Publications

2009

Journals:

• M.K. Carroll, G.A.Cecchi, I. Rish, R. Garg, A.R. Rao. Prediction and Interpretation of Distributed Neural Activity with Sparse Models, Neuroimage 44(1):112-22, 2009.

Conferences and Workshops:

• G. Cecchi, I. Rish, B. Thyreau, B. Thirion, M. Plaze, MLPaillere-Martinot, C.Martelli, JLMartinot, JBPoline. Discriminiative Network Models of Schizophrenia (supplemental material can be found here) in Proceedings of NIPS 2009, Vancouver, BC, Canada, December 2009.
• I. Rish, G. Grabarnik.Sparse Signal Recovery with Exponential-Family Noise, in Proceedings of Allerton 2009, Monticello, IL, September 2009.
• N. Bani Asadi, I. Rish, K. Scheinberg, D. Kanevsky, B. Ramabhadran. A MAP Approach to Learning Sparse Gaussian Markov Networks, in Proceedings of ICASSP 2009, Taipei, Taiwan, April 2009.
• N. Bani Asadi, I. Rish, K. Scheinberg. Selecting regularization parameter in sparse MRF learning, invited paper/talk at Information Theory and Applications (ITA) Workshop, San Diego, Feb 2009.

Technical Reports/Preprints:

• K. Scheinberg, N. Bani Asadi, I. Rish. Sparse MRF Learning with Priors on Regularization Parameters, IBM Technical Report RC24812. Code: SINCO, a C++/MATALB package for solving large-scale convex problems in sparse inverse covariance selection. Available from COIN-OR.

2008

Conferences and Workshops:

• I. Rish, G. Grabarnik, G. Cecchi, F. Pereira, G. Gordon. Closed-form Supervised Dimensionality Reduction with Generalized Linear Models, in Proceedings of ICML 2008, Helsinki, Finland, July 2008.
• I. Rish and G. Chandalia. Learning hidden factor models for network tomography, invited paper/talk at Information Theory and Applications (ITA) Workshop, San Diego, Feb 2008.

2007

Conferences and Workshops:

• G. Chandalia and I. Rish. Blind Source Separation Approach to Performance Diagnosis and Dependency Discovery, in Proceedings of IMC-2007, San Diego, CA, October 2007.
• I. Rish and G. Tesauro. Estimating End-to-End Performance by Collaborative Prediction with Active Sampling, in Proceedings of IM-2007, Munich, Germany, May 2007.
• A. Beygelzimer, J. Kephart and I. Rish. Evaluation of Optimization Methods for Network Bottleneck Diagnosis, in ICAC 2007.
• I. Rish and G. Tesauro. Active Collaborative Prediction with Maximum Margin Matrix Factorization, invited paper/talk at Information Theory and Applications (ITA) Workshop, San Diego, Feb 2007.

2006

Conferences and Workshops:

• A. Jakulin and I. Rish. Bayesian Learning of Markov Network Structure, in Proceedings of ECML-2006, Berlin, Germany, September 2006.
• A. Beygelzimer, M. Brodie, J. Lenchner, I. Rish, Automated Knowledge Elicitation and Flowchart Optimization for Problem Diagnosis, in UAI-06 Workshop on Applications of Bayesian Networks.
• I. Rish, Information-theoretic approaches to cost-efficient diagnosis, invited paper/talk at Information Theory and Applications (ITA) Inaugural Workshop, San Diego, Feb 2006.
• I. Rish, Active Sampling Approaches in Systems Management Applications, SysML Workshop at SIGMETRICS-06.

2005

Journals:

• I. Rish, M. Brodie, S. Ma, N. Odintsova, A. Beygelzimer, G. Grabarnik, K. Hernandez. Adaptive Diagnosis in Distributed Systems, in IEEE Transactions on Neural Networks (special issue on Adaptive Learning Systems in Communication Networks), vol. 16, no. 5, pp. 1088-1109, September 2005.
• A. Beygelzimer, R. Linsker, G. Grinstein, I. Rish. Improving Network Robustness by Edge Modification, Physica A, Vol: 357, No: 3-4, pp. 593-612, November 2005.

Conferences:

• I. Rish, Distributed Systems Diagnosis Using Belief Propagation, to appear in Proc. of the 43-d Annual Allerton Conference on Communication, Control and Computing, 2005.
• A. Zheng. I. Rish, A. Beygelzimer. Efficient Test Selection in Active Diagnosis via Entropy Approximation, in Proceedings of UAI-2005.
• N. Odintsova, I. Rish, S. Ma. Multifault Diagnosis in Dynamic Systems, in Proceedings of IM 2005. Extended version appeared as IBM Technical Report RC23385, 2004.
• A. Beygelzimer, M. Brodie, S. Ma, I. Rish. Test-based Diagnosis: Tree and Matrix Representations, in Proceedings of IM 2005.
• E. Erdogan, S. Ma, A. Beygelzimer, I. Rish. Statistical Models for Unequally Spaced Time Series, in Proceedings of SIAM DM 2005.

Technical Reports:

• A. Jakulin, I. Rish. Kikuchi-Bayes: Markov Networks for Classification, IBM Technical Report RC23602.
• N. Odintsova and I. Rish. Fault Diagnois in Scale-free versus Random Networks, IBM Technical Report RC23599.
• M. Brodie, J. Lenchner, S. Ma, I. Rish. Flowchart Learning and Optimization for Problem Diagnosis, IBM Technical Report RC23574.
• S. Guo, I. Rish, D. Loewenstern, Self-healing in large-scale systems: parallel and distributed diagnostic architectures, IBM Technical Report.

2004

Conferences:

• I. Rish, M. Brodie, N. Odintsova, S. Ma, G. Grabarnik. Real-time Problem Determination in Distributed Systems using Active Probing, in Proceedings of NOMS-2004, Seoul, Korea, April 2004.
• 1. A. Beygelzimer, G. Grinstein, R. Linsker, I. Rish, Improving Network Robustness, in Proceedings of ICAC-04.

Technical reports:

• A. Jakulin, I. Rish, I. Bratko, Kikuchi-Bayes: Factorized Models for Approximate Classification in Closed Form, IBM Technical Report RC23314, 2004.
• A. X. Zheng, I. Rish, A. Beygelzimer, Entropy Approximation for Active Fault Diagnosis, IBM Technical Report RC23441, 2004.
• M. Brodie, J. Lenchner, S. Ma, I. Rish. Flowchart Learning and Optimization for Problem Diagnosis, IBM Technical Report RC23574.
• N. Odintsova, I. Rish, S. Ma. Multifault Diagnosis in Dynamic Systems, IBM Technical Report RC23385.

 

2003
Journals:

• Dechter, R. and Rish, I. Mini-buckets: A general scheme for bounded inference, JACM 50(2): 107-153 (2003).

 

Conferences:

• R. Vilalta and  I. Rish (2003). A Decomposition Of Classes Via Clustering To Explain And Improve Naive Bayes,  in Proceedings of 14th European Conference on Machine Learning (ECML/PKDD 2003). Best paper award.
• M. Brodie, I. Rish, S. Ma, N. Odintsova (2003). Active Probing Strategies for Problem Diagnosis in Distributed Systems, in Proceedings of IJCAI-03, Acapulco, Mexico.
• R. K. Sahoo, A. J. Oliner,  I. Rish, M. Gupta, J.E. Moreira, S. Ma, R. Vilalta, A. Sivasubramaniam (2003). Critical Event Prediction for Proactive Management in Large-scale Computer Clusters,  in Proceedings of KDD-2003 (Industrial Track).
• A. Beygelzimer and I. Rish (2003). Approximability of Probability Distributions, to Proceedings of NIPS-2003.

Workshops:

• R.K. Sahoo, I. Rish, A.J. Oliner, M. Gupta, J.E. Moreira, S. Ma, R. Vilalta and A. Sivasubramaniam. Autonomic Computing Features for Large-scale Server Management and Control, in  the  IJCAI-03 workshop on AI and Autonomic Computing, August 2003, Acapulco, Mexico.
• I. Rish, M. Brodie, N. Odintsova, S. Ma, G. Grabarnik.  Problem Diagnosis in Distributed Systems using Active Probing, in the UAI-2003 workshop on Bayesian Modeling Applications, August 2003, Acapulco, Mexico.

Technical reports:

• M. Brodie, I. Rish, S. Ma, G. Grabarnik, N. Odintsova (2002). Active Probing. IBM Technical Report RC22817.

2002

Journals:

• Brodie, M., Rish, I. and Ma, S. (2002).  Intelligent probing: A Cost-Efficient Approach to Fault Diagnosis in Computer Networks,  IBM Systems Journal 41(3): 372-385.

Conferences:

• Rish, I., Brodie, M, and Ma, S. (2002). Accuracy vs. Efficiency Trade-offs in Probabilistic Diagnosis, in Proceedings of AAAI-2002, Edmonton, Alberta, Canada, August 2002.
• Beygelzimer, A. and  Rish, I. (2002). Inference complexity as a model-selection criterion for learning Bayesian networks, in Proceedings of  the  Eighth International Conference on Principles of Knowledge Representation  and Reasoning  (KR2002), Toulouse, France.

Workshops and symposiums:

• I.Rish, M. Brodie, S. Ma, G. Grabarnik, N. Odintsova (2002). Using Adaptive Probing for Real-Time Problem Diagnosis in Distributed Computer Systems, in  the AAAI-02 workshop on Real-Time Decision Support and Diagnosis Systems, Edmonton, Alberta, Canada.
• Rish, I., Brodie, M, and Ma, S. (2002). Efficient fault diagnosis using probing, in Proceedings of  2002 AAAI Spring Symposium on "Information Refinement and Revision for Decision  Making: Modeling for Diagnostics, Prognostics, and Prediction", Stanford, Palo Alto, March 25-27, 2002.
• Wang, H., Rish, I., and Ma, S. (2002). Using Sensitivity Analysis for Selective Parameter Update  in  Bayesian Network Learning, in Proceedings of  2002 AAAI Spring Symposium on "Information Refinement and Revision for Decision  Making: Modeling for Diagnostics, Prognostics, and Prediction", Stanford, Palo Alto, March 25-27, 2002.

Technical reports:

• M. Brodie, I. Rish, S. Ma, A. Beygelzimer, N. Odintsova (2002). Strategies for Problem Determination Using Probing. IBM Technical Report.
• A. Beygelzimer and I. Rish (2002). Approximability and the Effective Width of Probability Distributions, IBM Technical Report RC22558.

2001

• Brodie, M., Rish, I. and Ma, S. (2001).  Optimizing Probe Selection for Fault Localization, in Proceedings of DSOM01.
• Vilalta, R.,  Brodie, M.,  Oblinger, D., and  Rish, I. (2001). A unified framework for evaluation metrics in classification using decision trees, in Proceedings of ECML01  pp. 503-514.
• Rish,  I., (2001). An empirical study of the naive Bayes classifier,  in IJCAI-01 workshop on "Empirical Methods in AI". Also appeared as IBM Technical Report RC22230.

Technical reports:

• Rish, I.,  Brodie, M., Wang, H., and Ma, S. (2001). Efficient fault diagnosis using local inference, IBM Technical Report RC22229.
• Rish, I., Hellerstein, J.,  and Jayram, T.S. (2001). An analysis of data characteristics that affect naive Bayes performance. IBM Technical Report RC21993.

2000

• Rish, I. and  Dechter, R.(2000).  Resolution versus search; Two strategies for SAT. Journal of Automated  Reasoning, 24(1/2), pp.225-275.
• Hellerstein, J., Jayram, T.S., and Rish, I. (2000). Recognizing end-user transactions in performance management. Proceedings of AAAI-2000, pp. 596-602. Austin, Texas.
• Rish, I.(2000). Advances in Bayesian Learning. Proceedings of the 2000 International Conference on Artificial Intelligence (IC-AI'2000). Las Vegas.

1999

• PhD thesis,  Efficient Reasoning in Graphical Models , July 1999.

1998

• Rish, I.,  Kask, K., and Dechter, R.(1998).   Empirical Evaluation of Approximation Algorithms for Probabilistic Decoding. Proceedings of UAI98, Madison, Wisconsin.
• Rish, I. and Dechter, R.(1998).  On the impact of causal independence , 1998 Stanford Spring Symposium on Interactive and Mixed-Initiative Decision-Theoretic Systems. (Extended version available as a technical report ).

1997

• Rish, I. and Frost, D. (1997). Statistical Analysis of Backtracking on Inconsistent CSPs,  in Proceedings of CP97, Austria.
• Dechter, R. and Rish, I. (1997). A scheme for approximating probabilistic inference, in Proceedings of UAI-97,  Providence, Rhode Island.
• Frost, D., Rish, I. and Vila, L. (1997). Summarizing CSP hardness with continuous probability distributions,  in Proceedings of AAAI-97, pp. 327-333.

 

1994-96

• Rish, I. and  Dechter, R. (1996). To Guess or to Think? Hybrid Algorithms for SAT (ext. abstract). In Proceedings of PPCP-96. Cambridge, Massachusetts. (Full version is also available).
• Rish, I. and  Dechter, R. (1996). Variable Independence in Markov Decision Problems. In  Proceedings of AAAI-96 Workshop on Structural Issues in Planning and Temporal Reasoning. Portland, Oregon.
• Dechter, R. and Rish, I.(1994).  Directional Resolution: The Davis-Putnam Procedure, Revisited. In Proceedings of KR-94.
• Dechter, R. and Rish, I.(1994). Empirical Evaluation of Two Versions of the Davis-Putnam Algorithm. In Proceedings of AAAI-94 Workshop on Experimental Evaluation of Reasoning and Search Methods, Seattle.

Tutorials and presentations

2001

• I. Rish, Machine Learning in Systems Performance Management, presented at Distributed Systems Department meeting, January 2001.

2000

• I. Rish, Advances in Bayesian Learning, a short tutorial presented at IC-AI'2000, Las Vegas, June 2000.
• I. Rish and M. Singh,  Inference and Learning in Bayesian Networks, tutorial presented at IBM Watson Research Center, August 2000.
• I. Rish and R. Dechter, Approximation Techniques for Automated Inference, AAAI-2000 tutorial, Austin,TX, 2000.

1998

• R. Dechter and I. Rish, Principles and Methods for Automated Inference , AAAI-98 tutorial.