[2] Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. Neural machine translation by jointly learning to align and translate. CoRR, abs/1409.0473, 2014.
[3] Denny Britz, Anna Goldie, Minh-Thang Luong, and Quoc V. Le. Massive exploration o…[14] Zhongqiang Huang and Mary Harper. Self-training PCFG grammars with latent annotations across languages. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, pages 832–841. ACL, August 2009.
[15] R…
Minh-Thang Luong
scientist · 2 mentions across 1 reading
In this course
Minh-Thang Luong is a machine learning researcher best known for work on neural machine translation and attention mechanisms in deep learning. He appears in the course readings primarily as a co-author on foundational papers exploring the architectural possibilities of NMT systems, particularly the large-scale empirical study of neural translation models that helped consolidate understanding of what works at scale in sequence-to-sequence learning. His contributions are positioned within the genealogy of attention-based architectures that fundamentally changed how language models process and generate text.
Mentioned in 1 reading
Appears alongside
People mentioned in the same passages — sorted by co-occurrence weight.
Anna Goldie 1Bart van Merrienboer 1Caglar Gulcehre 1Denny Britz 1Dzmitry Bahdanau 1Fethi Bougares 1François Chollet 1Geoffrey Hinton 1Holger Schwenk 1Jamie Ryan Kiros 1Jianpeng Cheng 1Jimmy Lei Ba 1Kyunghyun Cho 1Li Dong 1Mirella Lapata 1Nal Kalchbrenner 1Quoc V. Le 1Stephan Gouws 1Yoshua Bengio 1Chris Dyer 1David McClosky 1Lukasz Kaiser 1Mary Harper 1Muhua Zhu 1Oriol Vinyals 1Slav Petrov 1Zhongqiang Huang 1