Robi Polikar

Orcid: 0000-0002-2739-4228

According to our database1, Robi Polikar authored at least 99 papers between 1999 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Adversary Aware Continual Learning.
IEEE Access, 2024

2023
Semi-Supervised and Incremental Sequence Analysis for Taxonomic Classification.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2023

2022
Contributor-Aware Defenses Against Adversarial Backdoor Attacks.
CoRR, 2022

False Memory Formation in Continual Learners Through Imperceptible Backdoor Trigger.
CoRR, 2022

Semi-supervised and Incremental VSEARCH for Metagenomic Classification.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2022

2021
Rethinking Noisy Label Models: Labeler-Dependent Noise with Adversarial Awareness.
CoRR, 2021

Incremental and Semi-Supervised Learning of 16S-rRNA Genes For Taxonomic Classification.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Incremental & Semi-Supervised Learning for Functional Analysis of Protein Sequences.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Adversarial Targeted Forgetting in Regularization and Generative Based Continual Learning Models.
Proceedings of the International Joint Conference on Neural Networks, 2021

OpinionRank: Extracting Ground Truth Labels from Unreliable Expert Opinions with Graph-Based Spectral Ranking.
Proceedings of the International Joint Conference on Neural Networks, 2021

2020
Comparative Analysis of Extreme Verification Latency Learning Algorithms.
CoRR, 2020

Targeted Forgetting and False Memory Formation in Continual Learners through Adversarial Backdoor Attacks.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Trajectory design of an Aircraft for Circular Motion.
Proceedings of the 16th IEEE International Conference on Control & Automation, 2020

2019
Vulnerability of Covariate Shift Adaptation Against Malicious Poisoning Attacks.
Proceedings of the International Joint Conference on Neural Networks, 2019

2018
A Sequential Learning Approach for Scaling Up Filter-Based Feature Subset Selection.
IEEE Trans. Neural Networks Learn. Syst., 2018

Extensions to Online Feature Selection Using Bagging and Boosting.
IEEE Trans. Neural Networks Learn. Syst., 2018

Adversarial Poisoning of Importance Weighting in Domain Adaptation.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2018

Resampling Techniques for Learning Under Extreme Verification Latency with Class Imbalance.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

Attack Strength vs. Detectability Dilemma in Adversarial Machine Learning.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

2017
LEVELIW: Learning extreme verification latency with importance weighting.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2016
Learning under extreme verification latency quickly: FAST COMPOSE.
Proceedings of the 2016 IEEE Symposium Series on Computational Intelligence, 2016

Non-negative matrix factorization for non-parametric and unsupervised image clustering and segmentation.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

2015
A Bootstrap Based Neyman-Pearson Test for Identifying Variable Importance.
IEEE Trans. Neural Networks Learn. Syst., 2015

Learning in Nonstationary Environments: A Survey.
IEEE Comput. Intell. Mag., 2015

Quantifying the limited and gradual concept drift assumption.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015

Constrained state estimation in particle filters.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Inductive learning based on rough set theory for medical decision making.
Proceedings of the 2015 IEEE International Conference on Fuzzy Systems, 2015

2014
Guest Editorial Learning in Nonstationary and Evolving Environments.
IEEE Trans. Neural Networks Learn. Syst., 2014

COMPOSE: A Semisupervised Learning Framework for Initially Labeled Nonstationary Streaming Data.
IEEE Trans. Neural Networks Learn. Syst., 2014

Optimal Bayesian classification in nonstationary streaming environments.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Domain adaptation bounds for multiple expert systems under concept drift.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Core support extraction for learning from initially labeled nonstationary environments using COMPOSE.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014

Scaling a neyman-pearson subset selection approach via heuristics for mining massive data.
Proceedings of the 2014 IEEE Symposium on Computational Intelligence and Data Mining, 2014

2013
Incremental Learning of Concept Drift from Streaming Imbalanced Data.
IEEE Trans. Knowl. Data Eng., 2013

A freshman level module in biometric systems.
Proceedings of the 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013), 2013

Incremental learning of new classes from unbalanced data.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

Active learning in nonstationary environments.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013

Discounted expert weighting for concept drift.
Proceedings of the 2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, 2013

2012
Learning from streaming data with concept drift and imbalance: an overview.
Prog. Artif. Intell., 2012

Open-ended design and performance evaluation of a biometric speaker identification system.
Proceedings of the 2012 IEEE International Symposium on Circuits and Systems, 2012

Semi-supervised learning in initially labeled non-stationary environments with gradual drift.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Transductive learning algorithms for nonstationary environments.
Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN), 2012

Forensic identification with environmental samples.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

Information theoretic feature selection for high dimensional metagenomic data.
Proceedings of the Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, 2012

2011
Incremental Learning of Concept Drift in Nonstationary Environments.
IEEE Trans. Neural Networks, 2011

Editorial: One Year as EiC, and Editorial-Board Changes at TNN.
IEEE Trans. Neural Networks, 2011

Information-theoretic approaches to SVM feature selection for metagenome read classification.
Comput. Biol. Chem., 2011

Semi-supervised learning in nonstationary environments.
Proceedings of the 2011 International Joint Conference on Neural Networks, 2011

Heuristic Updatable Weighted Random Subspaces for Non-stationary Environments.
Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Analysis of complexity based EEG features for the diagnosis of Alzheimer's disease.
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011

Ordering samples along environmental gradients using particle swarm optimization.
Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011

Hellinger distance based drift detection for nonstationary environments.
Proceedings of the 2011 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, 2011

2010
Learn<sup>++</sup>.MF: A random subspace approach for the missing feature problem.
Pattern Recognit., 2010

Incremental Learning of New Classes in Unbalanced Datasets: Learn<sup> + + </sup>.UDNC.
Proceedings of the Multiple Classifier Systems, 9th International Workshop, 2010

Neural network-based taxonomic clustering for metagenomics.
Proceedings of the International Joint Conference on Neural Networks, 2010

An ensemble based incremental learning framework for concept drift and class imbalance.
Proceedings of the International Joint Conference on Neural Networks, 2010

An Incremental Learning Algorithm for Non-stationary Environments and Class Imbalance.
Proceedings of the 20th International Conference on Pattern Recognition, 2010

Optimal nu-SVM parameter estimation using multi objective evolutionary algorithms.
Proceedings of the IEEE Congress on Evolutionary Computation, 2010

Fusion methods for boosting performance of speaker identification systems.
Proceedings of the IEEE Asia Pacific Conference on Circuits and Systems, 2010

2009
Learn<sup>++</sup>.NC: Combining Ensemble of Classifiers With Dynamically Weighted Consult-and-Vote for Efficient Incremental Learning of New Classes.
IEEE Trans. Neural Networks, 2009

Ensemble learning.
Scholarpedia, 2009

Incremental Learning of Variable Rate Concept Drift.
Proceedings of the Multiple Classifier Systems, 8th International Workshop, 2009

Incremental learning in nonstationary environments with controlled forgetting.
Proceedings of the International Joint Conference on Neural Networks, 2009

Functional Near-Infrared Spectroscopy and Electroencephalography: A Multimodal Imaging Approach.
Proceedings of the Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience, 2009

2008
Local Classifier Weighting by Quadratic Programming.
IEEE Trans. Neural Networks, 2008

An ensemble based data fusion approach for early diagnosis of Alzheimer's disease.
Inf. Fusion, 2008

Metagenome Fragment Classification Using N-Mer Frequency Profiles.
Adv. Bioinformatics, 2008

Learning concept drift in nonstationary environments using an ensemble of classifiers based approach.
Proceedings of the International Joint Conference on Neural Networks, 2008

Incremental learning in non-stationary environments with concept drift using a multiple classifier based approach.
Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

Nearest hyperdisk methods for high-dimensional classification.
Proceedings of the Machine Learning, 2008

Margin-based discriminant dimensionality reduction for visual recognition.
Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008

2007
An Ensemble-Based Incremental Learning Approach to Data Fusion.
IEEE Trans. Syst. Man Cybern. Part B, 2007

Bootstrap - Inspired Techniques in Computation Intelligence.
IEEE Signal Process. Mag., 2007

Comparative multiresolution wavelet analysis of ERP spectral bands using an ensemble of classifiers approach for early diagnosis of Alzheimer's disease.
Comput. Biol. Medicine, 2007

An Ensemble Approach for Incremental Learning in Nonstationary Environments.
Proceedings of the Multiple Classifier Systems, 7th International Workshop, 2007

Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features.
Proceedings of the Multiple Classifier Systems, 7th International Workshop, 2007

Random Feature Subset Selection for Analysis of Data with Missing Features.
Proceedings of the International Joint Conference on Neural Networks, 2007

Ensemble Based Data Fusion from Parietal Region Event Related Potentials for Early Diagnosis of Alzheimer's Disease.
Proceedings of the International Joint Conference on Neural Networks, 2007

2006
Comparison of Ensemble Techniques for Incremental Learning of New Concept Classes under Hostile Non-stationary Environments.
Proceedings of the IEEE International Conference on Systems, 2006

Ensemble Techniques with Weighted Combination Rules for Early Diagnosis of Alzheimer's Disease.
Proceedings of the International Joint Conference on Neural Networks, 2006

Majority Vote and Decision Template Based Ensemble Classifiers Trained on Event Related Potentials for Early Diagnosis of Alzheimer's Disease.
Proceedings of the 2006 IEEE International Conference on Acoustics Speech and Signal Processing, 2006

Can AdaBoost.M1 Learn Incrementally? A Comparison to Learn<sup>++</sup> Under Different Combination Rules.
Proceedings of the Artificial Neural Networks, 2006

Stacked Generalization for Early Diagnosis of Alzheimer's Disease.
Proceedings of the 28th International Conference of the IEEE Engineering in Medicine and Biology Society, 2006

2005
An architecture for intelligent systems based on smart sensors.
IEEE Trans. Instrum. Meas., 2005

Ensemble Confidence Estimates Posterior Probability.
Proceedings of the Multiple Classifier Systems, 6th International Workshop, 2005

Ensemble of SVMs for Incremental Learning.
Proceedings of the Multiple Classifier Systems, 6th International Workshop, 2005

Classification of Volatile Organic Compounds with Incremental SVMs and RBF Networks.
Proceedings of the Computer and Information Sciences, 2005

Multiresolution wavelet analysis and ensemble of classifiers for early diagnosis of Alzheimer's disease.
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005

Reducing the Effect of Out-Voting Problem in Ensemble Based Incremental Support Vector Machines.
Proceedings of the Artificial Neural Networks: Formal Models and Their Applications, 2005

2004
Combining classifiers for multisensor data fusion.
Proceedings of the IEEE International Conference on Systems, 2004

Learn++.MT: A New Approach to Incremental Learning.
Proceedings of the Multiple Classifier Systems, 5th International Workshop, 2004

2003
An Ensemble Approach for Data Fusion with Learn++.
Proceedings of the Multiple Classifier Systems, 4th International Workshop, 2003

Confidence Estimation Using the Incremental Learning Algorithm, Learn++.
Proceedings of the Artificial Neural Networks and Neural Information Processing, 2003

2001
Learn++: an incremental learning algorithm for supervised neural networks.
IEEE Trans. Syst. Man Cybern. Part C, 2001

Detection and identification of odorants using an electronic nose.
Proceedings of the IEEE International Conference on Acoustics, 2001

Adaptive noise cancellation schemes for magnetic flux leakage signals obtained from gas pipeline inspection.
Proceedings of the IEEE International Conference on Acoustics, 2001

2000
Fuzzy ARTMAP network with evolutionary learning.
Proceedings of the IEEE International Conference on Acoustics, 2000

LEARN++: an incremental learning algorithm for multilayer perceptron networks.
Proceedings of the IEEE International Conference on Acoustics, 2000

1999
Nonlinear cluster transformations for increasing pattern separability.
Proceedings of the International Joint Conference Neural Networks, 1999


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