Ph.D. student
Machine Learning Group
Department of Computer Science
University of Toronto

[eleni at cs dot toronto dot edu]




Eleni Triantafillou

I've been recently interested in few-shot learning, and in particular using meta-learning as an avenue for achieving it. My advisors are Raquel Urtasun and Richard Zemel.

When I'm not doing research, I enjoy writing music, dancing, playing the piano and singing.
Here is a song I wrote and another one.

Publications and preprints

Meta-dataset: A dataset of datasets for learning to learn from few examples.
Eleni Triantafillou, Tyler Zhu, Vincent Dumoulin, Pascal Lamblin, Kelvin Xu, Ross Goroshin, Carles Gelada, Kevin Swersky, Pierre-Antoine Manzagol, Hugo Larochelle. [arXiv preprint].

Meta Learning for Semi-Supervised Few-Shot Classification.
Mengye Ren, Eleni Triantafillou*, Sachin Ravi*, Jake Snell, Kevin Swersky, Joshua B. Tenenbaum, Hugo Larochelle, Richard S. Zemel. ICLR 2018. [paper]

Few-Shot Learning Through an Information Retrieval Lens.
Eleni Triantafillou, Richard Zemel and Raquel Urtasun. NIPS 2017. [paper]

Non-Deterministic Planning with Temporally Extended Goals: LTL over finite and infinite traces.
Alberto Camacho, Eleni Triantafillou, Christian Muise, Jorge Baier, and Sheila McIlraith. AAAI, 2017. [paper]

Towards Generalizable Sentence Embeddings
Eleni Triantafillou, Jamie Ryan Kiros, Raquel Urtasun, Richard Zemel.
1st Workshop on Representation Learning for NLP. ACL, 2016. [paper]

A Unifying Framework for Planning with LTL and Regular Expressions
Eleni Triantafillou, Jorge A. Baier, Sheila A. McIlraith.
In Proceedings of MOCHAP, ICAPS, 2015, pages 23-31. [paper]