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Robi Polikar
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2020 – today
- 2023
- [c73]Adriana Fasino, Emrecan Ozdogan, Bahrad A. Sokhansanj
, Gail Rosen
, Robi Polikar
:
Semi-Supervised and Incremental Sequence Analysis for Taxonomic Classification. SSCI 2023: 1132-1138 - [i9]Muhammad Umer, Robi Polikar:
Adversary Aware Continual Learning. CoRR abs/2304.14483 (2023) - 2022
- [c72]Emrecan Ozdogan, Adriana Fasino, Rachel Nguyen, Bahrad A. Sokhansanj
, Gail Rosen
, Robi Polikar
:
Semi-supervised and Incremental VSEARCH for Metagenomic Classification. SSCI 2022: 1119-1126 - [i8]Muhammad Umer, Robi Polikar:
False Memory Formation in Continual Learners Through Imperceptible Backdoor Trigger. CoRR abs/2202.04479 (2022) - [i7]Glenn Dawson, Muhammad Umer, Robi Polikar:
Contributor-Aware Defenses Against Adversarial Backdoor Attacks. CoRR abs/2206.03583 (2022) - 2021
- [c71]Glenn Dawson, Robi Polikar:
OpinionRank: Extracting Ground Truth Labels from Unreliable Expert Opinions with Graph-Based Spectral Ranking. IJCNN 2021: 1-8 - [c70]Muhammad Umer, Robi Polikar:
Adversarial Targeted Forgetting in Regularization and Generative Based Continual Learning Models. IJCNN 2021: 1-8 - [c69]Mali Halac, Bahrad A. Sokhansanj, William L. Trimble, Thomas Coard, Norman C. Sabin, Emrecan Ozdogan, Robi Polikar, Gail L. Rosen:
Incremental & Semi-Supervised Learning for Functional Analysis of Protein Sequences. SSCI 2021: 1-8 - [c68]Emrecan Ozdogan, Norman C. Sabin, Thomas Gracie, Steven Portley, Mali Halac, Thomas Coard, William L. Trimble, Bahrad A. Sokhansanj
, Gail Rosen
, Robi Polikar
:
Incremental and Semi-Supervised Learning of 16S-rRNA Genes For Taxonomic Classification. SSCI 2021: 1-7 - [i6]Glenn Dawson, Robi Polikar:
OpinionRank: Extracting Ground Truth Labels from Unreliable Expert Opinions with Graph-Based Spectral Ranking. CoRR abs/2102.05884 (2021) - [i5]Muhammad Umer, Robi Polikar:
Adversarial Targeted Forgetting in Regularization and Generative Based Continual Learning Models. CoRR abs/2102.08355 (2021) - [i4]Glenn Dawson, Robi Polikar:
Rethinking Noisy Label Models: Labeler-Dependent Noise with Adversarial Awareness. CoRR abs/2105.14083 (2021) - 2020
- [c67]Nicholas DeCicco, Kristine Napolitano, Russell Trafford, Petia Georgieva
, Nidhal Bouaynaya, Robi Polikar:
Trajectory design of an Aircraft for Circular Motion. ICCA 2020: 373-377 - [c66]Muhammad Umer, Glenn Dawson, Robi Polikar:
Targeted Forgetting and False Memory Formation in Continual Learners through Adversarial Backdoor Attacks. IJCNN 2020: 1-8 - [i3]Muhammad Umer, Glenn Dawson, Robi Polikar:
Targeted Forgetting and False Memory Formation in Continual Learners through Adversarial Backdoor Attacks. CoRR abs/2002.07111 (2020) - [i2]Muhammad Umer, Robi Polikar:
Comparative Analysis of Extreme Verification Latency Learning Algorithms. CoRR abs/2011.14917 (2020)
2010 – 2019
- 2019
- [c65]Muhammad Umer, Christopher Frederickson, Robi Polikar:
Vulnerability of Covariate Shift Adaptation Against Malicious Poisoning Attacks. IJCNN 2019: 1-8 - 2018
- [j22]Gregory Ditzler
, Robi Polikar
, Gail Rosen
:
A Sequential Learning Approach for Scaling Up Filter-Based Feature Subset Selection. IEEE Trans. Neural Networks Learn. Syst. 29(6): 2530-2544 (2018) - [j21]Gregory Ditzler
, Joseph LaBarck, James Ritchie
, Gail Rosen
, Robi Polikar
:
Extensions to Online Feature Selection Using Bagging and Boosting. IEEE Trans. Neural Networks Learn. Syst. 29(9): 4504-4509 (2018) - [c64]Christopher Frederickson, Michael Moore, Glenn Dawson, Robi Polikar:
Attack Strength vs. Detectability Dilemma in Adversarial Machine Learning. IJCNN 2018: 1-8 - [c63]Christopher Frederickson, Robi Polikar:
Resampling Techniques for Learning Under Extreme Verification Latency with Class Imbalance. IJCNN 2018: 1-8 - [c62]Muhammad Umer, Christopher Frederickson, Robi Polikar:
Adversarial Poisoning of Importance Weighting in Domain Adaptation. SSCI 2018: 381-388 - [e3]Georg Krempl, Vincent Lemaire, Daniel Kottke, Adrian Calma, Andreas Holzinger, Robi Polikar, Bernhard Sick:
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning (ECML 2018) and Principles and Practice of Knowledge Discovery in Databases (PKDD 2018), Dublin, Ireland, September 10th, 2018. CEUR Workshop Proceedings 2192, CEUR-WS.org 2018 [contents] - [i1]Christopher Frederickson, Michael Moore, Glenn Dawson, Robi Polikar:
Attack Strength vs. Detectability Dilemma in Adversarial Machine Learning. CoRR abs/1802.07295 (2018) - 2017
- [c61]Muhammad Umer, Robi Polikar, Christopher Frederickson:
LEVELIW: Learning extreme verification latency with importance weighting. IJCNN 2017: 1740-1747 - [e2]Georg Krempl, Vincent Lemaire, Robi Polikar, Bernhard Sick, Daniel Kottke, Adrian Calma:
Proceedings of the Workshop and Tutorial on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017), Skopje, Macedonia, September 18, 2017. CEUR Workshop Proceedings 1924, CEUR-WS.org 2017 [contents] - 2016
- [c60]Dimah Dera
, Nidhal Bouaynaya, Robi Polikar, Hassan M. Fathallah-Shaykh
:
Non-negative matrix factorization for non-parametric and unsupervised image clustering and segmentation. IJCNN 2016: 3068-3075 - [c59]Muhammad Umer, Christopher Frederickson, Robi Polikar:
Learning under extreme verification latency quickly: FAST COMPOSE. SSCI 2016: 1-8 - 2015
- [j20]Gregory Ditzler, Manuel Roveri
, Cesare Alippi, Robi Polikar
:
Learning in Nonstationary Environments: A Survey. IEEE Comput. Intell. Mag. 10(4): 12-25 (2015) - [j19]Gregory Ditzler, Robi Polikar
, Gail Rosen
:
A Bootstrap Based Neyman-Pearson Test for Identifying Variable Importance. IEEE Trans. Neural Networks Learn. Syst. 26(4): 880-886 (2015) - [c58]Ahmad Taher Azar
, Nidhal Bouaynaya, Robi Polikar:
Inductive learning based on rough set theory for medical decision making. FUZZ-IEEE 2015: 1-8 - [c57]Bradley Ebinger, Nidhal Bouaynaya, Robi Polikar
, Roman Shterenberg:
Constrained state estimation in particle filters. ICASSP 2015: 4050-4054 - [c56]Joseph Sarnelle, Anthony Sanchez, Robert Capo, Joshua Haas, Robi Polikar
:
Quantifying the limited and gradual concept drift assumption. IJCNN 2015: 1-8 - 2014
- [j18]Robi Polikar
, Cesare Alippi:
Guest Editorial Learning in Nonstationary and Evolving Environments. IEEE Trans. Neural Networks Learn. Syst. 25(1): 9-11 (2014) - [j17]Karl B. Dyer, Robert Capo, Robi Polikar
:
COMPOSE: A Semisupervised Learning Framework for Initially Labeled Nonstationary Streaming Data. IEEE Trans. Neural Networks Learn. Syst. 25(1): 12-26 (2014) - [c55]Gregory Ditzler, Matthew Austen, Gail L. Rosen
, Robi Polikar
:
Scaling a neyman-pearson subset selection approach via heuristics for mining massive data. CIDM 2014: 439-445 - [c54]Gregory Ditzler, Gail L. Rosen
, Robi Polikar
:
Domain adaptation bounds for multiple expert systems under concept drift. IJCNN 2014: 595-601 - [c53]Robert Capo, Anthony Sanchez, Robi Polikar
:
Core support extraction for learning from initially labeled nonstationary environments using COMPOSE. IJCNN 2014: 602-608 - [c52]Jehandad Khan, Nidhal Bouaynaya, Robi Polikar
:
Optimal Bayesian classification in nonstationary streaming environments. IJCNN 2014: 609-616 - 2013
- [j16]Gregory Ditzler, Robi Polikar
:
Incremental Learning of Concept Drift from Streaming Imbalanced Data. IEEE Trans. Knowl. Data Eng. 25(10): 2283-2301 (2013) - [c51]Gregory Ditzler, Gail Rosen
, Robi Polikar
:
Discounted expert weighting for concept drift. CIDUE 2013: 61-67 - [c50]Robert Capo, Karl B. Dyer, Robi Polikar
:
Active learning in nonstationary environments. IJCNN 2013: 1-8 - [c49]Gregory Ditzler, Gail Rosen
, Robi Polikar
:
Incremental learning of new classes from unbalanced data. IJCNN 2013: 1-8 - [c48]Sara H. Davis, Megan N. Frankle, Ravi Prakash Ramachandran, Kevin D. Dahm, Robi Polikar
:
A freshman level module in biometric systems. ISCAS 2013: 2767-2770 - 2012
- [j15]T. Ryan Hoens, Robi Polikar, Nitesh V. Chawla
:
Learning from streaming data with concept drift and imbalance: an overview. Prog. Artif. Intell. 1(1): 89-101 (2012) - [c47]Gregory Ditzler, Gail Rosen
, Robi Polikar
:
Information theoretic feature selection for high dimensional metagenomic data. GENSiPS 2012: 143-146 - [c46]Gregory Ditzler, Gail Rosen
, Robi Polikar
:
Forensic identification with environmental samples. ICASSP 2012: 1861-1864 - [c45]Gregory Ditzler, Gail L. Rosen
, Robi Polikar
:
Transductive learning algorithms for nonstationary environments. IJCNN 2012: 1-8 - [c44]Karl B. Dyer, Robi Polikar
:
Semi-supervised learning in initially labeled non-stationary environments with gradual drift. IJCNN 2012: 1-9 - [c43]Ravi Prakash Ramachandran, Robi Polikar
, Kevin D. Dahm, Sachin S. Shetty
:
Open-ended design and performance evaluation of a biometric speaker identification system. ISCAS 2012: 2697-2700 - 2011
- [j14]Elaine Garbarine, Joseph DePasquale, Vinay Gadia, Robi Polikar
, Gail L. Rosen
:
Information-theoretic approaches to SVM feature selection for metagenome read classification. Comput. Biol. Chem. 35(3): 199-209 (2011) - [j13]Marco Baglietto
, Lubica Benusková, Ivo Bukovsky
, Tianping Chen, Tom Heskes
, Kazushi Ikeda
, Fakhri Karray, Rhee Man Kil, Robert Legenstein, Jinhu Lu
, Yunqian Ma, Malik Magdon-Ismail, Michael G. Paulin, Robi Polikar
, Danil V. Prokhorov, Marco A. Wiering, Vicente Zarzoso:
Editorial: One Year as EiC, and Editorial-Board Changes at TNN. IEEE Trans. Neural Networks 22(1): 1-7 (2011) - [j12]Ryan Elwell, Robi Polikar
:
Incremental Learning of Concept Drift in Nonstationary Environments. IEEE Trans. Neural Networks 22(10): 1517-1531 (2011) - [c42]Gregory Ditzler, Robi Polikar
:
Hellinger distance based drift detection for nonstationary environments. CIDUE 2011: 41-48 - [c41]Tyler Staudinger, Robi Polikar
:
Analysis of complexity based EEG features for the diagnosis of Alzheimer's disease. EMBC 2011: 2033-2036 - [c40]Steven D. Essinger, Robi Polikar
, Gail Rosen
:
Ordering samples along environmental gradients using particle swarm optimization. EMBC 2011: 4382-4385 - [c39]T. Ryan Hoens, Nitesh V. Chawla
, Robi Polikar
:
Heuristic Updatable Weighted Random Subspaces for Non-stationary Environments. ICDM 2011: 241-250 - [c38]Gregory Ditzler, Robi Polikar
:
Semi-supervised learning in nonstationary environments. IJCNN 2011: 2741-2748 - 2010
- [j11]Robi Polikar
, Joseph DePasquale, Hussein Syed Mohammed, Gavin Brown, Ludmila I. Kuncheva
:
Learn++.MF: A random subspace approach for the missing feature problem. Pattern Recognit. 43(11): 3817-3832 (2010) - [c37]Gregory Ditzler, James Ethridge, Ravi Prakash Ramachandran, Robi Polikar
:
Fusion methods for boosting performance of speaker identification systems. APCCAS 2010: 116-119 - [c36]James Ethridge, Gregory Ditzler, Robi Polikar
:
Optimal nu-SVM parameter estimation using multi objective evolutionary algorithms. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c35]Gregory Ditzler, Robi Polikar
, Nitesh V. Chawla
:
An Incremental Learning Algorithm for Non-stationary Environments and Class Imbalance. ICPR 2010: 2997-3000 - [c34]Gregory Ditzler, Robi Polikar
:
An ensemble based incremental learning framework for concept drift and class imbalance. IJCNN 2010: 1-8 - [c33]Steven D. Essinger, Robi Polikar
, Gail L. Rosen
:
Neural network-based taxonomic clustering for metagenomics. IJCNN 2010: 1-7 - [c32]Gregory Ditzler, Michael D. Muhlbaier, Robi Polikar:
Incremental Learning of New Classes in Unbalanced Datasets: Learn + + .UDNC. MCS 2010: 33-42
2000 – 2009
- 2009
- [j10]Robi Polikar:
Ensemble learning. Scholarpedia 4(1): 2776 (2009) - [j9]Michael D. Muhlbaier, Apostolos Topalis, Robi Polikar
:
Learn++.NC: Combining Ensemble of Classifiers With Dynamically Weighted Consult-and-Vote for Efficient Incremental Learning of New Classes. IEEE Trans. Neural Networks 20(1): 152-168 (2009) - [c31]Anna Caterina Merzagora, Meltem Izzetoglu, Robi Polikar
, Valerie Weisser, Banu Onaral, Maria T. Schultheis
:
Functional Near-Infrared Spectroscopy and Electroencephalography: A Multimodal Imaging Approach. HCI (16) 2009: 417-426 - [c30]Ryan Elwell, Robi Polikar
:
Incremental learning in nonstationary environments with controlled forgetting. IJCNN 2009: 771-778 - [c29]Ryan Elwell, Robi Polikar
:
Incremental Learning of Variable Rate Concept Drift. MCS 2009: 142-151 - 2008
- [j8]Gail L. Rosen, Elaine Garbarine, Diamantino Caseiro, Robi Polikar, Bahrad A. Sokhansanj:
Metagenome Fragment Classification Using N-Mer Frequency Profiles. Adv. Bioinformatics 2008: 205969:1-205969:12 (2008) - [j7]Robi Polikar
, Apostolos Topalis, Devi Parikh, Deborah Green, Jennifer Frymiare, John Kounios, Christopher M. Clark:
An ensemble based data fusion approach for early diagnosis of Alzheimer's disease. Inf. Fusion 9(1): 83-95 (2008) - [j6]Hakan Cevikalp
, Robi Polikar
:
Local Classifier Weighting by Quadratic Programming. IEEE Trans. Neural Networks 19(10): 1832-1838 (2008) - [c28]Hakan Cevikalp, Bill Triggs, Frédéric Jurie, Robi Polikar
:
Margin-based discriminant dimensionality reduction for visual recognition. CVPR 2008 - [c27]Hakan Cevikalp, Bill Triggs, Robi Polikar:
Nearest hyperdisk methods for high-dimensional classification. ICML 2008: 120-127 - [c26]Matthew T. Karnick, Michael Muhlbaier, Robi Polikar:
Incremental learning in non-stationary environments with concept drift using a multiple classifier based approach. ICPR 2008: 1-4 - [c25]Matthew T. Karnick, Metin Ahiskali, Michael Muhlbaier, Robi Polikar
:
Learning concept drift in nonstationary environments using an ensemble of classifiers based approach. IJCNN 2008: 3455-3462 - 2007
- [j5]Robi Polikar
, Apostolos Topalis, Deborah Green, John Kounios, Christopher M. Clark:
Comparative multiresolution wavelet analysis of ERP spectral bands using an ensemble of classifiers approach for early diagnosis of Alzheimer's disease. Comput. Biol. Medicine 37(4): 542-558 (2007) - [j4]Robi Polikar
:
Bootstrap - Inspired Techniques in Computation Intelligence. IEEE Signal Process. Mag. 24(4): 59-72 (2007) - [j3]Devi Parikh, Robi Polikar
:
An Ensemble-Based Incremental Learning Approach to Data Fusion. IEEE Trans. Syst. Man Cybern. Part B 37(2): 437-450 (2007) - [c24]Joseph DePasquale, Robi Polikar
:
Random Feature Subset Selection for Analysis of Data with Missing Features. IJCNN 2007: 2379-2384 - [c23]Brian A. Balut, Matthew T. Karnick, Deborah Green, John Kounios, Christopher M. Clark, Robi Polikar
:
Ensemble Based Data Fusion from Parietal Region Event Related Potentials for Early Diagnosis of Alzheimer's Disease. IJCNN 2007: 2409-2414 - [c22]Joseph DePasquale, Robi Polikar:
Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features. MCS 2007: 251-260 - [c21]Michael Muhlbaier, Robi Polikar:
An Ensemble Approach for Incremental Learning in Nonstationary Environments. MCS 2007: 490-500 - 2006
- [c20]Hardik Gandhi, Deborah Green, John Kounios, Christopher M. Clark, Robi Polikar
:
Stacked Generalization for Early Diagnosis of Alzheimer's Disease. EMBC 2006: 5350-5353 - [c19]Hussein Syed Mohammed, James Leander, Matthew Marbach, Robi Polikar:
Can AdaBoost.M1 Learn Incrementally? A Comparison to Learn++ Under Different Combination Rules. ICANN (1) 2006: 254-263 - [c18]Nicholas Stepenosky, Deborah Green, John Kounios, Christopher M. Clark, Robi Polikar:
Majority Vote and Decision Template Based Ensemble Classifiers Trained on Event Related Potentials for Early Diagnosis of Alzheimer's Disease. ICASSP (5) 2006: 901-904 - [c17]Nicholas Stepenosky, Robi Polikar, John Kounios, Christopher M. Clark:
Ensemble Techniques with Weighted Combination Rules for Early Diagnosis of Alzheimer's Disease. IJCNN 2006: 1935-1941 - [c16]Hussein Syed Mohammed, James Leander, Matthew Marbach, Robi Polikar
:
Comparison of Ensemble Techniques for Incremental Learning of New Concept Classes under Hostile Non-stationary Environments. SMC 2006: 4838-4844 - 2005
- [j2]John L. Schmalzel, Fernando Figueroa
, Jon Morris, Shreekanth Mandayam, Robi Polikar
:
An architecture for intelligent systems based on smart sensors. IEEE Trans. Instrum. Meas. 54(4): 1612-1616 (2005) - [c15]Zeki Erdem, Robi Polikar, Fikret S. Gürgen, Nejat Yumusak:
Reducing the Effect of Out-Voting Problem in Ensemble Based Incremental Support Vector Machines. ICANN (2) 2005: 607-612 - [c14]Genevieve Jacques, Jennifer Frymiare, John Kounios, Christopher M. Clark, Robi Polikar
:
Multiresolution wavelet analysis and ensemble of classifiers for early diagnosis of Alzheimer's disease. ICASSP (5) 2005: 389-392 - [c13]Zeki Erdem, Robi Polikar
, Nejat Yumusak, Fikret S. Gürgen:
Classification of Volatile Organic Compounds with Incremental SVMs and RBF Networks. ISCIS 2005: 322-331 - [c12]Zeki Erdem, Robi Polikar
, Fikret S. Gürgen, Nejat Yumusak:
Ensemble of SVMs for Incremental Learning. Multiple Classifier Systems 2005: 246-256 - [c11]Michael Muhlbaier, Apostolos Topalis, Robi Polikar:
Ensemble Confidence Estimates Posterior Probability. Multiple Classifier Systems 2005: 326-335 - [e1]Nikunj C. Oza, Robi Polikar, Josef Kittler, Fabio Roli:
Multiple Classifier Systems, 6th International Workshop, MCS 2005, Seaside, CA, USA, June 13-15, 2005, Proceedings. Lecture Notes in Computer Science 3541, Springer 2005, ISBN 3-540-26306-3 [contents] - 2004
- [c10]Michael Muhlbaier, Apostolos Topalis, Robi Polikar
:
Learn++.MT: A New Approach to Incremental Learning. Multiple Classifier Systems 2004: 52-61 - [c9]Devi Parikh, Min T. Kim, Joseph Oagaro, Shreekanth Mandayam, Robi Polikar
:
Combining classifiers for multisensor data fusion. SMC (2) 2004: 1232-1237 - 2003
- [c8]Jeffrey Byorick, Robi Polikar:
Confidence Estimation Using the Incremental Learning Algorithm, Learn++. ICANN 2003: 181-188 - [c7]Michael Lewitt, Robi Polikar:
An Ensemble Approach for Data Fusion with Learn++. Multiple Classifier Systems 2003: 176-185 - 2001
- [j1]Robi Polikar
, L. Upda, S. S. Upda, Vasant G. Honavar
:
Learn++: an incremental learning algorithm for supervised neural networks. IEEE Trans. Syst. Man Cybern. Part C 31(4): 497-508 (2001) - [c6]Robi Polikar, Ruth Shinar, Vasant G. Honavar, Lalita Udpa, Marc D. Porter:
Detection and identification of odorants using an electronic nose. ICASSP 2001: 3137-3140 - [c5]Muhammad Afzal, Robi Polikar, Lalita Udpa, Satish S. Udpa:
Adaptive noise cancellation schemes for magnetic flux leakage signals obtained from gas pipeline inspection. ICASSP 2001: 3389-3392 - [c4]Muhammad Afzal, Robi Polikar, Lalita Udpa, Satish S. Udpa:
Adaptive noise cancellation schemes for magnetic flux leakage signals obtained from gas pipeline inspection. ICASSP 2001: 3389-3392 - 2000
- [c3]Robi Polikar, Lalita Udpa, Satish S. Udpa, Vasant G. Honavar
:
LEARN++: an incremental learning algorithm for multilayer perceptron networks. ICASSP 2000: 3414-3417 - [c2]Pradeep Ramuhalli
, Robi Polikar, Lalita Udpa, Satish S. Udpa:
Fuzzy ARTMAP network with evolutionary learning. ICASSP 2000: 3466-3469
1990 – 1999
- 1999
- [c1]Robi Polikar, Lalita Udpa, Satish S. Udpa:
Nonlinear cluster transformations for increasing pattern separability. IJCNN 1999: 4006-4011
Coauthor Index
aka: Gail Rosen
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