Irina Rish

Affiliations:
  • IBM Research


According to our database1, Irina Rish authored at least 104 papers between 1994 and 2022.

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Bibliography

2022
Foundational Models for Continual Learning: An Empirical Study of Latent Replay.
CoRR, 2022

APP: Anytime Progressive Pruning.
CoRR, 2022

WOODS: Benchmarks for Out-of-Distribution Generalization in Time Series Tasks.
CoRR, 2022

Towards Scaling Difference Target Propagation by Learning Backprop Targets.
CoRR, 2022

Gradient Masked Averaging for Federated Learning.
CoRR, 2022

A Remedy For Distributional Shifts Through Expected Domain Translation.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
Learning Brain Dynamics With Coupled Low-Dimensional Nonlinear Oscillators and Deep Recurrent Networks.
Neural Comput., 2021

Continual Learning In Environments With Polynomial Mixing Times.
CoRR, 2021

Compositional Attention: Disentangling Search and Retrieval.
CoRR, 2021

Scaling Laws for the Few-Shot Adaptation of Pre-trained Image Classifiers.
CoRR, 2021

Approximate Bayesian Optimisation for Neural Networks.
CoRR, 2021

Sequoia: A Software Framework to Unify Continual Learning Research.
CoRR, 2021

Parametric Scattering Networks.
CoRR, 2021

Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization.
CoRR, 2021

SAND-mask: An Enhanced Gradient Masking Strategy for the Discovery of Invariances in Domain Generalization.
CoRR, 2021

Continual Learning in Deep Networks: an Analysis of the Last Layer.
CoRR, 2021

Gradient Masked Federated Optimization.
CoRR, 2021

Towards Causal Federated Learning For Enhanced Robustness and Privacy.
CoRR, 2021

Understanding Continual Learning Settings with Data Distribution Drift Analysis.
CoRR, 2021

Adversarial Feature Desensitization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Toward Optimal Solution for the Context-Attentive Bandit Problem.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021


Double-Linear Thompson Sampling for Context-Attentive Bandits.
Proceedings of the IEEE International Conference on Acoustics, 2021

Toward Skills Dialog Orchestration with Online Learning.
Proceedings of the IEEE International Conference on Acoustics, 2021

2020
Towards Continual Reinforcement Learning: A Review and Perspectives.
CoRR, 2020

COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing.
CoRR, 2020

Adversarial Feature Desensitization.
CoRR, 2020

COVI White Paper.
CoRR, 2020

Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL.
CoRR, 2020

Towards Lifelong Self-Supervision For Unpaired Image-to-Image Translation.
CoRR, 2020

Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning.
CoRR, 2020

Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Survey on Applications of Multi-Armed and Contextual Bandits.
Proceedings of the IEEE Congress on Evolutionary Computation, 2020

A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

Modeling Dialogues with Hashcode Representations: A Nonparametric Approach.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Reinforcement Learning Models of Human Behavior: Reward Processing in Mental Disorders.
CoRR, 2019

A Survey on Practical Applications of Multi-Armed and Contextual Bandits.
CoRR, 2019

Continual Learning with Self-Organizing Maps.
CoRR, 2019

Predicting conversion to psychosis in clinical high risk patients using resting-state functional MRI features.
Proceedings of the Medical Imaging 2019: Biomedical Applications in Molecular, 2019

Beyond Backprop: Online Alternating Minimization with Auxiliary Variables.
Proceedings of the 36th International Conference on Machine Learning, 2019

Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference.
Proceedings of the 7th International Conference on Learning Representations, 2019

Kernelized Hashcode Representations for Relation Extraction.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Beyond Backprop: Alternating Minimization with co-Activation Memory.
CoRR, 2018

Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM.
CoRR, 2018

Adaptive Representation Selection in Contextual Bandit with Unlabeled History.
CoRR, 2018

Dialogue Modeling Via Hash Functions.
Proceedings of the Linguistic and Cognitive Approaches To Dialog Agents Workshop co-located with the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence (IJCAI-ECAI 2018), 2018

Contextual Bandit with Adaptive Feature Extraction.
Proceedings of the 2018 IEEE International Conference on Data Mining Workshops, 2018

2017
Holographic brain: Distributed versus local activation patterns in fMRI.
IBM J. Res. Dev., 2017

Computational psychiatry: Advancing predictive modeling of neurodegeneration with neuroimaging of Huntington's disease.
IBM J. Res. Dev., 2017

Computing the structure of language for neuropsychiatric evaluation.
IBM J. Res. Dev., 2017

Learning Neural Markers of Schizophrenia Disorder Using Recurrent Neural Networks.
CoRR, 2017

Efficient Representation for Natural Language Processing via Kernelized Hashcodes.
CoRR, 2017

Learning discriminative functional network features of schizophrenia.
Proceedings of the Medical Imaging 2017: Biomedical Applications in Molecular, 2017

Context Attentive Bandits: Contextual Bandit with Restricted Context.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World.
Proceedings of the 5th International Conference on Learning Representations, 2017

Bandit Models of Human Behavior: Reward Processing in Mental Disorders.
Proceedings of the Artificial General Intelligence - 10th International Conference, 2017

2016
MINT: Mutual Information Based Transductive Feature Selection for Genetic Trait Prediction.
IEEE ACM Trans. Comput. Biol. Bioinform., 2016

Learning Representations from EEG with Deep Recurrent-Convolutional Neural Networks.
Proceedings of the 4th International Conference on Learning Representations, 2016

Mental State Recognition via Wearable EEG.
CoRR, 2016

Evaluating effects of methylphenidate on brain activity in cocaine addiction: a machine-learning approach.
Proceedings of the Medical Imaging 2016: Biomedical Applications in Molecular, Structural, and Functional Imaging, San Diego, California, United States, 27 February, 2016

2014
Transductive HSIC Lasso.
Proceedings of the 2014 SIAM International Conference on Data Mining, 2014

2013
MINT: Mutual Information based Transductive Feature Selection for Genetic Trait Prediction.
CoRR, 2013

Functional MRI Analysis with Sparse Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

2012
Predictive Dynamics of Human Pain Perception.
PLoS Comput. Biol., 2012

Variable Selection for Gaussian Graphical Models.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Sparse regression analysis of task-relevant information distribution in the brain.
Proceedings of the Medical Imaging 2012: Image Processing, 2012

2010
Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

Sparse Markov net learning with priors on regularization parameters.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2010

Sparse Regression Models of Pain Perception.
Proceedings of the Brain Informatics, International Conference, 2010

2009
Prediction and interpretation of distributed neural activity with sparse models.
NeuroImage, 2009

Discriminative Network Models of Schizophrenia.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Map approach to learning sparse Gaussian Markov networks.
Proceedings of the IEEE International Conference on Acoustics, 2009

2008
Active Collaborative Prediction with Maximum Margin Matrix Factorization.
Proceedings of the International Symposium on Artificial Intelligence and Mathematics, 2008

Closed-form supervised dimensionality reduction with generalized linear models.
Proceedings of the Machine Learning, 2008

2007
Empirical Study of Topology Effects on Diagnosis in Computer Networks.
Proceedings of the IEEE 4th International Conference on Mobile Adhoc and Sensor Systems, 2007

Blind source separation approach to performance diagnosis and dependency discovery.
Proceedings of the 7th ACM SIGCOMM Internet Measurement Conference, 2007

Estimating End-to-End Performance by Collaborative Prediction with Active Sampling.
Proceedings of the Integrated Network Management, 2007

Evaluation of Optimization Methods for Network Bottleneck Diagnosis.
Proceedings of the Fourth International Conference on Autonomic Computing (ICAC'07), 2007

2006
Bayesian Learning of Markov Network Structure.
Proceedings of the Machine Learning: ECML 2006, 2006

2005
Adaptive diagnosis in distributed systems.
IEEE Trans. Neural Networks, 2005

Efficient Test Selection in Active Diagnosis via Entropy Approximation.
Proceedings of the UAI '05, 2005

Statictical Models for Unequally Spaced Time Series.
Proceedings of the 2005 SIAM International Conference on Data Mining, 2005

Test-based diagnosis: tree and matrix representations.
Proceedings of the Integrated Network Management, 2005

2004
Real-time problem determination in distributed systems using active probing.
Proceedings of the Managing Next Generation Convergence Networks and Services, 2004

Improving Network Robustness.
Proceedings of the 1st International Conference on Autonomic Computing (ICAC 2004), 2004

2003
Mini-buckets: A general scheme for bounded inference.
J. ACM, 2003

Approximability of Probability Distributions.
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003

Critical event prediction for proactive management in large-scale computer clusters.
Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 24, 2003

Active Probing Strategies for Problem Diagnosis in Distributed Systems.
Proceedings of the IJCAI-03, 2003

A Decomposition of Classes via Clustering to Explain and Improve Naive Bayes.
Proceedings of the Machine Learning: ECML 2003, 2003

2002
Intelligent probing: A cost-effective approach to fault diagnosis in computer networks.
IBM Syst. J., 2002

Inference Complexity as a Model-Selection Criterion for Learning Bayesian Networks.
Proceedings of the Eights International Conference on Principles and Knowledge Representation and Reasoning (KR-02), 2002

Accuracy vs. Efficiency Trade-offs in Probabilistic Diagnosis.
Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002

2001
A Unified Framework for Evaluation Metrics in Classification Using Decision Trees.
Proceedings of the Machine Learning: EMCL 2001, 2001

Optimizing Probe Selection for Fault Localization.
Proceedings of the Operations & Management, 2001

2000
Resolution versus Search: Two Strategies for SAT.
J. Autom. Reason., 2000

Recognizing End-User Transactions in Performance Management.
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on on Innovative Applications of Artificial Intelligence, July 30, 2000

1998
Empirical Evaluation of Approximation Algorithms for Probabilistic Decoding.
Proceedings of the UAI '98: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, 1998

1997
A Scheme for Approximating Probabilistic Inference.
Proceedings of the UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, 1997

Statistical Analysis of Backtracking on Inconsistent CSPs.
Proceedings of the Principles and Practice of Constraint Programming - CP97, Third International Conference, Linz, Austria, October 29, 1997

Summarizing CSP Hardness with Continuous Probability Distributions.
Proceedings of the Fourteenth National Conference on Artificial Intelligence and Ninth Innovative Applications of Artificial Intelligence Conference, 1997

1996
To Guess or to Think? Hybrid Algorithms for SAT (Extended Abstract).
Proceedings of the Second International Conference on Principles and Practice of Constraint Programming, 1996

1994
Directional Resolution: The Davis-Putnam Procedure, Revisited.
Proceedings of the 4th International Conference on Principles of Knowledge Representation and Reasoning (KR'94). Bonn, 1994


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