| 2024 | SP | MM-BD: Post-Training Detection of Backdoor Attacks with Arbitrary Backdoor Pattern Types Using a Maximum Margin Statistic. | Hang Wang, Zhen Xiang, David J. Miller, George Kesidis |
| 2023 | ICASSP | Training Set Cleansing of Backdoor Poisoning by Self-Supervised Representation Learning. | Hang Wang, Sahar Karami, Ousmane Dia, Hippolyt Ritter, Ehsan Emamjomeh-Zadeh, Jiahui Chen, Zhen Xiang, David J. Miller, George Kesidis |
| 2022 | ICASSP | Test-Time Detection of Backdoor Triggers for Poisoned Deep Neural Networks. | Xi Li, Zhen Xiang, David J. Miller, George Kesidis |
| 2022 | ICASSP | Detecting Backdoor Attacks against Point Cloud Classifiers. | Zhen Xiang, David J. Miller, Siheng Chen, Xi Li, George Kesidis |
| 2022 | ICLR | Post-Training Detection of Backdoor Attacks for Two-Class and Multi-Attack Scenarios. | Zhen Xiang, David J. Miller, George Kesidis |
| 2021 | ICASSP | L-Red: Efficient Post-Training Detection of Imperceptible Backdoor Attacks Without Access to the Training Set. | Zhen Xiang, David J. Miller, George Kesidis |
| 2021 | ICCV | A Backdoor Attack against 3D Point Cloud Classifiers. | Zhen Xiang, David J. Miller, Siheng Chen, Xi Li, George Kesidis |
| 2020 | ICASSP | Revealing Backdoors, Post-Training, in DNN Classifiers via Novel Inference on Optimized Perturbations Inducing Group Misclassification. | Zhen Xiang, David J. Miller, George Kesidis |
| 2019 | DCC | Learned Neural Iterative Decoding for Lossy Image Compression Systems. | Alexander G. Ororbia II, Ankur Mali, Jian Wu, Scott O'Connell, William Dreese, David J. Miller, C. Lee Giles |
| 2019 | ICASSP | When Not to Classify: Detection of Reverse Engineering Attacks on DNN Image Classifiers. | Yujia Wang, David J. Miller, George Kesidis |
| 2018 | CIKM | Toward Automated Multiparty Privacy Conflict Detection. | Haoti Zhong, Anna Cinzia Squicciarini, David J. Miller |
| 2018 | CISS | Locally optimal, delay-tolerant predictive source coding. | Zhen Xiang, David J. Miller |
| 2017 | ICASSP | Flow based botnet detection through semi-supervised active learning. | Zhicong Qiu, David J. Miller, George Kesidis |
| 2017 | IJCAI | A Group-Based Personalized Model for Image Privacy Classification and Labeling. | Haoti Zhong, Anna Cinzia Squicciarini, David J. Miller, Cornelia Caragea |
| 2016 | CIKM | Semi-supervised Multi-Label Topic Models for Document Classification and Sentence Labeling. | Hossein Soleimani, David J. Miller |
| 2016 | IJCAI | Content-Driven Detection of Cyberbullying on the Instagram Social Network. | Haoti Zhong, Hao Li, Anna Cinzia Squicciarini, Sarah Michele Rajtmajer, Christopher Griffin, David J. Miller, Cornelia Caragea |
| 2016 | IJCNN | Exploiting the value of class labels in topic models for semi-supervised document classification. | Hossein Soleimani, David J. Miller |
| 2014 | CISS | Detecting anomalous latent classes in a batch of network traffic flows. | Fatih Kocak, David J. Miller, George Kesidis |
| 2013 | ICASSP | A generative semi-supervised model for multi-view learning when some views are label-free. | Gaole Jin, Raviv Raich, David J. Miller |
| 2012 | CISS | Semisupervised domain adaptation for mixture model based classifiers. | Jayaram Raghuram, David J. Miller, George Kesidis |
| 2012 | NOMS | Enabling open-source high speed network monitoring on NetFPGA. | Gianni Antichi, Stefano Giordano, David J. Miller, Andrew W. Moore |
| 2010 | CISS | Feasibility of range estimation using sonar LPI. | J. Daniel Park, David J. Miller, John F. Doherty, Stephen C. Thompson |
| 2010 | ICMLA | Improved Fine-Grained Component-Conditional Class Labeling with Active Learning. | David J. Miller, Chu-Fang Lin, George Kesidis, Christopher M. Collins |
| 2009 | CISS | A study on the feasibility of low probability of intercept sonar. | J. Daniel Park, David J. Miller, John F. Doherty, Stephen C. Thompson |
| 2009 | FPL | Tracking elephant flows in internet backbone traffic with an FPGA-based cache. | Martin Zdnk, Marco Canini, Andrew W. Moore, David J. Miller, Wei Li |
| 2008 | ICASSP | A transductive extension of maximum entropy/iterative scaling for decision aggregation in distributed classification. | David J. Miller, Yanxin Zhang, George Kesidis |
| 2006 | BIBE | Learning the Tree of Phenotypes Using Genomic Data and VISDA. | Yuanjian Feng, Zuyi Wang, Yitan Zhu, Jianhua Xuan, David J. Miller |
| 2006 | CISS | Transductive Methods for Distributed Ensemble Classification. | David J. Miller, Siddharth Pal |
| 2006 | SIGCOMM | Polymorphic worm detection and defense: system design, experimental methodology, and data resources. | Jisheng Wang, Ihab Hamadeh, George Kesidis, David J. Miller |
| 2005 | GLOBECOM | Hierarchical shaped deficit round-robin scheduling. | Soranun Jiwasurat, George Kesidis, David J. Miller |
| 2005 | ICASSP | Semisupervised learning of mixture models with class constraints. | Qi Zhao, David J. Miller |
| 2004 | ICASSP | A deterministic, annealing-based approach for learning and model selection in finite mixture models. | Qi Zhao, David J. Miller |
| 2003 | ICASSP | A mixture model and EM algorithm for robust classification, outlier rejection, and class discovery. | David J. Miller, John Browning |
| 2003 | WSC | Automated material handling systems: automated reticle handling: a comparison of distributed and centralized reticle storage and transport. | Anne M. Murray, David J. Miller |
| 2002 | ICASSP | A sequence-based generalization of mean-field annealing using the Forward/Backward algorithm: Application to image segmentation. | David J. Miller, Piya Bunyaratavej, Qi Zhao |
| 2001 | ICASSP | Locally optimal joint encoding of image transform coefficients. | Piya Bunyaratavej, David J. Miller |
| 2001 | VTC | Mobile multimedia services for third generation communications systems. | A. Ravindran, Hang Liu, Izzet Agoren, Alex J. Lackpour, David J. Miller, Mohsen Kavehrad, John F. Doherty |
| 1999 | DCC | Improved Joint Source-Channel Decoding for Variable-Length Encoded Data Using Soft Decisions and MMSE Estimation. | MoonSeo Park, David J. Miller |
| 1999 | ICASSP | Ensemble classification by critic-driven combining. | David J. Miller, Lian Yan |
| 1999 | ICASSP | Joint source-channel decoding for variable-length encoded data by exact and approximate MAP sequence estimation. | MoonSeo Park, David J. Miller |
| 1999 | ICASSP | Time series prediction via neural network inversion. | Lian Yan, David J. Miller |
| 1999 | IJCNN | Approximate maximum entropy joint feature inference for discrete space classification. | David J. Miller, Lian Yan |
| 1998 | ICIP | A New Set Partitioning Method for Wavelet-based Image Coding. | Jeongjin Roh, David J. Miller |
| 1997 | ICASSP | Deterministically annealed mixture of experts models for statistical regression. | Ajit V. Rao, David J. Miller, Kenneth Rose, Allen Gersho |
| 1997 | ICIP | Image Decoding Over Noisy Channels Using Minimum Mean-Squared Estimation and a Markov Mesh. | MoonSeo Park, David J. Miller |
| 1996 | ICASSP | A generalized VQ method for combined compression and estimation. | Ajit V. Rao, David J. Miller, Kenneth Rose, Allen Gersho |
| 1994 | DCC | Entropy-Constrained Tree-Structured Vector Quantizer Design by the Minimum Cross Entropy Principle. | Kenneth Rose, David J. Miller, Allen Gersho |
| 1994 | ICASSP | Deterministic annealing for trellis quantizer and HMM design using Baum-Welch re-estimation. | David J. Miller, Kenneth Rose, Philip A. Chou |
| 1994 | WSC | The role of simulation in semiconductor logistics. | David J. Miller |
| 1993 | DCC | An Improved Sequential Search Multistage Vector Quantizer. | David J. Miller, Kenneth Rose |
| 1992 | ICASSP | Joint source-channel vector quantization using deterministic annealing. | David J. Miller, Kenneth Rose |
| 1990 | ICRA | An object-oriented environment for robot system architectures. | David J. Miller, R. Charleene Lennox |
| 1989 | WSC | Implementing the results of a manufacturing simulation in a semiconductor line. | David J. Miller |