Search Results for author: Hong-You Chen

Found 8 papers, 1 papers with code

On Bridging Generic and Personalized Federated Learning

no code implementations2 Jul 2021 Hong-You Chen, Wei-Lun Chao

On the one hand, we introduce a family of losses that are robust to non-identical class distributions, enabling clients to train a generic predictor with a consistent objective across them.

Personalized Federated Learning

Glyph2Vec: Learning Chinese Out-of-Vocabulary Word Embedding from Glyphs

no code implementations ACL 2020 Hong-You Chen, Sz-Han Yu, Shou-De Lin

Chinese NLP applications that rely on large text often contain huge amounts of vocabulary which are sparse in corpus.

Multiple Text Style Transfer by using Word-level Conditional Generative Adversarial Network with Two-Phase Training

no code implementations IJCNLP 2019 Chih-Te Lai, Yi-Te Hong, Hong-You Chen, Chi-Jen Lu, Shou-De Lin

The objective of non-parallel text style transfer, or controllable text generation, is to alter specific attributes (e. g. sentiment, mood, tense, politeness, etc) of a given text while preserving its remaining attributes and content.

Style Transfer Text Style Transfer

DEEP-TRIM: REVISITING L1 REGULARIZATION FOR CONNECTION PRUNING OF DEEP NETWORK

no code implementations ICLR 2019 Chih-Kuan Yeh, Ian E. H. Yen, Hong-You Chen, Chun-Pei Yang, Shou-De Lin, Pradeep Ravikumar

State-of-the-art deep neural networks (DNNs) typically have tens of millions of parameters, which might not fit into the upper levels of the memory hierarchy, thus increasing the inference time and energy consumption significantly, and prohibiting their use on edge devices such as mobile phones.

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