Irina Rish

Cited by

	All	Since 2016
Citations	8361	4180
h-index	34	22
i10-index	93	58

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Co-authors

Guillermo CecchiIBM ResearchVerified email at us.ibm.com
Dimitri KanevskyRessearcher, IBM T.J. WatsonVerified email at us.ibm.com
Pouya BashivanAssistant Professor, McGill universityVerified email at mcgill.ca
Ricardo VilaltaUniversity of HoustonVerified email at ieee.org
Katya ScheinbergCornell UniversityVerified email at cornell.edu
Aurelie LozanoResearch Staff Member, IBM ResearchVerified email at us.ibm.com
Bhuvana RamabhadranManager, GoogleVerified email at google.com
Rahul GargProfessor, Computer Science and Engineering, Indian Institute of Technology, DelhiVerified email at cse.iitd.ac.in
Joseph HellersteinUniversity of WashingtonVerified email at uw.edu
Dan HeIBM T. J. WatsonVerified email at us.ibm.com
Marwan N BalikiNorthwestern UniversityVerified email at northwestern.edu
Mohammed YeasinUniversity of MemphisVerified email at memphis.edu
Noel CodellaMicrosoftVerified email at microsoft.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
Apkar Vania ApkarianNorthwestern UniversityVerified email at northwestern.edu
Aleks Jakulin1o IncVerified email at stat.columbia.edu
T.S. JayramIBM Almaden ResearchVerified email at us.ibm.com
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 Quantum computing


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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	3064	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	429	2015
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	353	2003
Mini-buckets: A general scheme for bounded inference R Dechter, I Rish Journal of the ACM (JACM) 50 (2), 107-153, 2003	254	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	228	2005
Directional resolution: The davis-putnam procedure, revisited R Dechter, I Rish Principles of knowledge representation and reasoning, 134-145, 1994	217	1994
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	198	2009
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	198	2005
Sparse modeling: theory, algorithms, and applications I Rish, G Grabarnik CRC press, 2014	158	2014
Resolution versus search: Two strategies for SAT I Rish, R Dechter Journal of Automated Reasoning 24 (1), 225-275, 2000	156	2000
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	132	2004
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	127	2001
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	121	2018
Optimizing probe selection for fault localization M Brodie, I Rish, S Ma	104	2001
Smart card reader M Lahteenmaki, J Uusilehto, T Kannisto, J Uusi-Rantala, K Ketola, ... US Patent 6,942,147, 2005	103	2005
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	102	2002
A scheme for approximating probabilistic inference R Dechter, I Rish arXiv preprint arXiv:1302.1534, 2013	87	2013
Summarizing CSP hardness with continuous probability distributions D Frost, I Rish, L Vila AAAI/IAAI, 327-333, 1997	84	1997
Efficient test selection in active diagnosis via entropy approximation AX Zheng, I Rish, A Beygelzimer arXiv preprint arXiv:1207.1418, 2012	80	2012
Closed-form supervised dimensionality reduction with generalized linear models I Rish, G Grabarnik, G Cecchi, F Pereira, GJ Gordon Proceedings of the 25th international conference on Machine learning, 832-839, 2008	75	2008

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