Phong Le (Lê Phong in Vietnamese)
Amazon Alexa, Cambridge, UK
I'm an applied scientist at Amazon Alexa. Before, I was a tenure-track research fellow at the University of Manchester. I did a postdoc with Ivan Titov at the University of Amsterdam and the University of Edinburgh. I got a PhD from the University of Amsterdam under the supervision of (Jelle) Willem Zuidema.
I'm interested in neural networks and deep learning. My current work is to employ them to solve natural language processing tasks such as entity linking, coreference resolution, and dependency parsing. I'm also interested in formal semantics, especially learning semantic parsing, which is the topic of my master thesis.
Natural Language Processing
W. Zuidema, P. Le. Vector-based and Neural Models of Semantics (book chapter). In: Peter Hagoort (ed.), Human Language: From Genes and Brains to Behavior, MIT Press.
P. Le, M. Dymetman, J-M. Renders. LSTM-based Mixture-of-Experts for Knowledge-Aware Dialogues. ACL Workshop on Representation Learning for NLP, 2016. [pdf, bib].
P. Le and W. Zuidema. Quantifying the vanishing gradient and long distance dependency problem in recursive neural networks and recursive LSTMs. ACL Workshop on Representation Learning for NLP, 2016. [pdf, bib]
P. Le and W. Zuidema. Inside-Outside Semantics: A Framework for Neural Models of Semantic Composition. NIPS 2014 Workshop on Deep Learning and Representation Learning [pdf]
P. Le, W. Zuidema, and R.J.H. Scha. Learning from errors: Using vector-based compositional semantics for parse reranking. ACL Workshop on Continuous Vector Space Models and their Compositionality (oral) [pdf, bib]
P. Le, A.D. Duong, H.Q. Vu, and N.T. Pham (2009). Adaptive hybrid mean shift and particle filter. In proceedings of International Conference on Computing and Communication Technologies, 2009. RIVF’09, pages 1–4. [pdf]
P. Le, N.T. Pham, A.D. Duong, and H.Q. Vu (2008). Tracking a variable number of humans and motorcycles in video via Probability Hypothesis Density filter. IEEE Student Paper Contest. Seoul, Korea.
P. Le. Learning Vector Representations for Sentences - The Recursive Deep Learning Approach. PhD's Thesis, University of Amsterdam. [pdf]
P. Le, M. Dymetman, J. Renders. Dialog device with dialog support generated using a mixture of language models combined using a recurrent neural network. US Patent 20170316775, 2017 [pdf]
2021: ACL, EACL, NAACL
2020: AAAI, ICLR, ACL, ICML, NeurIPS, COLING, EMNLP, AACL
2019: ACL, EMNLP-IJCNLP, CoNLL, *SEM, ICLR, ICML, NeurIPS
2018: ACL, EMNLP, COLING, LREC, NIPS, ICML, ICLR
2017: ACL, NIPS, ICML, ICLR
2016: ACL, NIPS, ICML
Administration chair for CoNLL 2018
Publication chair for *SEM 2016