David J. Miller
Orcid: 0000-0001-8848-1643Affiliations:
- Pennsylvania State University, University Park, PA, USA
- University of California, Santa Barbara, CA, USA (PhD 1995)
According to our database1,
David J. Miller
authored at least 156 papers
between 1992 and 2024.
Collaborative distances:
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Bibliography
2024
Universal Post-Training Reverse-Engineering Defense Against Backdoors in Deep Neural Networks.
CoRR, 2024
2023
Improved Activation Clipping for Universal Backdoor Mitigation and Test-Time Detection.
CoRR, 2023
Anomaly detection of adversarial examples using class-conditional generative adversarial networks.
Comput. Secur., 2023
Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023
Training Set Cleansing of Backdoor Poisoning by Self-Supervised Representation Learning.
Proceedings of the IEEE International Conference on Acoustics, 2023
2022
IEEE Trans. Neural Networks Learn. Syst., 2022
IEEE Signal Process. Mag., 2022
Training set cleansing of backdoor poisoning by self-supervised representation learning.
CoRR, 2022
Post-Training Detection of Backdoor Attacks for Two-Class and Multi-Attack Scenarios.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the IEEE International Conference on Acoustics, 2022
Proceedings of the IEEE International Conference on Acoustics, 2022
2021
Detecting Scene-Plausible Perceptible Backdoors in Trained DNNs Without Access to the Training Set.
Neural Comput., 2021
Anomaly Detection of Test-Time Evasion Attacks using Class-conditional Generative Adversarial Networks.
CoRR, 2021
Reverse engineering imperceptible backdoor attacks on deep neural networks for detection and training set cleansing.
Comput. Secur., 2021
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021
L-Red: Efficient Post-Training Detection of Imperceptible Backdoor Attacks Without Access to the Training Set.
Proceedings of the IEEE International Conference on Acoustics, 2021
2020
Adversarial Learning Targeting Deep Neural Network Classification: A Comprehensive Review of Defenses Against Attacks.
Proc. IEEE, 2020
Entropy, 2020
Revealing Perceptible Backdoors in DNNs, Without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic.
Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020
Revealing Backdoors, Post-Training, in DNN Classifiers via Novel Inference on Optimized Perturbations Inducing Group Misclassification.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020
A Scalable Mixture Model Based Defense Against Data Poisoning Attacks on Classifiers.
Proceedings of the Dynamic Data Driven Applications Systems, 2020
Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation.
Proceedings of the CODASPY '20: Tenth ACM Conference on Data and Application Security and Privacy, 2020
2019
Exploiting the value of class labels on high-dimensional feature spaces: topic models for semi-supervised document classification.
Pattern Anal. Appl., 2019
When Not to Classify: Anomaly Detection of Attacks (ADA) on DNN Classifiers at Test Time.
Neural Comput., 2019
Revealing Perceptible Backdoors, without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic.
CoRR, 2019
Notes on Lipschitz Margin, Lipschitz Margin Training, and Lipschitz Margin p-Values for Deep Neural Network Classifiers.
CoRR, 2019
Adversarial Learning in Statistical Classification: A Comprehensive Review of Defenses Against Attacks.
CoRR, 2019
A Benchmark Study Of Backdoor Data Poisoning Defenses For Deep Neural Network Classifiers And A Novel Defense.
Proceedings of the 29th IEEE International Workshop on Machine Learning for Signal Processing, 2019
When Not to Classify: Detection of Reverse Engineering Attacks on DNN Image Classifiers.
Proceedings of the IEEE International Conference on Acoustics, 2019
Proceedings of the Data Compression Conference, 2019
Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019
2018
Detection of Sources in Non-Negative Blind Source Separation by Minimum Description Length Criterion.
IEEE Trans. Neural Networks Learn. Syst., 2018
A Locally Optimal Algorithm for Estimating a Generating Partition from an Observed Time Series and Its Application to Anomaly Detection.
Neural Comput., 2018
A Mixture Model Based Defense for Data Poisoning Attacks Against Naive Bayes Spam Filters.
CoRR, 2018
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018
Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018
Proceedings of the 28th IEEE International Workshop on Machine Learning for Signal Processing, 2018
Proceedings of the 52nd Annual Conference on Information Sciences and Systems, 2018
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018
2017
A Maximum Entropy Framework for Semisupervised and Active Learning With Unknown and Label-Scarce Classes.
IEEE Trans. Neural Networks Learn. Syst., 2017
Neural Comput., 2017
Automated Functional Analysis of Astrocytes from Chronic Time-Lapse Calcium Imaging Data.
Frontiers Neuroinformatics, 2017
Proceedings of the 27th IEEE International Workshop on Machine Learning for Signal Processing, 2017
A locally optimal algorithm for estimating a generating partition from an observed time series.
Proceedings of the 27th IEEE International Workshop on Machine Learning for Signal Processing, 2017
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017
Proceedings of the 2017 IEEE International Conference on Acoustics, 2017
A simulation framework for uneconomic virtual bidding in day-ahead electricity markets.
Proceedings of the 2017 American Control Conference, 2017
2016
IEEE Trans. Knowl. Data Eng., 2016
A simulation framework for uneconomic virtual bidding in day-ahead electricity markets: Short talk.
SIGMETRICS Perform. Evaluation Rev., 2016
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
IP-level fast re-routing for robustness to mass failure events using a hybrid bandwidth and reliability cost metric.
Proceedings of the 2016 IEEE Military Communications Conference, 2016
FASP: A machine learning approach to functional astrocyte phenotyping from time-lapse calcium imaging data.
Proceedings of the 13th IEEE International Symposium on Biomedical Imaging, 2016
Exploiting the value of class labels in topic models for semi-supervised document classification.
Proceedings of the 2016 International Joint Conference on Neural Networks, 2016
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016
Semi-supervised Multi-Label Topic Models for Document Classification and Sentence Labeling.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016
2015
IEEE Trans. Knowl. Data Eng., 2015
Multicategory Crowdsourcing Accounting for Variable Task Difficulty, Worker Skill, and Worker Intention.
IEEE Trans. Knowl. Data Eng., 2015
Peer-to-Peer Netw. Appl., 2015
EURASIP J. Adv. Signal Process., 2015
Detecting clusters of anomalies on low-dimensional feature subsets with application to network traffic flow data.
Proceedings of the 25th IEEE International Workshop on Machine Learning for Signal Processing, 2015
2014
Instance-Level Constraint-Based Semisupervised Learning With Imposed Space-Partitioning.
IEEE Trans. Neural Networks Learn. Syst., 2014
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2014
Proceedings of the 9th International Workshop on Feedback Computing, 2014
Proceedings of the 48th Annual Conference on Information Sciences and Systems, 2014
2013
Schema matching and embedded value mapping for databases with opaque column names and mixed continuous and discrete-valued data fields.
ACM Trans. Database Syst., 2013
Multicategory Crowdsourcing Accounting for Plurality in Worker Skill and Intention, Task Difficulty, and Task Heterogeneity.
CoRR, 2013
Latent Interest-Group Discovery and Management by Peer-to-Peer Online Social Networks.
Proceedings of the International Conference on Social Computing, SocialCom 2013, 2013
A generative semi-supervised model for multi-view learning when some views are label-free.
Proceedings of the IEEE International Conference on Acoustics, 2013
Defeating Tyranny of the Masses in Crowdsourcing: Accounting for Low-Skilled and Adversarial Workers.
Proceedings of the Decision and Game Theory for Security - 4th International Conference, 2013
Proceedings of the 3rd ACM SIGMOD Workshop on Databases and Social Networks, 2013
2012
IEEE Trans. Neural Networks Learn. Syst., 2012
Improved Generative Semisupervised Learning Based on Finely Grained Component-Conditional Class Labeling.
Neural Comput., 2012
Sequential anomaly detection in a batch with growing number of tests: Application to network intrusion detection.
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing, 2012
Proceedings of the 46th Annual Conference on Information Sciences and Systems, 2012
2011
IEEE Signal Process. Mag., 2011
A Flow Classifier with Tamper-Resistant Features and an Evaluation of Its Portability to New Domains.
IEEE J. Sel. Areas Commun., 2011
Proceedings of the 4th Workshop on Cyber Security Experimentation and Test, 2011
2010
Margin-maximizing feature elimination methods for linear and nonlinear kernel-based discriminant functions.
IEEE Trans. Neural Networks, 2010
Uninterpreted Schema Matching with Embedded Value Mapping under Opaque Column Names and Data Values.
IEEE Trans. Knowl. Data Eng., 2010
Joint Parsimonious Modeling and Model Order Selection for Multivariate Gaussian Mixtures.
IEEE J. Sel. Top. Signal Process., 2010
Matched Gene Selection and Committee Classifier for Molecular Classification of Heterogeneous Diseases.
J. Mach. Learn. Res., 2010
Proceedings of the Ninth International Conference on Machine Learning and Applications, 2010
Proceedings of the 44th Annual Conference on Information Sciences and Systems, 2010
2009
Comput. Methods Programs Biomed., 2009
An algorithm for learning maximum entropy probability models of disease risk that efficiently searches and sparingly encodes multilocus genomic interactions.
Bioinform., 2009
Proceedings of the 43rd Annual Conference on Information Sciences and Systems, 2009
2008
Extensions of transductive learning for distributed ensemble classification and application to biometric authentication.
Neurocomputing, 2008
Decision Aggregation in Distributed Classification by a Transductive Extension of Maximum Entropy/Improved Iterative Scaling.
EURASIP J. Adv. Signal Process., 2008
caBIG<sup>TM</sup> VISDA: Modeling, visualization, and discovery for cluster analysis of genomic data.
BMC Bioinform., 2008
A transductive extension of maximum entropy/iterative scaling for decision aggregation in distributed classification.
Proceedings of the IEEE International Conference on Acoustics, 2008
2007
An Extension of Iterative Scaling for Decision and Data Aggregation in Ensemble Classification.
J. VLSI Signal Process., 2007
Guest Editorial for Special Issue on the 2005 IEEE Workshop on Machine Learning for Signal Processing.
J. VLSI Signal Process., 2007
Neural Comput., 2007
2006
Unsupervised learning of parsimonious mixtures on large spaces with integrated feature and component selection.
IEEE Trans. Signal Process., 2006
Efficient Mining of the Multidimensional Traffic Cluster Hierarchy for Digesting, Visualization, and Anomaly Identification.
IEEE J. Sel. Areas Commun., 2006
Polymorphic worm detection and defense: system design, experimental methodology, and data resources.
Proceedings of the 2006 SIGCOMM Workshop on Large-Scale Attack Defense, 2006
Proceedings of the 28th International Conference of the IEEE Engineering in Medicine and Biology Society, 2006
Proceedings of the 40th Annual Conference on Information Sciences and Systems, 2006
Proceedings of the Sixth IEEE International Symposium on BioInformatics and BioEngineering (BIBE 2006), 2006
2005
Neural Comput., 2005
Proceedings of the 2005 IEEE International Conference on Acoustics, 2005
Proceedings of the Global Telecommunications Conference, 2005. GLOBECOM '05, St. Louis, Missouri, USA, 28 November, 2005
2004
J. VLSI Signal Process., 2004
J. VLSI Signal Process., 2004
Joint source-channel decoding of predictively and nonpredictively encoded sources: a two-stage estimation approach.
IEEE Trans. Commun., 2004
A deterministic, annealing-based approach for learning and model selection in finite mixture models.
Proceedings of the 2004 IEEE International Conference on Acoustics, 2004
2003
A sequence-based extension of mean-field annealing using the forward/backward algorithm: application to image segmentation.
IEEE Trans. Signal Process., 2003
A Mixture Model and EM-Based Algorithm for Class Discovery, Robust Classification, and Outlier Rejection in Mixed Labeled/Unlabeled Data Sets.
IEEE Trans. Pattern Anal. Mach. Intell., 2003
A mixture model framework for class discovery and outlier detection in mixed labeled/unlabeled data sets.
Proceedings of the NNSP 2003, 2003
A mixture model and EM algorithm for robust classification, outlier rejection, and class discovery.
Proceedings of the 2003 IEEE International Conference on Acoustics, 2003
2002
An iterative hillclimbing algorithm for discrete optimization on images: application to joint encoding of image transform coefficients.
IEEE Signal Process. Lett., 2002
A sequence-based generalization of mean-field annealing using the Forward/Backward algorithm: Application to image segmentation.
Proceedings of the IEEE International Conference on Acoustics, 2002
2001
Proceedings of the 54th IEEE Vehicular Technology Conference, 2001
Proceedings of the IEEE International Conference on Acoustics, 2001
2000
General statistical inference for discrete and mixed spaces by an approximate application of the maximum entropy principle.
IEEE Trans. Neural Networks Learn. Syst., 2000
Joint source-channel decoding for variable-length encoded data by exact and approximate MAP sequence estimation.
IEEE Trans. Commun., 2000
Approximate Maximum Entropy Joint Feature Inference Consistent with Arbitrary Lower-Order Probability Constraints: Application to Statistical Classification.
Neural Comput., 2000
1999
Improved image decoding over noisy channels using minimum mean-squared estimation and a Markov mesh.
IEEE Trans. Image Process., 1999
Transport of wireless video using separate, concatenated, and joint source-channel coding.
Proc. IEEE, 1999
A Deterministic Annealing Approach for Parsimonious Design of Piecewise Regression Models.
IEEE Trans. Pattern Anal. Mach. Intell., 1999
Approximate maximum entropy joint feature inference for discrete space classification.
Proceedings of the International Joint Conference Neural Networks, 1999
Proceedings of the 1999 IEEE International Conference on Acoustics, 1999
Proceedings of the 1999 IEEE International Conference on Acoustics, 1999
Improved Joint Source-Channel Decoding for Variable-Length Encoded Data Using Soft Decisions and MMSE Estimation.
Proceedings of the Data Compression Conference, 1999
1998
A sequence-based approximate MMSE decoder for source coding over noisy channels using discrete hidden Markov models.
IEEE Trans. Commun., 1998
Neural Comput., 1998
Proceedings of the 1998 IEEE International Conference on Image Processing, 1998
1997
IEEE Trans. Signal Process., 1997
IEEE Signal Process. Lett., 1997
Image Decoding Over Noisy Channels Using Minimum Mean-Squared Estimation and a Markov Mesh.
Proceedings of the Proceedings 1997 International Conference on Image Processing, 1997
Proceedings of the 1997 IEEE International Conference on Acoustics, 1997
1996
IEEE Trans. Signal Process., 1996
IEEE Trans. Image Process., 1996
Neural Comput., 1996
A Mixture of Experts Classifier with Learning Based on Both Labelled and Unlabelled Data.
Proceedings of the Advances in Neural Information Processing Systems 9, 1996
Proceedings of the 1996 IEEE International Conference on Acoustics, 1996
1995
Proceedings of the Advances in Neural Information Processing Systems 8, 1995
1994
IEEE Trans. Commun., 1994
Deterministic annealing for trellis quantizer and HMM design using Baum-Welch re-estimation.
Proceedings of ICASSP '94: IEEE International Conference on Acoustics, 1994
Entropy-Constrained Tree-Structured Vector Quantizer Design by the Minimum Cross Entropy Principle.
Proceedings of the IEEE Data Compression Conference, 1994
1993
Proceedings of the IEEE Data Compression Conference, 1993
1992
Proceedings of the 1992 IEEE International Conference on Acoustics, 1992