Search Results for author: Jared Lichtarge

Found 5 papers, 0 papers with code

Heterogeneous Federated Learning Using Knowledge Codistillation

no code implementations4 Oct 2023 Jared Lichtarge, Ehsan Amid, Shankar Kumar, Tien-Ju Yang, Rohan Anil, Rajiv Mathews

Federated Averaging, and many federated learning algorithm variants which build upon it, have a limitation: all clients must share the same model architecture.

Federated Learning Image Classification +2

Simple and Effective Gradient-Based Tuning of Sequence-to-Sequence Models

no code implementations10 Sep 2022 Jared Lichtarge, Chris Alberti, Shankar Kumar

For T5, we show that learning hyper-parameters during pretraining can improve performance across downstream NLU tasks.

Hyperparameter Optimization Machine Translation +2

Data Weighted Training Strategies for Grammatical Error Correction

no code implementations7 Aug 2020 Jared Lichtarge, Chris Alberti, Shankar Kumar

Recent progress in the task of Grammatical Error Correction (GEC) has been driven by addressing data sparsity, both through new methods for generating large and noisy pretraining data and through the publication of small and higher-quality finetuning data in the BEA-2019 shared task.

Grammatical Error Correction Machine Translation +2

Weakly Supervised Grammatical Error Correction using Iterative Decoding

no code implementations31 Oct 2018 Jared Lichtarge, Christopher Alberti, Shankar Kumar, Noam Shazeer, Niki Parmar

We describe an approach to Grammatical Error Correction (GEC) that is effective at making use of models trained on large amounts of weakly supervised bitext.

Grammatical Error Correction

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