Hi! I'm Yann.

I'm a computer engineer and a machine learning researcher. I'm currently pursuing a Ph.D. at U. of Montréal on deep learning algorithms for large-scale problems.

Email:

Curriculum Vitae: PDF

Publications

Here are some my research publications in peer-reviewed conferences and journals:

An embedding.

Y. Bengio, G. Mesnil, Y. Dauphin, S. Rifai. Better Mixing via Deep Representations. In Proceedings of the 30th International Conference on Machine Learning (ICML 2013).

S. Rifai, Y. Bengio, Y. Dauphin, P. Vincent. A Generative Process for Sampling Contractive Auto-Encoders. In Proceedings of the 29th International Conference on Machine Learning (ICML 2012).

S. Rifai, Y. Dauphin, P. Vincent, Y. Bengio, X. Muller. The Manifold Tangent Classifier. In Advances in Neural Information Processing Systems (NIPS 2011). Invited as plenary Talk. Best student paper award: Honourable mention.

Y. Dauphin, X. Glorot, Y. Bengio. Large-Scale Learning of Embeddings with Reconstruction Sampling. In Proceedings of the 28th International Conference on Machine Learning (ICML 2011).

S. Rifai, G. Mesnil, P. Vincent, X. Muller, Y. Bengio, Y. Dauphin, X. Glorot. Higher Order Contractive Auto-Encoder. In Proceedings of the European Conference on Machine Learning (ECML 2011).

G. Mesnil, Y. Dauphin, X. Glorot, S. Rifai, Y. Bengio, et al. Unsupervised and Transfer Learning Challenge: a Deep Learning approach. In Journal of Machine Learning Workshop and Conference Papers (JMLR W&CP 2011).

Talks

Manifold Tangent Classifier

At the Neural Information Processing Systems (NIPS) 2011.

Large-scale Learning of Embeddings with Reconstruction Sampling

At the International Conference on Machine Learning (ICML) 2011.

Work Experience

Here are some of my work experiences (check my CV for the full list):

Microsoft Research Logo.

Deep Spoken Language Understanding at Microsoft Research

Tags: Deep Neural Networks, Spoken Language Understanding, Natural Language Processing

I was a research intern in the summer of 2013 to apply deep learning to the problem of Spoken Language Understanding, specifically domain classification and semantic parsing.

Google Logo.

Deep Speech Recognition at Google

Tags: Deep Neural Networks, Speech

I was hired as an intern in the summer of 2012 to do research on deep learning algorithms for Automatic Speech Recognition (ASR). This is for an application that is deployed on every Android phone: Voice Search.

  • I implemented and developed new deep learning algorithms that scaled to billions of examples.

Open Source

Here are some my open source contributions (check my CV for the full list):

Binary

Compiler construction

Tags: JIT compilation, Common Lisp

In 2007, I started working on a Just-in-Time (JIT) compiler for the open source CLisp Virtual Machine. I started development on my own because I wanted to make CLisp faster. I am now an official member of the CLisp team.

Started in the autumn of 2007. Development is ongoing.

Musings

Genetic programming

Tags: Algorithms, Image processing, Creativity

I was amazed by a post written by Roger Alsing. He made an algorithm that could reproduce images using a limited amount of semi-transparent polygons. I wanted to make my own.

  • On the left is a video someone made of my algorithm evolving the Mona Lisa.
  • My project was added to the popular JGap Genetic Algorithm library as an example.