Publications
Books
2019
Beyond Backprop: Online Alternating Minimization with Auxiliary Variables
Anna Choromanska*, Benjamin Cowen*, Sadhana Kumaravel*, Ronny Luss*, Mattia Rigotti*, Irina Rish*, Brian Kingsbury, Paolo DiAchille, Viatcheslav Gurev, Ravi Tejwani, Djallel Bouneffouf
International Conference on Machine Learning (ICML 2019) Code is available here.
Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference
Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, Gerald Tesauro
International Conference on Learning Representations (ICLR-2019)
Kernelized Hashcode Representations for Biomedical Relation Extraction
Garg, Sahil, Aram Galstyan, Greg Ver Steeg, Irina Rish, Guillermo Cecchi, and Shuyang Gao
Thirty-third AAAI conference on Artificial Intelligence (AAAI-2019), 2019
Predicting conversion to psychosis in clinical high risk patients using resting-state functional MRI features
J. McDonnell, W. Hord, J. Reinen, P. Polosecki, I. Rish and G. Cecchi
SPIE Medical Imaging 2019: Biomedical Applications in Molecular, Structural, and Functional Imaging, pp. 109532A
2018
Dialogue Modeling Via Hash Functions
S. Garg, A. Galstyan, I. Rish, G.A. Cecchi, S. Gao
Linguistic and Cognitive Approaches to Dialog Agents (LaCATODA) 2018 IJCAI/ICML Workshop
Baseline multimodal information predicts future motor impairment in premanifest Huntington's disease
E. Castro, P. Polosecki, I. Rish, D. Pustina, JH Warner, A. Wood, C. Sampaio, GA Cecchi
NeuroImage - Clinical, 2018
Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM
German Abrevaya, Aleksandr Aravkin, Guillermo Cecchi, Irina Rish, Pablo Polosecki, Peng Zheng, Silvina Dawson
arXiv:1805.09874 [stat.ML], 2018
Contextual Bandit with Adaptive Feature Extraction
Baihan Lin, Guillermo Cecchi, Djallel Bouneffouf, Irina Rish
Proc of IEEE ICDM-2020 Workshop on Data Science and Big Data Analytics, 2018
Variable Selection in Gaussian Markov Random Fields
Jean Honorio, Dimitris Samaras, Irina Rish, Guillermo A. Cecchi
Book chapter in Log-Linear Models, Extensions and Applications, MIT Press, 2018
2017
Learning Neural Markers of Schizophrenia Disorder Using Recurrent Neural Networks
Jumana Dakka, Pouya Bashivan, Mina Gheiratmand, Irina Rish, Shantenu Jha, Russell Greiner
NIPS 2017 workshop on Machine Learning for Health (ML4H), arXiv preprint arXiv:1712.00512
Bandit Models of Human Behavior: Reward Processing in Mental Disorders
Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi
Artificial General Intelligence (AGI-2017)
P. Polosecki, E. Castro, A. Wood, J. H. Warner, I. Rish and G. A. Cecchi
IBM Journal of Research and Development 61(2/3), IEEE , 2017
Attentive Bandit: Contextual Bandit with Restricted Context
Djallel Bouneffouf, Irina Rish, Raphael Feraud and Guillermo Cecchi
International Joint Conference on Artificial Intelligence (IJCAI-2017)
Learning stable and predictive network-based patterns of schizophrenia and its clinical symptoms
Mina Gheiratmand, Irina Rish, Guillermo A Cecchi, Matthew RG Brown, Russell Greiner, Pablo I Polosecki, Pouya Bashivan, Andrew J Greenshaw, Rajamannar Ramasubbu, Serdar M Dursun
npj Schizophrenia 3(1), 22, Nature Publishing Group, 2017
Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World
Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurelie Lozano
International Joint Conference on Artificial Intelligence (IJCAI-2017). Extended verion arXiv:1701.06106
Computing the structure of language for neuropsychiatric evaluation
G. A. Cecchi, V. Gurev, S.J. Heisig, R. Norel, I. Rish, S. R. Schrecke
IBM Journal of Research and Development 61(2/3), IEEE, 2017
Holographic brain: Distributed versus local activation patterns in fMRI
I. Rish and G.A. Cecchi
IBM Journal of Research and Development 61(2/3), IEEE, 2017
Learning Discriminative Functional Network Features of Schizophrenia
Mina Gheiratmand, Irina Rish, Guillermo Cecchi, Matthew Brown, Russell Greiner, Pouya Bashivan, Pablo Polosecki, Serdar Dursun
SPIE Medical Imaging, 2017
Functional Network Disruptions in Schizophrenia
Irina Rish and Guillermo A. Cecchi
Book chapter, Biological Networks and Pathway Analysis, edited by Y. Nikolsky and T. Tatarinova , Springer, 2017
2016
Irina Rish, Pouya Bashivan, Guillermo A. Cecchi, Rita Z. Goldstein
SPIE Medical Imaging, 2016
Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks
Pouya Bashivan, Irina Rish, Mohammed Yeasin, Noel Codella
ICLR 2016 : International Conference on Learning Representations 2016
2015
Variable-Selection Emerges on Top in Empirical Comparison of Whole-Genome Complex-Trait Prediction Methods
D. C. Haws, I. Rish, S. Teyssedre, D. He, A. C. Lozano, P. Kambadur, Z. Karaman, L. Parida
PLoS ONE 10(10), e0138903, 2015
Mental State Recognition via Wearable EEG
Pouya Bashivan, Irina Rish, Steve Heisig
NIPS Workshop on Machine Learning and Interpretation in Neuroimaging (MLINI2015)
MINT: Mutual Information based Transductive Feature Selection for Genetic Trait Prediction
He, D., Rish, I. Haws, D. and Parida, L.
IEEE/ACM Transactions on Computational Biology and Bioinformatics pp. 99, 2015
Turing a la Freud: Test for an Automated Psychiatrist
G.A. Cecchi and I. Rish
Beyond the Turing Test - AAAI 2015 Workshop
2014
Sparse Modeling: Theory, Algorithms and Applications
Irina Rish and Genady Grabarnik
Chapman & Hall/CRC Machine Learning & Pattern Recognition, 2014
Practical Applications of Sparse Modeling
Irina Rish, Guillermo A. Cecchi, Aurelie Lozano and Alexandru Niculescu-Mizil
MIT Press, 2014
Augmented Human: Human OS for Improved Mental Function
Steve Heisig, Guillermo Cecchi, Ravi Rao and Irina Rish
AAAI 2014 Workshop on Cognitive Computing and Augmented Human Intelligence
Abstract
D.He, I. Rish, L. Parida
In Proc of SIAM Data Mining (SDM), 2014
Abstract
Reliability Estimation and Enhancement via Spatial Smoothing in Sparse fMRI Modeling
Carroll, Melissa K., Guillermo A. Cecchi, Irina Rish, Rahul Garg, Marwan Baliki, and A. Vania Apkarian
Practical Applications of Sparse Modeling, pp. 123-150, MIT Press, 2014
Abstract
2013
MINT: Mutual Information based Transductive Feature Selection for Genetic Trait Prediction
D. He, I. Rish, D. Haws, S.Teyssedre, Z. Karaman, L. Parida
The Seventh International Workshop on Machine Learning in Systems Biology (MLSB 2013),
Abstract
Functional MRI Analysis with Sparse Models
I. Rish
Invited paper at NECTAR track of the European Conference on Machine Learning (ECML-2013)
Abstract
Sparse Signal Recovery with Exponential-Family Noise
Irina Rish and Genady Grabarnik
Book chapter, Compressed Sensing & Sparse Filtering, Springer, 2013
Abstract
Schizophrenia as a network disease: disruption of emergent brain function in patients with auditory hallucinations
I. Rish, G. Cecchi, B. Thyreau, B. Thirion, M. Plaze, M. L. Paillere-Martinot, C. Martelli, J. L. Martinot, J. B. Poline
PLoS ONE 8(1), e50625, 2013
2012
Edited by Georg Langs, Irina Rish, Moritz Grosse-Wentrup, Brian Murphy
Springer, 2012
Sparse regression analysis of task-relevant information distribution in the brain
Irina Rish, Guillermo A Cecchi, Kyle Heuton, Marwan N Baliki, A Vania Apkarian
SPIE Medical Imaging, 2012
Abstract
Predictive dynamics of human pain perception
G. A. Cecchi, L. Huang, J. A. Hashmi, M. Baliki, M. V. Centeno, I. Rish, A. V. Apkarian
PLoS Comput. Biol. 8(10), e1002719, 2012
Schizophrenia classification using functional network features
Irina Rish, Guillermo A Cecchi, Kyle Heuton
SPIE Medical Imaging, pp. 83170W--83170W, 2012
Abstract
Variable Selection for Gaussian Graphical Models
Jean Honorio, Dimitris Samaras, Irina Rish, Guillermo Cecchi
AISTATS, 2012
Abstract
2011
Adult neurogenesis as efficient sparsification
I. Rish, G. Cecchi, A. Lozano, R. Rao
Neuroscience 2011 (SfN meeting), November 12-16
Abstract
2010
Sparse Markov Net Learning with Priors on Regularization Parameters
Katya Scheinberg, Irina Rish, Narges Bani Asadi
in Proceedings of The Eleventh International Symposium on Artificial Intelligence and Mathematics (ISAIM 2010), pp. 112--122
Abstract
Sparse regression models of pain perception
Irina Rish, Guillermo A Cecchi, Marwan N Baliki, A Vania Apkarian
Brain Informatics, pp. 212--223, Springer, 2010
Abstract
Learning sparse Gaussian Markov networks using a greedy coordinate ascent approach
Katya Scheinberg, Irina Rish
European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), pp. 196--212, Springer, 2010
Abstract
2009
Isometry-enforcing data transformations for improving sparse model learning
Avishy Carmi, Irina Rish, Guillermo Cecchi, Dimitri Kanevsky, Bhuvana Ramabhadran
IBM Tech Report RC24801, Tech. Rep. RC 24801, Human Language Technologies, IBM, 2009
Discriminative network models of schizophrenia
Guillermo Cecchi, Irina Rish, Benjamin Thyreau, Bertrand Thirion, Marion Plaze, Marie-Laure Paillere-Martinot, Catherine Martelli, Jean-Luc Martinot, Jean-Baptiste Poline
Advances in Neural Information Processing Systems (NIPS 2009) , pp. 252--260, Citeseer
Prediction and interpretation of distributed neural activity with sparse models
Melissa K Carroll, Guillermo A Cecchi, Irina Rish, Rahul Garg, A Ravishankar Rao
NeuroImage 44(1), 112--122, Elsevier, 2009
SINCO-a greedy coordinate ascent method for sparse inverse covariance selection problem
Katya Scheinberg, Irina Rish
preprint, 2009
Map approach to learning sparse Gaussian Markov networks
N Bani Asadi, I Rish, K Scheinberg, D Kanevsky, B Ramabhadran
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on, pp. 1721--1724
Sparse signal recovery with exponential-family noise
Irina Rish, Genady Grabarnik
Communication, Control, and Computing, 2009. Allerton 2009. 47th Annual Allerton Conference on, pp. 60--66
2008
A New Family of Extended Baum-Welch Update Rules
Dimitri Kanevsky, Daniel Povey, Bhuvana Ramabhadran, Irina Rish, Tara Sainath
2008
Closed-form supervised dimensionality reduction with generalized linear models
Irina Rish, Genady Grabarnik, Guillermo Cecchi, Francisco Pereira, Geoffrey J Gordon
Proceedings of the 25th international conference on Machine learning, pp. 832--839, 2008
2007
Evaluation of optimization methods for network bottleneck diagnosis
Alina Beygelzimer, Jeff Kephart, Irina Rish
Autonomic Computing, 2007. ICAC'07. Fourth International Conference on, pp. 20--20, IEEE
Blind source separation approach to performance diagnosis and dependency discovery
Gaurav Chandalia, Irina Rish
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement, pp. 259--264, 2007
Empirical study of topology effects on diagnosis in computer networks
Natalia Odintsova, Irina Rish
Mobile Adhoc and Sensor Systems, 2007. MASS 2007. IEEE Internatonal Conference on, pp. 1--6
Estimating end-to-end performance by collaborative prediction with active sampling
Irina Rish, Gerald Tesauro
Integrated Network Management, 2007. IM'07. 10th IFIP/IEEE International Symposium on, pp. 294--303
2006
Automated Knowledge Elicitation and Flowchart Optimization for Problem Diagnosis
Alina Beygelzimer, Mark Brodie, Jonathan Lenchner, Irina Rish
UAI-06 Workshop on Applications of Bayesian Networks, 2006
Information-theoretic approaches to cost-efficient diagnosis
Irina Rish
Proc. Information Theory and Applications Inaugural Work., San Diego, CA, 2006
Bayesian learning of Markov network structure
Aleks Jakulin, Irina Rish
ECML 2006, pp. 198--209, Springer
Active Sampling Approaches in Systems Management Applications
Irina Rish
SysML Workshop at SIGMETRICS-06 , Citeseer, 2006
2005
Improving network robustness by edge modification
Alina Beygelzimer, Geoffrey Grinstein, Ralph Linsker, Irina Rish
Physica A: Statistical Mechanics and its Applications 357(3), 593--612, Elsevier, 2005
Efficient test selection in active diagnosis via entropy approximation
Alice X Zheng, Irina Rish, Alina Beygelzimer
UAI-2005
Multi-fault diagnosis in dynamic systems
Natalia Odintsova, Irina Rish, Sheng Ma
Proceedings of the 9th IFIP/IEEE International Symposium on Integrated Network Management (IM 2005, Poster-CD)
Test-based diagnosis: Tree and matrix representations
Alina Beygelzimer, Mark Brodie, Sheng Ma, Irina Rish
Integrated Network Management, 2005. IM 2005. 2005 9th IFIP/IEEE International Symposium on, pp. 529--542
Self-healing in large-scale systems: parallel and distributed diagnostic architectures
Loewenstern Odintsova D N S. Guo I. Rish
Technical Report, 2005
Multifault Diagnosis in Dynamic Systems
N Odintsova, I Rish, S Ma
Integrated management (IM-2005), Nice, France
Adaptive diagnosis in distributed systems
I. Rish, M. Brodie, S. Ma, N. Odintsova, A. Beygelzimer, G. Grabarnik, K. Hernandez
IEEE Trans Neural Netw 16(5), 1088--1109, 2005
Distributed systems diagnosis using belief propagation
Irina Rish
Proc. Allerton Conf. Communication, Control and Computing, Monticello, IL, Citeseer, 2005
Self-healing in large-scale systems: parallel and distributed diagnostic architectures
D Loewenstern N Odintsova S Guo, Irina Rish, David Loewenstern
Technical Report, Technical report, IBM TJ Watson Research Center, 2005
2004
Kikuchi-Bayes: Factorized models for approximate classification in closed form
Aleks Jakulin, Irina Rish, Ivan Bratko
Technical Report, Technical Report RC23314, IBM, 2004
Statistical models for unequally spaced time series
Emre Erdogan, Sheng Ma, Alina Beygelzimer, Irina Rish
Proceedings of the Fifth SIAM International Conference on Data Mining, SIAM, 2004
A Beygelmizer, Geoffrey Grinstein, Ralph Linsker, Irina Rish
Proceedings of International Conference on Autonomic Computing, pp. 322--323, 2004
Multifault Diagnosis in Dynamic Systems
N Odintsova, I Rish, S Ma
Technical Report RC23385, 2004
Real-time problem determination in distributed systems using active probing
Irina Rish, Mark Brodie, Natalia Odintsova, Sheng Ma, Genady Grabarnik
Network Operations and Management Symposium, 2004. NOMS 2004. IEEE/IFIP, pp. 133--146
2003
Critical event prediction for proactive management in large-scale computer clusters
Ramendra K Sahoo, Adam J Oliner, Irina Rish, Manish Gupta, Jos\'e E Moreira, Sheng Ma, Ricardo Vilalta, Anand Sivasubramaniam
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 426--435, ACM, 2003
Autonomic computing features for large-scale server management and control
RK Sahoo, I Rish, AJ Oliner, M Gupta, JE Moreira, S Ma, R Vilalta, A Sivasubramaniam
AIAC Workshop, IJCAI 2003
Problem Diagnosis in Distributed Systems using Active Probing
Irina Rish, Mark Brodie, Natalia Odintsova, Sheng Ma, Genady Grabarnik
UAI-2003 workshop on Bayesian Modeling Applications
A decomposition of classes via clustering to explain and improve naive Bayes (Best Paper Award)
Ricardo Vilalta, Irina Rish
Machine Learning: ECML 2003, pp. 444--455, Springer
Mini-buckets: A general scheme for bounded inference
Rina Dechter, Irina Rish
Journal of the ACM (JACM) 50(2), 107--153, ACM, 2003
Active probing strategies for problem diagnosis in distributed systems
Mark Brodie, Irina Rish, Sheng Ma, Natalia Odintsova, Alina Beygelzimer
Proceedings of the The Eighteenth International Joint Conference on Artificial Intelligence (IJCAI-03), Acapulco, Mexico, pp. 1337--1338, LAWRENCE ERLBAUM ASSOCIATES LTD, 2003
Approximability of probability distributions
Alina Beygelzimer, Irina Rish
Advances in Neural Information Processing Systems 16 (NIPS-2003), MIT Press
2002
Using sensitivity analysis for selective parameter update in Bayesian network learning
Haiqin Wang, Irina Rish, Sheng Ma
Information Refinement and Revision for Decision Making: Modeling for Diagnostics, Prognostics and Prediction, AAAI 2002 Spring Symposium, Technical Report SS-02-03, pp. 29--36
Approximability and the Effective Width of Probability Distributions
Alina Beygelzimer, Irina Rish
IBM Technical Report RC22558, 2002
Efficient fault diagnosis using probing
Irina Rish, Mark Brodie, Sheng Ma
Proceedings of 2002 AAAI Spring Symposium on Information Refinement and Revision for Decision Making: Modeling for Diagnostics, Prognostics, and Prediction, Stanford, Palo Alto
Intelligent probing: a Cost-Efficient Approach to Fault Diagnosis in Computer Networks
I. Rish, M. Brodie, S. Ma
IBM Systems Journal, 41(3), pp 372-385 41(3), 372--385, 2002
On the importance of using treewidth as a model-selection criterion for learning Bayesian networks
A. Beygelzimer, I. Rish
Proceedings of the 7th Valencia International Meeting on Bayesian Statistics, 2002
Inference complexity as a model-selection criterion for learning bayesian networks
Alina Beygelzimer, Irina Rish
Proceedings of the Eighth International Conference on Principles of Knowledge Representation and Reasoning (KR2002), Toulouse, France, pp. 558--567, Morgan Kaufmann Publishers; 1998
Strategies for problem determination using probing
Mark Brodie, Irina Rish, Sheng Ma, Alina Beygelzimer, Natalia Odintsova
IBM Technical Report, 2002
Accuracy vs. efficiency trade-offs in probabilistic diagnosis
Irina Rish, Mark Brodie, Sheng Ma
Proceedings of AAAI-2002, Edmonton, Alberta, Canada, pp. 560--566, Menlo Park, CA; Cambridge, MA; London; AAAI Press; MIT Press; 1999
Using adaptive probing for real-time problem diagnosis in distributed computer systems
I Rish, M Brodie, S Ma, G Grabarnik, N Odintsova
Proceedings AAAI-02/KDD-02/UAI-02 workshop on Real-Time Decision Support and Diagnosis Systems, Edmonton, Alberta, Canada, 2002
2001
An analysis of data characteristics that affect naive Bayes performance
Irina Rish, Joseph Hellerstein, Thathachar Jayram
IBM Technical Report RC21993, 2001
An empirical study of the naive Bayes classifier
Irina Rish
Proceedings of IJCAI-2001 workshop on Empirical Methods in AI (also, IBM Technical Report RC22230), pp. 41--46
Optimizing probe selection for fault localization
Mark Brodie, Irina Rish, Sheng Ma
Proceedings of Distributed Systems Operation and Management (DSOM-2001)
A unified framework for evaluation metrics in classification using decision trees
Ricardo Vilalta, Mark Brodie, Daniel Oblinger, Irina Rish
Machine Learning: ECML 2001, pp. 503--514, Springer
Efficient fault diagnosis using local inference
I. Rish, M. Brodie, H. Wang, S. Ma
IBM Technical Report RC22229, 2001
2000
Advances in Bayesian Learning.
I. Rish
Proceedings of the 2000 International Conference on Artificial Intelligence (IC-AI'2000), Las Vegas, Nevada
Resolution vs. search; Two strategies for SAT
I. Rish, R. Dechter
Journal of Automated Reasoning, 24(1/2), pp.225-275, 2000
Recognizing end-user transactions in performance management
Joseph L Hellerstein, TS Jayram, Irina Rish, others
Proceedings of AAAI-2000, Austin, Texas, pp. 596--602, IBM TJ Watson Research Center
1999
Efficient reasoning in graphical models
Irina Rish
Ph.D. thesis, Information and Computer Science, University of California, Irvine, 1999
1998
On the impact of causal independence
Irina Rish, Rina Dechter
In Proceedings of 1998 AAAI Spring Symposium on Interactive and Mixed-Initiative Decision-Theoretic Systems, Technical report, Dept. Information and Computer Science, UCI
Empirical evaluation of approximation algorithms for probabilistic decoding
Irina Rish, Kalev Kask, Rina Dechter
Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence, pp. 455--463, 1998
1997
Summarizing CSP hardness with continuous probability distributions
Daniel Frost, Irina Rish, Lluis Vila
Proceedings of the Fourteenth National Conference on Artificial Intelligence (AAAI-97), pp. 327--333, Citeseer, 1997
Statistical analysis of backtracking on inconsistent CSPs
Irina Rish, Daniel Frost
Principles and Practice of Constraint Programming-CP97, pp. 150--162, Springer, 1997
A scheme for approximating probabilistic inference
Rind Dechter, Irina Rish
Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence, pp. 132--141, 1997
1996
Value iteration and policy iteration algorithms for Markov decision problem
Elena Pashenkova, Irina Rish, Rina Dechter
AAAI’96: Workshop on Structural Issues in Planning and Temporal Reasoning, Citeseer, 1996
Variable Independence in Markov Decision Problems
Irina Rish, Rina Dechter
Proceedings of AAAI-96 Workshop on Structural Issues in Planning and Temporal Reasoning, Portland, Oregon, 1996
To Guess or to Think? Hybrid Algorithms for SAT (Extended Abstract; full version TR attached)
I. Rish, R. Dechter
Proceedings of the International Conference on Principles and Practice of Constraint Programming (CP96), Cambridge, Massachusetts, 1996
1994
Empirical evaluation of two versions of the Davis-Putnam algorithm
Rina Dechter, Irina Rish
Proceedings of the AAAI-94 Workshop on Experimental Evaluation of Reasoning and Search Methods, Seattle, Washington, Citeseer, 1994
Directional Resolution: The Davis-Putnam Procedure, Revisited.
R. Dechter, I. Rish
Proceedings of the International Conference on Principles of Knowledge Representation and Reasoning (KR-94), pp. 134-145, 1994