Publications


Adversity Helps Exploration: a KL-regularized Actor Critic.
Under review, 2020.


Is Standard Deviation the New Standard? Revisiting the Critic in Deep Policy Gradients.
Under review, 2020.

Link PDF


Only Relevant Information Matters: Filtering Out Noisy Samples to Boost RL.
29th International Joint Conference on Artificial Intelligence (IJCAI), 2020.

Link PDF


Temperature Decreases Spread Parameters of the New Covid-19 Case Dynamics.
Biology, 9(5), p.94, 2020.

Link PDF


MERL: Multi-Head Reinforcement Learning.
Deep Reinforcement Learning Workshop, NeurIPS, 2019.

Link PDF


High-Dimensional Control Using Generalized Auxiliary Tasks.
Research Report hal-02295705, 2019.

Link PDF


Hearables in Hearing Care: Discovering Usage Patterns Through IoT Devices.
International Conference on Universal Access in Human-Computer Interaction, 2017.

Link

Invited Talks

Oral & Panel Discussion: Do we control the algorithms we create?
November, 2019
Improving Policy Gradient Updates with MERL and SAUNA
October, 2019
Deep Reinforcement Learning at Scale
April, 2019
QA and Deep Learning for Language Understanding
November, 2017

Teaching

Reinforcement Learning - Fall 2019 - MVA - ENS Paris-Saclay

Instructors: Alessandro Lazaric, Matteo Pirotta & Reda Ouhamma

Reinforcement Learning Summer School 2019

Instructors: Felix Berkenkamp, Tristan Cazenave, Ludovic Denoyer, Gabriel Dulac-Arnold, Audrey Durand, Vincent François-Lavet, Matteo Hessel, Emilie Kaufmann, Marc Lanctot, Max Lapan, Alessandro Lazaric, Odalric-Ambrym Maillard, Jérémie Mary, Gerhard Neumann, Guillaume Obozinski, Olivier Pietquin, Bilal Piot, Matteo Pirotta, Bruno Scherrer, Florian Strub, Eleni Vasilaki, Oriol Vinyals

Professional Experience

 
 
 
 
 
November 2017 – October 2018
Nantes, FR

Machine Learning Engineer

iAdvize

Designed and executed product-focused research agendas, which led to building a conversational model for human/machine interface using deep learning.
 
 
 
 
 
August 2017 – November 2017
Copenhagen, DK

Research Assistant

DTU

Research work at DTU Compute laboratory focusing on deep convolutional neural network models for image classification and generative adversarial network models for image generation from a mixture of human artworks and photographs.
 
 
 
 
 
March 2017 – August 2017
Copenhagen, DK

Machine Learning Researcher

Soply (part-time during MSc)

Defined with the co-founders a roadmap for ML projects in the company, which led to building a system to recommend artists according to their photographic style and three artworks classification models (content, style & type) in collaboration with the National Gallery of Denmark.
 
 
 
 
 
November 2015 – January 2017
Copenhagen, DK

Machine Learning Engineer

EasyTranslate (part-time during MSc)

Several research projects in collaboration with the product team including a seq2seq machine translation model for specialized text and a recommendation system for human translators using LDA models trained on Wikipedia, deployed on AWS.