Irina Rish

Mila > About Mila > Team > Irina Rish
Core Academic Member
Irina Rish
Associate Professor, Associate Professor, Université de Montréal
Irina Rish

Irina Rish is an Associate Professor in the Computer Science and Operations Research department at the Université de Montréal (UdeM) and a core member of Mila – Quebec AI Institute. She holds the Canada CIFAR AI Chair and the Canadian Excellence Research Chair in Autonomous AI. She holds MSc and PhD in AI from University of California, Irvine and MSc in Applied Mathematics from Moscow Gubkin Institute. Dr. Rish’s research focus is on machine learning, neural data analysis and neuroscience-inspired AI.

Her current research interests include continual lifelong learning, optimization algorithms for deep neural networks, sparse modelling and probabilistic inference, dialog generation, biologically plausible reinforcement learning, and dynamical systems approaches to brain imaging analysis. Before joining UdeM and Mila in 2019, she was a research scientist at the IBM T. J. Watson Research Center, where she worked on various projects at the intersection of neuroscience and AI, and led the Neuro-AI challenge. Dr. Rish holds 64 patents, has published over 80 research papers, several book chapters, three edited books, and a monograph on Sparse Modelling.

To view Dr. Rish’s detailed CV, click here.

Publications

2020-12

Towards Continual Reinforcement Learning: A Review and Perspectives.
Khimya Khetarpal, Matthew Riemer, Irina Rish and Doina Precup
arXiv: Learning
(2020-12-28)
arxiv.orgPDF

2020-10

COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing
Prateek Gupta, Tegan Maharaj, Martin Weiss, Nasim Rahaman, Hannah Alsdurf, Abhinav Sharma, Nanor Minoyan, Soren Harnois-Leblanc, Victor Schmidt, Pierre-Luc St. Charles, Tristan Deleu, Andrew Williams, Akshay Patel, Meng Qu, Olexa Bilaniuk, Gaétan Marceau Caron, Pierre Luc Carrier, Satya Ortiz-Gagné, Marc-Andre Rousseau, David Buckeridge... (9 more)
arXiv preprint arXiv:2010.16004
(2020-10-30)
arxiv.orgPDF
Predicting Infectiousness for Proactive Contact Tracing
Yoshua Bengio, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif Muller, Meng Qu, Victor Schmidt, Pierre-Luc St-Charles, Hannah Alsdurf, Olexa Bilanuik, David Buckeridge, Gáetan Marceau Caron, Pierre-Luc Carrier, Joumana Ghosn, Satya Ortiz-Gagne, Chris Pal, Irina Rish, Bernhard Schölkopf... (3 more)
arXiv preprint arXiv:2010.12536
(2020-10-23)
arxiv.orgPDF

2020-09

An Empirical Study of Human Behavioral Agents in Bandits, Contextual Bandits and Reinforcement Learning.
Baihan Lin, Guillermo Cecchi, Djallel Bouneffouf, Jenna Reinen and Irina Rish
arXiv: Artificial Intelligence
(2020-09-10)
arxiv.orgPDF

2020-07

Survey on Applications of Multi-Armed and Contextual Bandits
Djallel Bouneffouf, Irina Rish and Charu Aggarwal
CEC 2020
(2020-07-01)
xplorestaging.ieee.org

2020-06

Adversarial Feature Desensitization.
arXiv preprint arXiv:2006.04621
(2020-06-08)
ui.adsabs.harvard.eduPDF

2020-05

COVI White Paper.
Hannah Alsdurf, Yoshua Bengio, Tristan Deleu, Prateek Gupta, Daphne Ippolito, Richard Janda, Max Jarvie, Tyler Kolody, Sekoul Krastev, Tegan Maharaj, Robert Obryk, Dan Pilat, Valerie Pisano, Benjamin Prud'homme, Meng Qu, Nasim Rahaman, Irina Rish, Jean-Franois Rousseau, Abhinav Sharma, Brooke Struck... (3 more)
arXiv preprint arXiv:2005.08502
(2020-05-18)
dblp.uni-trier.dePDF
Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL
Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Jenna Reinen and Irina Rish
arXiv preprint arXiv:2005.04544
(2020-05-10)
dblp.uni-trier.dePDF

2020-03

Towards Lifelong Self-Supervision For Unpaired Image-to-Image Translation
Victor Schmidt, Makesh Narsimhan Sreedhar, Mostafa ElAraby and Irina Rish
arXiv preprint arXiv:2004.00161
(2020-03-31)
dblp.uni-trier.dePDF
Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning.
Massimo Caccia, Pau Rodríguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Caccia, Issam H. Laradji, Irina Rish, Alexandre Lacoste, David Vázquez and Laurent Charlin
arXiv preprint arXiv:2003.05856
(2020-03-12)
ui.adsabs.harvard.eduPDF
Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning
Massimo Caccia, Pau Rodriguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Page-Caccia, Issam Hadj Laradji, Irina Rish, Alexandre Lacoste, David Vázquez and Laurent Charlin
NEURIPS 2020
(2020-03-01)
papers.nips.cc

2020-02

Modeling Dialogues with Hashcode Representations: A Nonparametric Approach
Sahil Garg, Irina Rish, Guillermo Cecchi, Palash Goyal, Shuyang Gao, Sarik Ghazarian, Greg Ver Steeg and Aram Galstyan
AAAI 2020
(2020-02-07)
aaai.orgPDF

2020-01

Resting-state connectivity stratifies premanifest Huntington's disease by longitudinal cognitive decline rate.
Pablo Polosecki, Eduardo Castro, Irina Rish, Dorian Pustina, John H. Warner, Andrew Wood, Cristina Sampaio and Guillermo A. Cecchi
Scientific Reports
(2020-01-27)
www.nature.com
Double-Linear Thompson Sampling for Context-Attentive Bandits.
Djallel Bouneffouf, Raphaël Féraud, Sohini Upadhyay, Yasaman Khazaeni and Irina Rish
(venue unknown)
(2020-01-01)
dblp.uni-trier.de
A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry.
Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Jenna Reinen and Irina Rish
Autonomous Agents and Multi-Agent Systems
(2020-01-01)
dblp.uni-trier.de

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