Google
Google Scholar
MS Academic
CiteSeerX
CORE
Semantic ScholarIrina Rish
Person information
- affiliation: IBM Research
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2010 – today
- 2018
[c40]Sahil Garg, Guillermo A. Cecchi, Irina Rish, Shuyang Gao, Greg Ver Steeg, Sarik Ghazarian, Palash Goyal, Aram Galstyan:
Dialogue Modeling Via Hash Functions. LaCATODA@IJCAI 2018: 24-36- [i15]Baihan Lin, Guillermo A. Cecchi, Djallel Bouneffouf, Irina Rish:
Adaptive Representation Selection in Contextual Bandit with Unlabeled History. CoRR abs/1802.00981 (2018) - [i14]German Abrevaya, Aleksandr Y. Aravkin, Guillermo A. Cecchi, Irina Rish, Pablo Polosecki, Peng Zheng, Silvina Ponce Dawson:
Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM. CoRR abs/1805.09874 (2018) - [i13]Anna Choromanska, Sadhana Kumaravel, Ronny Luss, Irina Rish, Brian Kingsbury, Ravi Tejwani, Djallel Bouneffouf:
Beyond Backprop: Alternating Minimization with co-Activation Memory. CoRR abs/1806.09077 (2018) - [i12]Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, Gerald Tesauro:
Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference. CoRR abs/1810.11910 (2018) - 2017
- [j10]Guillermo A. Cecchi, Viatcheslav Gurev, Steve Heisig, Raquel Norel, Irina Rish, Samantha R. Schrecke:
Computing the structure of language for neuropsychiatric evaluation. IBM Journal of Research and Development 61(2/3): 1 (2017) - [j9]Irina Rish, Guillermo A. Cecchi:
Holographic brain: Distributed versus local activation patterns in fMRI. IBM Journal of Research and Development 61(2/3): 3 (2017) - [j8]Pablo Polosecki, Eduardo Castro, Andrew Wood, John H. Warner, Irina Rish, Guillermo A. Cecchi:
Computational psychiatry: Advancing predictive modeling of neurodegeneration with neuroimaging of Huntington's disease. IBM Journal of Research and Development 61(2/3): 4 (2017) - [c39]Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi:
Bandit Models of Human Behavior: Reward Processing in Mental Disorders. AGI 2017: 237-248 - [c38]Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi, Raphaël Féraud:
Context Attentive Bandits: Contextual Bandit with Restricted Context. IJCAI 2017: 1468-1475 - [c37]Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurelie C. Lozano:
Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. IJCAI 2017: 1696-1702 - [i11]Sahil Garg, Irina Rish, Guillermo A. Cecchi, Aurélie C. Lozano:
Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World. CoRR abs/1701.06106 (2017) - [i10]Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi, Raphaël Féraud:
Context Attentive Bandits: Contextual Bandit with Restricted Context. CoRR abs/1705.03821 (2017) - [i9]Djallel Bouneffouf, Irina Rish, Guillermo A. Cecchi:
Bandit Models of Human Behavior: Reward Processing in Mental Disorders. CoRR abs/1706.02897 (2017) - [i8]Sahil Garg, Aram Galstyan, Irina Rish, Guillermo A. Cecchi, Shuyang Gao:
Efficient Representation for Natural Language Processing via Kernelized Hashcodes. CoRR abs/1711.04044 (2017) - [i7]Jumana Dakka, Pouya Bashivan, Mina Gheiratmand, Irina Rish, Shantenu Jha, Russell Greiner:
Learning Neural Markers of Schizophrenia Disorder Using Recurrent Neural Networks. CoRR abs/1712.00512 (2017) - 2016
- [j7]Dan He, Irina Rish, David Haws, Laxmi Parida:
MINT: Mutual Information Based Transductive Feature Selection for Genetic Trait Prediction. IEEE/ACM Trans. Comput. Biology Bioinform. 13(3): 578-583 (2016) - [e2]Irina Rish, Georg Langs, Leila Wehbe, Guillermo A. Cecchi, Kai-min Kevin Chang, Brian Murphy:
Machine Learning and Interpretation in Neuroimaging - 4th International Workshop, MLINI 2014, Held at NIPS 2014, Montreal, QC, Canada, December 13, 2014, Revised Selected Papers. Lecture Notes in Computer Science 9444, Springer 2016, ISBN 978-3-319-45173-2 [contents] - [i6]Pouya Bashivan, Irina Rish, Steve Heisig:
Mental State Recognition via Wearable EEG. CoRR abs/1602.00985 (2016) - 2015
- [i5]Pouya Bashivan, Irina Rish, Mohammed Yeasin, Noel Codella:
Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks. CoRR abs/1511.06448 (2015) - 2014
- [c36]
- 2013
- [c35]
- [i4]Irina Rish, Kalev Kask, Rina Dechter:
Empirical Evaluation of Approximation Algorithms for Probabilistic Decoding. CoRR abs/1301.7409 (2013) - [i3]Rina Dechter, Irina Rish:
A Scheme for Approximating Probabilistic Inference. CoRR abs/1302.1534 (2013) - [i2]Dan He, Irina Rish, David Haws, Simon Teyssedre, Zivan Karaman, Laxmi Parida:
MINT: Mutual Information based Transductive Feature Selection for Genetic Trait Prediction. CoRR abs/1310.1659 (2013) - 2012
- [j6]Guillermo A. Cecchi, Lejian Huang, Javeria Ali Hashmi, Marwan N. Baliki, María V. Centeno, Irina Rish, A. Vania Apkarian:
Predictive Dynamics of Human Pain Perception. PLoS Computational Biology 8(10) (2012) - [c34]Irina Rish, Guillermo A. Cecchi, Kyle Heuton, Marwan N. Baliki, A. Vania Apkarian:
Sparse regression analysis of task-relevant information distribution in the brain. Medical Imaging: Image Processing 2012: 831412 - [c33]Jean Honorio, Dimitris Samaras, Irina Rish, Guillermo A. Cecchi:
Variable Selection for Gaussian Graphical Models. AISTATS 2012: 538-546 - [e1]Georg Langs, Irina Rish, Moritz Grosse-Wentrup, Brian Murphy:
Machine Learning and Interpretation in Neuroimaging - International Workshop, MLINI 2011, Held at NIPS 2011, Sierra Nevada, Spain, December 16-17, 2011, Revised Selected and Invited Contributions. Lecture Notes in Computer Science 7263, Springer 2012, ISBN 978-3-642-34712-2 [contents] - [i1]Alice X. Zheng, Irina Rish, Alina Beygelzimer:
Efficient Test Selection in Active Diagnosis via Entropy Approximation. CoRR abs/1207.1418 (2012) - 2010
- [c32]Irina Rish, Guillermo A. Cecchi, Marwan N. Baliki, A. Vania Apkarian:
Sparse Regression Models of Pain Perception. Brain Informatics 2010: 212-223 - [c31]Katya Scheinberg, Irina Rish, Narges Bani Asadi:
Sparse Markov net learning with priors on regularization parameters. ISAIM 2010 - [c30]Katya Scheinberg, Irina Rish:
Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach. ECML/PKDD (3) 2010: 196-212
2000 – 2009
- 2009
- [j5]Melissa K. Carroll, Guillermo A. Cecchi, Irina Rish, Rahul Garg, A. Ravishankar Rao:
Prediction and interpretation of distributed neural activity with sparse models. NeuroImage 44(1): 112-122 (2009) - [c29]Narges Bani Asadi, Irina Rish, Katya Scheinberg, Dimitri Kanevsky, Bhuvana Ramabhadran:
Map approach to learning sparse Gaussian Markov networks. ICASSP 2009: 1721-1724 - [c28]Guillermo A. Cecchi, Irina Rish, Benjamin Thyreau, Bertrand Thirion, Marion Plaze, Marie-Laure Paillère-Martinot, Catherine Martelli, Jean-Luc Martinot, Jean-Baptiste Poline:
Discriminative Network Models of Schizophrenia. NIPS 2009: 252-260 - 2008
- [c27]Irina Rish, Genady Grabarnik, Guillermo A. Cecchi, Francisco Pereira, Geoffrey J. Gordon:
Closed-form supervised dimensionality reduction with generalized linear models. ICML 2008: 832-839 - [c26]Irina Rish, Gerald Tesauro:
Active Collaborative Prediction with Maximum Margin Matrix Factorization. ISAIM 2008 - 2007
- [c25]Alina Beygelzimer, Jeffrey O. Kephart, Irina Rish:
Evaluation of Optimization Methods for Network Bottleneck Diagnosis. ICAC 2007: 20 - [c24]Irina Rish, Gerald Tesauro:
Estimating End-to-End Performance by Collaborative Prediction with Active Sampling. Integrated Network Management 2007: 294-303 - [c23]Gaurav Chandalia, Irina Rish:
Blind source separation approach to performance diagnosis and dependency discovery. Internet Measurement Conference 2007: 259-264 - [c22]Natalia Odintsova, Irina Rish:
Empirical Study of Topology Effects on Diagnosis in Computer Networks. MASS 2007: 1-6 - 2006
- [c21]
- 2005
- [j4]Irina Rish, Mark Brodie, Sheng Ma, Natalia Odintsova, Alina Beygelzimer, Genady Grabarnik, Karina Hernandez:
Adaptive diagnosis in distributed systems. IEEE Trans. Neural Networks 16(5): 1088-1109 (2005) - [c20]Alina Beygelzimer, Mark Brodie, Sheng Ma, Irina Rish:
Test-based diagnosis: tree and matrix representations. Integrated Network Management 2005: 529-542 - [c19]Alina Beygelzimer, Emre Erdogan, Sheng Ma, Irina Rish:
Statictical Models for Unequally Spaced Time Series. SDM 2005: 626-630 - [c18]Alice X. Zheng, Irina Rish, Alina Beygelzimer:
Efficient Test Selection in Active Diagnosis via Entropy Approximation. UAI 2005: 675- - 2004
- [c17]Alina Beygelzimer, Geoffrey Grinstein, Ralph Linsker, Irina Rish:
Improving Network Robustness. ICAC 2004: 322-323 - [c16]Irina Rish, Mark Brodie, Natalia Odintsova, Sheng Ma, Genady Grabarnik:
Real-time problem determination in distributed systems using active probing. NOMS (1) 2004: 133-146 - 2003
- [j3]Rina Dechter, Irina Rish:
Mini-buckets: A general scheme for bounded inference. J. ACM 50(2): 107-153 (2003) - [c15]Ricardo Vilalta, Irina Rish:
A Decomposition of Classes via Clustering to Explain and Improve Naive Bayes. ECML 2003: 444-455 - [c14]Mark Brodie, Irina Rish, Sheng Ma, Natalia Odintsova:
Active Probing Strategies for Problem Diagnosis in Distributed Systems. IJCAI 2003: 1337-1338 - [c13]Ramendra K. Sahoo, Adam J. Oliner, Irina Rish, Manish Gupta, José E. Moreira, Sheng Ma, Ricardo Vilalta, Anand Sivasubramaniam:
Critical event prediction for proactive management in large-scale computer clusters. KDD 2003: 426-435 - [c12]
- 2002
- [j2]Mark Brodie, Irina Rish, Sheng Ma:
Intelligent probing: A cost-effective approach to fault diagnosis in computer networks. IBM Systems Journal 41(3): 372-385 (2002) - [c11]Irina Rish, Mark Brodie, Sheng Ma:
Accuracy vs. Efficiency Trade-offs in Probabilistic Diagnosis. AAAI/IAAI 2002: 560-566 - [c10]Alina Beygelzimer, Irina Rish:
Inference Complexity as a Model-Selection Criterion for Learning Bayesian Networks. KR 2002: 558-567 - 2001
- [c9]Mark Brodie, Irina Rish, Sheng Ma:
Optimizing Probe Selection for Fault Localization. DSOM 2001: 88-98 - [c8]Ricardo Vilalta, Mark Brodie, Daniel Oblinger, Irina Rish:
A Unified Framework for Evaluation Metrics in Classification Using Decision Trees. ECML 2001: 503-514 - 2000
- [j1]Irina Rish, Rina Dechter:
Resolution versus Search: Two Strategies for SAT. J. Autom. Reasoning 24(1/2): 225-275 (2000) - [c7]Joseph L. Hellerstein, T. S. Jayram, Irina Rish:
Recognizing End-User Transactions in Performance Management. AAAI/IAAI 2000: 596-602
1990 – 1999
- 1998
- [c6]Irina Rish, Kalev Kask, Rina Dechter:
Empirical Evaluation of Approximation Algorithms for Probabilistic Decoding. UAI 1998: 455-463 - 1997
- [c5]Daniel Frost, Irina Rish, Lluís Vila:
Summarizing CSP Hardness with Continuous Probability Distributions. AAAI/IAAI 1997: 327-333 - [c4]Irina Rish, Daniel Frost:
Statistical Analysis of Backtracking on Inconsistent CSPs. CP 1997: 150-162 - [c3]
- 1996
- [c2]Irina Rish, Rina Dechter:
To Guess or to Think? Hybrid Algorithms for SAT (Extended Abstract). CP 1996: 555-556 - 1994
- [c1]Rina Dechter, Irina Rish:
Directional Resolution: The Davis-Putnam Procedure, Revisited. KR 1994: 134-145
Coauthor Index
maintained by 
, founded at 
, founded at 
last updated on 2018-12-25 18:45 CET by the dblp team
data released under the ODC-BY 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
the dblp computer science bibliography is funded by:
