2008 |
38 | EE | David J. Miller,
Carl A. Nelson,
Dmitry Oleynikov,
David D. Jones:
Pre-operative ordering of minimally invasive surgical tools: A fuzzy inference system approach.
Artificial Intelligence in Medicine 43(1): 35-45 (2008) |
37 | EE | David J. Miller,
Siddharth Pal,
Yue Wang:
Extensions of transductive learning for distributed ensemble classification and application to biometric authentication.
Neurocomputing 72(1-3): 119-125 (2008) |
2007 |
36 | EE | David J. Miller,
Siddharth Pal:
Transductive Methods for the Distributed Ensemble Classification Problem.
Neural Computation 19(3): 856-884 (2007) |
35 | EE | David J. Miller,
Deniz Erdogmus:
Guest Editorial for Special Issue on the 2005 IEEE Workshop on Machine Learning for Signal Processing.
VLSI Signal Processing 48(1-2): 1-3 (2007) |
34 | EE | Siddharth Pal,
David J. Miller:
An Extension of Iterative Scaling for Decision and Data Aggregation in Ensemble Classification.
VLSI Signal Processing 48(1-2): 21-37 (2007) |
2006 |
33 | | Yuanjian Feng,
Zuyi Wang,
Yitan Zhu,
Jianhua Xuan,
David J. Miller:
Learning the Tree of Phenotypes Using Genomic Data and VISDA.
BIBE 2006: 165-170 |
32 | EE | Jisheng Wang,
David J. Miller,
George Kesidis:
Efficient Mining of the Multidimensional Traffic Cluster Hierarchy for Digesting, Visualization, and Anomaly Identification.
IEEE Journal on Selected Areas in Communications 24(10): 1929-1941 (2006) |
31 | EE | Michael W. Graham,
David J. Miller:
Unsupervised learning of parsimonious mixtures on large spaces with integrated feature and component selection.
IEEE Transactions on Signal Processing 54(4): 1289-1303 (2006) |
2005 |
30 | EE | Qi Zhao,
David J. Miller:
Mixture Modeling with Pairwise, Instance-Level Class Constraints.
Neural Computation 17(11): 2482-2507 (2005) |
2004 |
29 | EE | Victor P. Holmes,
Wilbur R. Johnson,
David J. Miller:
Integrating Metadata Tools with the Data Services Archive to Provide Web-based Management of Large-Scale Scientific Simulation Data.
Annual Simulation Symposium 2004: 72-79 |
28 | EE | John F. Lindner,
Scott B. Hughes,
David J. Miller,
Bradley C. Thomas,
Kurt Wiesenfeld:
The flux creep Automaton.
I. J. Bifurcation and Chaos 14(3): 1155-1175 (2004) |
27 | EE | David J. Miller,
Elias S. G. Carotti,
Yu-Wei Wang,
Juan Carlos De Martin:
Joint source-channel decoding of predictively and nonpredictively encoded sources: a two-stage estimation approach.
IEEE Transactions on Communications 52(9): 1575-1584 (2004) |
26 | EE | David J. Miller,
Tülay Adali,
Jan Larsen,
Marc M. Van Hulle:
Guest Editorial for Special Issue on Machine Learning for Signal Processing.
VLSI Signal Processing 37(2-3): 171-175 (2004) |
25 | EE | John Browning,
David J. Miller:
A Maximum Entropy Approach for Collaborative Filtering.
VLSI Signal Processing 37(2-3): 199-209 (2004) |
2003 |
24 | EE | Victor P. Holmes,
Wilbur R. Johnson,
David J. Miller:
Integrating Web Service and Grid Enabling Technologies to Provide Desktop Access to High-Performance Cluster-Based Components for Large-Scale Data Services.
Annual Simulation Symposium 2003: 167-174 |
23 | EE | Anne M. Murray,
David J. Miller:
Automated material handling systems: automated reticle handling: a comparison of distributed and centralized reticle storage and transport.
Winter Simulation Conference 2003: 1360-1365 |
22 | EE | David J. Miller,
John Browning:
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. 25(11): 1468-1483 (2003) |
2002 |
21 | EE | Victor P. Holmes,
Stephen D. Kleban,
David J. Miller,
Constantine J. Pavlakos,
Clark A. Poore,
Ruthe L. Vandewart,
Charles P. Crowley:
An Architecture and Implementation to Support Large-scale Data Access in Scientific Simulation Environments.
Annual Simulation Symposium 2002: 169-176 |
2001 |
20 | EE | Victor P. Holmes,
John M. Linebarger,
David J. Miller,
Ruthe L. Vandewart,
Charles P. Crowley:
Evolving the Web-based Distributed SI/PDO Architecture for High-Performance Visualization.
Annual Simulation Symposium 2001: 151-158 |
2000 |
19 | | David J. Miller,
Lian Yan:
Approximate Maximum Entropy Joint Feature Inference Consistent with Arbitrary Lower-Order Probability Constraints: Application to Statistical Classification.
Neural Computation 12(9): 2175-2207 (2000) |
1999 |
18 | EE | MoonSeo Park,
David J. Miller:
Improved Joint Source-Channel Decoding for Variable-Length Encoded Data Using Soft Decisions and MMSE Estimation.
Data Compression Conference 1999: 544 |
17 | EE | Bernd Mohr,
Federico Bassetti,
Kei Davis,
Stefan Hüttemann,
Pascale Launay,
Dan C. Marinescu,
David J. Miller,
Ruthe L. Vandewart,
Matthias Müller,
Augustin Prodan:
Parallel / High-Performance Object-Oriented Scientific Computing.
ECOOP Workshops 1999: 222-239 |
16 | | David J. Miller,
Ruthe L. Vandewart:
An Object-Based Metasystem for Distributed High Performance Simulation and Product Realization.
ECOOP Workshops 1999: 230-232 |
15 | EE | Ajit V. Rao,
David J. Miller,
Kenneth Rose,
Allen Gersho:
A Deterministic Annealing Approach for Parsimonious Design of Piecewise Regression Models.
IEEE Trans. Pattern Anal. Mach. Intell. 21(2): 159-173 (1999) |
14 | EE | MoonSeo Park,
David J. Miller:
Improved image decoding over noisy channels using minimum mean-squared estimation and a Markov mesh.
IEEE Transactions on Image Processing 8(6): 863-867 (1999) |
1998 |
13 | | Jeongjin Roh,
David J. Miller:
A New Set Partitioning Method for Wavelet-based Image Coding.
ICIP (1) 1998: 102-106 |
12 | | David J. Miller,
Hasan S. Uyar:
Combined Learning and Use for a Mixture Model Equivalent to the RBF Classifier.
Neural Computation 10(2): 281-293 (1998) |
1997 |
11 | EE | MoonSeo Park,
David J. Miller:
Image Decoding Over Noisy Channels Using Minimum Mean-Squared Estimation and a Markov Mesh.
ICIP (3) 1997: 594- |
1996 |
10 | EE | David J. Miller,
Hasan S. Uyar:
A Mixture of Experts Classifier with Learning Based on Both Labelled and Unlabelled Data.
NIPS 1996: 571-577 |
9 | EE | Kenneth Rose,
David J. Miller,
Allen Gersho:
Entropy-constrained tree-structured vector quantizer design.
IEEE Transactions on Image Processing 5(2): 393-398 (1996) |
1995 |
8 | EE | David J. Miller,
Ajit V. Rao,
Kenneth Rose,
Allen Gersho:
An Information-theoretic Learning Algorithm for Neural Network Classification.
NIPS 1995: 591-597 |
7 | EE | X. Allan Lu,
John D. Holt,
David J. Miller:
Boolean System Revisited: Its Performance and its Behavior.
TREC 1995 |
1994 |
6 | | Kenneth Rose,
David J. Miller,
Allen Gersho:
Entropy-Constrained Tree-Structured Vector Quantizer Design by the Minimum Cross Entropy Principle.
Data Compression Conference 1994: 12-21 |
5 | EE | David J. Miller:
The role of simulation in semiconductor logistics.
Winter Simulation Conference 1994: 885-891 |
4 | EE | David J. Miller,
Kenneth Rose:
A non-greedy approach to tree-structured clustering.
Pattern Recognition Letters 15(7): 683-690 (1994) |
1993 |
3 | | David J. Miller,
Kenneth Rose:
An Improved Sequential Search Multistage Vector Quantizer.
Data Compression Conference 1993: 12-21 |
1990 |
2 | | David J. Miller:
Simulation of a Semiconductor Manufacturing Line.
Commun. ACM 33(10): 98-108 (1990) |
1989 |
1 | EE | David J. Miller:
Implementing the results of a manufacturing simulation in a semiconductor line.
Winter Simulation Conference 1989: 922-929 |