mohri et al. (2019), which is amenable to other private mechanisms such as secure aggregation.
1 code implementation • COLING 2020 • Hao Zhang, Jae Ro, Richard Sproat
Breaking domain names such as openresearch into component words open and research is important for applications like Text-to-Speech synthesis and web search.
1 code implementation • 5 Nov 2020 • Hao Zhang, Jae Ro, Richard Sproat
Breaking domain names such as openresearch into component words open and research is important for applications like Text-to-Speech synthesis and web search.
no code implementations • 19 Jul 2020 • Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh, Ke wu
We present a theoretical and algorithmic study of the multiple-source domain adaptation problem in the common scenario where the learner has access only to a limited amount of labeled target data, but where the learner has at disposal a large amount of labeled data from multiple source domains.
1 code implementation • 25 Feb 2020 • Yishay Mansour, Mehryar Mohri, Jae Ro, Ananda Theertha Suresh
The standard objective in machine learning is to train a single model for all users.