Irina Rish

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Citations	11902	6572
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Guillermo CecchiIBM ResearchVerified email at us.ibm.com
Pouya BashivanAssistant Professor, McGill universityVerified email at mcgill.ca
Dimitri KanevskyRessearcher, IBM T.J. WatsonVerified email at us.ibm.com
Ricardo VilaltaUniversity of HoustonVerified email at ieee.org
Katya ScheinbergCornell UniversityVerified email at cornell.edu
Bhuvana RamabhadranManager, GoogleVerified email at google.com
Joseph HellersteinUniversity of WashingtonVerified email at uw.edu
Rahul GargProfessor, Computer Science and Engineering, Indian Institute of Technology, DelhiVerified email at cse.iitd.ac.in
Dan HeIBM T. J. WatsonVerified email at us.ibm.com
Mohammed YeasinUniversity of MemphisVerified email at memphis.edu
Noel CodellaPrincipal Researcher @ MicrosoftVerified email at microsoft.com
Marwan N BalikiNorthwestern UniversityVerified email at northwestern.edu
Apkar Vania ApkarianNorthwestern UniversityVerified email at northwestern.edu
Aurelie LozanoResearch Staff Member, IBM ResearchVerified email at us.ibm.com
JB PolineMNI, McGill University and UC BerkeleyVerified email at mcgill.ca
Marion PlazePsychiatrist at Sainte-Anne hospital, Paris Descartes University & INSERM U894Verified email at ch-sainte-anne.fr
Bertrand ThirionInriaVerified email at inria.fr
T.S. JayramIBM Almaden ResearchVerified email at us.ibm.com
Aleks Jakulin1o IncVerified email at stat.columbia.edu
Francisco PereiraMachine Learning Team, National Institute of Mental HealthVerified email at nih.gov

Irina Rish

University of Montreal / Mila -Quebec AI Institute

Verified email at mila.quebec - Homepage

Artificial Intelligence Machine Learning Neuroscience


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An empirical study of the naive Bayes classifier I Rish IJCAI 2001 workshop on empirical methods in artificial intelligence 3 (22 …, 2001	4611	2001
Learning representations from EEG with deep recurrent-convolutional neural networks P Bashivan, I Rish, M Yeasin, N Codella arXiv preprint arXiv:1511.06448, 2015	724	2015
Learning to learn without forgetting by maximizing transfer and minimizing interference M Riemer, I Cases, R Ajemian, M Liu, I Rish, Y Tu, G Tesauro arXiv preprint arXiv:1810.11910, 2018	473	2018
Critical event prediction for proactive management in large-scale computer clusters RK Sahoo, AJ Oliner, I Rish, M Gupta, JE Moreira, S Ma, R Vilalta, ... Proceedings of the ninth ACM SIGKDD international conference on Knowledge …, 2003	379	2003
Mini-buckets: A general scheme for bounded inference R Dechter, I Rish Journal of the ACM (JACM) 50 (2), 107-153, 2003	282	2003
Adaptive diagnosis in distributed systems I Rish, M Brodie, S Ma, N Odintsova, A Beygelzimer, G Grabarnik, ... IEEE Transactions on neural networks 16 (5), 1088-1109, 2005	242	2005
Directional resolution: The davis-putnam procedure, revisited R Dechter, I Rish Principles of knowledge representation and reasoning, 134-145, 1994	233	1994
Improving network robustness by edge modification A Beygelzimer, G Grinstein, R Linsker, I Rish Physica A: Statistical Mechanics and its Applications 357 (3-4), 593-612, 2005	232	2005
Sparse modeling: theory, algorithms, and applications I Rish, G Grabarnik CRC press, 2014	221	2014
Prediction and interpretation of distributed neural activity with sparse models MK Carroll, GA Cecchi, I Rish, R Garg, AR Rao NeuroImage 44 (1), 112-122, 2009	210	2009
Survey on applications of multi-armed and contextual bandits D Bouneffouf, I Rish, C Aggarwal 2020 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2020	193	2020
Resolution versus search: Two strategies for SAT I Rish, R Dechter Journal of Automated Reasoning 24 (1-2), 225-275, 2000	160	2000
An analysis of data characteristics that affect naive Bayes performance I Rish, J Hellerstein, J Thathachar IBM TJ Watson Research Center 30, 1-8, 2001	146	2001
Real-time problem determination in distributed systems using active probing I Rish, M Brodie, N Odintsova, S Ma, G Grabarnik 2004 IEEE/IFIP Network Operations and Management Symposium (IEEE Cat. No …, 2004	137	2004
Optimizing probe selection for fault localization M Brodie, I Rish, S Ma	107	2001
Intelligent probing: A cost-effective approach to fault diagnosis in computer networks M Brodie, I Rish, S Ma IBM systems journal 41 (3), 372-385, 2002	103	2002
Online fast adaptation and knowledge accumulation: a new approach to continual learning M Caccia, P Rodriguez, O Ostapenko, F Normandin, M Lin, L Caccia, ... arXiv preprint arXiv:2003.05856, 2020	101*	2020
Towards continual reinforcement learning: A review and perspectives K Khetarpal, M Riemer, I Rish, D Precup Journal of Artificial Intelligence Research 75, 1401-1476, 2022	94	2022
Summarizing CSP hardness with continuous probability distributions D Frost, I Rish, L Vila AAAI/IAAI, 327-333, 1997	94	1997
A scheme for approximating probabilistic inference R Dechter, I Rish arXiv preprint arXiv:1302.1534, 2013	89	2013

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