132 citations · 161 across the 15 of their papers we have counts for
4 papers · 1 filter
Communication-Efficient Federated Learning for Neural Machine Translation
Tanya Roosta, Peyman Passban, Ankit Chadha
Training neural machine translation (NMT) models in federated learning (FL) settings could be inefficient both computationally and communication-wise, due to the large size of tran…
Not Far Away, Not So Close: Sample Efficient Nearest Neighbour Data Augmentation via MiniMax
Ehsan Kamalloo, Mehdi Rezagholizadeh, Peyman Passban +1
In Natural Language Processing (NLP), finding data augmentation techniques that can produce high-quality human-interpretable examples has always been challenging. Recently, leverag…
Robust Embeddings Via Distributions
Kira A. Selby, Yinong Wang, Ruizhe Wang +4
Despite recent monumental advances in the field, many Natural Language Processing (NLP) models still struggle to perform adequately on noisy domains. We propose a novel probabilist…
From Fully Trained to Fully Random Embeddings: Improving Neural Machine Translation with Compact Word Embedding Tables
Krtin Kumar, Peyman Passban, Mehdi Rezagholizadeh +2
Embedding matrices are key components in neural natural language processing (NLP) models that are responsible to provide numerical representations of input tokens.\footnote{In this…