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2020 – today
- 2020
[c132]Craig Carthel, Jordan LeNoach, Stefano Coraluppi, Alan S. Willsky, Brandon Bale:
Analysis of MHT and GBT Approaches to Disparate-Sensor Fusion. FUSION 2020: 1-7
2010 – 2019
- 2019
- [c131]Stefano P. Coraluppi, Craig A. Carthel, Alan S. Willsky:
Graph-Based Tracking with Uncertain ID Measurement Associations. FUSION 2019: 1-8 - 2017
- [c130]Stefano P. Coraluppi, Craig A. Carthel, Alan S. Willsky:
Multi-Sensor tracking of move-stop-move targets. SDF 2017: 1-6 - 2016
- [c129]Stefano Coraluppi, Craig Carthel, William Kreamer, Alan S. Willsky:
New graph-based and MCMC approaches to multi-INT surveillance. FUSION 2016: 394-401 - 2015
- [j126]James Saunderson
, Pablo A. Parrilo, Alan S. Willsky:
Semidefinite Descriptions of the Convex Hull of Rotation Matrices. SIAM J. Optim. 25(3): 1314-1343 (2015) - [j125]Ying Liu, Oliver Kosut, Alan S. Willsky:
Sampling From Gaussian Markov Random Fields Using Stationary and Non-Stationary Subgraph Perturbations. IEEE Trans. Signal Process. 63(3): 576-589 (2015) - [c128]Stefano Coraluppi, Craig Carthel, William Kreamer, Alan S. Willsky:
MCMC and MHT Approaches to Multi-INT surveillance. FUSION 2015: 2057-2064 - 2014
- [j124]Müjdat Çetin, Ivana Stojanovic, N. Özben Önhon, Kush R. Varshney, Sadegh Samadi, William Clement Karl, Alan S. Willsky:
Sparsity-Driven Synthetic Aperture Radar Imaging: Reconstruction, autofocusing, moving targets, and compressed sensing. IEEE Signal Process. Mag. 31(4): 27-40 (2014) - [c127]James Saunderson, Pablo A. Parrilo, Alan S. Willsky:
Semidefinite relaxations for optimization problems over rotation matrices. CDC 2014: 160-166 - [c126]Matthew James Johnson, Alan S. Willsky:
Stochastic Variational Inference for Bayesian Time Series Models. ICML 2014: 1854-1862 - 2013
- [j123]Matthew J. Johnson, Alan S. Willsky:
Bayesian nonparametric hidden semi-Markov models. J. Mach. Learn. Res. 14(1): 673-701 (2013) - [c125]James Saunderson, Pablo A. Parrilo, Alan S. Willsky:
Diagonal and low-rank decompositions and fitting ellipsoids to random points. CDC 2013: 6031-6036 - [c124]Ying Liu, Alan S. Willsky:
Recursive FMP for distributed inference in Gaussian graphical models. ISIT 2013: 2483-2487 - [c123]Ying Liu, Oliver Kosut, Alan S. Willsky:
Sampling from Gaussian graphical models using subgraph perturbations. ISIT 2013: 2498-2502 - [c122]Ying Liu, Alan S. Willsky:
Learning Gaussian Graphical Models with Observed or Latent FVSs. NIPS 2013: 1833-1841 - [c121]Matthew J. Johnson, James Saunderson, Alan S. Willsky:
Analyzing Hogwild Parallel Gaussian Gibbs Sampling. NIPS 2013: 2715-2723 - [i17]Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky:
A New Class of Upper Bounds on the Log Partition Function. CoRR abs/1301.0610 (2013) - [i16]Ying Liu, Alan S. Willsky:
Learning Gaussian Graphical Models with Observed or Latent FVSs. CoRR abs/1311.2241 (2013) - 2012
- [j122]Venkat Chandrasekaran, Benjamin Recht, Pablo A. Parrilo, Alan S. Willsky:
The Convex Geometry of Linear Inverse Problems. Found. Comput. Math. 12(6): 805-849 (2012) - [j121]Animashree Anandkumar, Vincent Y. F. Tan, Furong Huang, Alan S. Willsky:
High-dimensional Gaussian graphical model selection: walk summability and local separation criterion. J. Mach. Learn. Res. 13: 2293-2337 (2012) - [j120]Myung Jin Choi, Antonio Torralba, Alan S. Willsky:
A Tree-Based Context Model for Object Recognition. IEEE Trans. Pattern Anal. Mach. Intell. 34(2): 240-252 (2012) - [j119]Myung Jin Choi, Antonio Torralba, Alan S. Willsky:
Context models and out-of-context objects. Pattern Recognit. Lett. 33(7): 853-862 (2012) - [j118]James Saunderson, Venkat Chandrasekaran, Pablo A. Parrilo, Alan S. Willsky:
Diagonal and Low-Rank Matrix Decompositions, Correlation Matrices, and Ellipsoid Fitting. SIAM J. Matrix Anal. Appl. 33(4): 1395-1416 (2012) - [j117]Venkat Chandrasekaran, Pablo A. Parrilo, Alan S. Willsky:
Convex Graph Invariants. SIAM Rev. 54(3): 513-541 (2012) - [j116]Ying Liu, Venkat Chandrasekaran, Animashree Anandkumar, Alan S. Willsky:
Feedback Message Passing for Inference in Gaussian Graphical Models. IEEE Trans. Signal Process. 60(8): 4135-4150 (2012) - [c120]Venkat Chandrasekaran, Pablo A. Parrilo, Alan S. Willsky:
Convex graph invariants. CISS 2012: 1-6 - [i15]Matthew J. Johnson, Alan S. Willsky:
The Hierarchical Dirichlet Process Hidden Semi-Markov Model. CoRR abs/1203.3485 (2012) - [i14]Venkat Chandrasekaran, Pablo A. Parrilo, Alan S. Willsky:
Rejoinder: Latent variable graphical model selection via convex optimization. CoRR abs/1211.0835 (2012) - 2011
- [j115]Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky:
Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates. J. Mach. Learn. Res. 12: 1617-1653 (2011) - [j114]Myung Jin Choi, Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky:
Learning Latent Tree Graphical Models. J. Mach. Learn. Res. 12: 1771-1812 (2011) - [j113]Venkat Chandrasekaran, Sujay Sanghavi, Pablo A. Parrilo, Alan S. Willsky:
Rank-Sparsity Incoherence for Matrix Decomposition. SIAM J. Optim. 21(2): 572-596 (2011) - [j112]Vincent Y. F. Tan, Animashree Anandkumar, Lang Tong, Alan S. Willsky:
A Large-Deviation Analysis of the Maximum-Likelihood Learning of Markov Tree Structures. IEEE Trans. Inf. Theory 57(3): 1714-1735 (2011) - [j111]Sujay Sanghavi, Dmitry M. Malioutov, Alan S. Willsky:
Belief Propagation and LP Relaxation for Weighted Matching in General Graphs. IEEE Trans. Inf. Theory 57(4): 2203-2212 (2011) - [j110]Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky:
Bayesian Nonparametric Inference of Switching Dynamic Linear Models. IEEE Trans. Signal Process. 59(4): 1569-1585 (2011) - [j109]Kush R. Varshney, Alan S. Willsky:
Linear Dimensionality Reduction for Margin-Based Classification: High-Dimensional Data and Sensor Networks. IEEE Trans. Signal Process. 59(6): 2496-2512 (2011) - [c119]Vincent Y. F. Tan, Alan S. Willsky:
Sample complexity for topology estimation in networks of LTI systems. CDC/ECC 2011: 187-192 - [c118]James Saunderson, Venkat Chandrasekaran, Pablo A. Parrilo, Alan S. Willsky:
Tree-structured statistical modeling via convex optimization. CDC/ECC 2011: 2883-2888 - [c117]Paul Balister, Béla Bollobás, Animashree Anandkumar, Alan S. Willsky:
Energy-latency tradeoff for in-network function computation in random networks. INFOCOM 2011: 1575-1583 - [c116]Animashree Anandkumar, Vincent Y. F. Tan, Alan S. Willsky:
High-Dimensional Graphical Model Selection: Tractable Graph Families and Necessary Conditions. NIPS 2011: 1863-1871 - [i13]Paul N. Balister, Béla Bollobás, Animashree Anandkumar, Alan S. Willsky:
Energy-Latency Tradeoff for In-Network Function Computation in Random Networks. CoRR abs/1101.0858 (2011) - [i12]Ying Liu, Venkat Chandrasekaran, Animashree Anandkumar, Alan S. Willsky:
Feedback Message Passing for Inference in Gaussian Graphical Models. CoRR abs/1105.1853 (2011) - [i11]Animashree Anandkumar, Vincent Y. F. Tan, Alan S. Willsky:
High-Dimensional Gaussian Graphical Model Selection: Tractable Graph Families. CoRR abs/1107.1270 (2011) - [i10]Animashree Anandkumar, Vincent Y. F. Tan, Alan S. Willsky:
High-Dimensional Structure Estimation in Ising Models: Tractable Graph Families. CoRR abs/1107.1736 (2011) - 2010
- [j108]Erik B. Sudderth, Alexander T. Ihler, Michael Isard, William T. Freeman, Alan S. Willsky:
Nonparametric belief propagation. Commun. ACM 53(10): 95-103 (2010) - [j107]Kush R. Varshney, Alan S. Willsky:
Classification Using Geometric Level Sets. J. Mach. Learn. Res. 11: 491-516 (2010) - [j106]Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Willsky:
Sequential Compressed Sensing. IEEE J. Sel. Top. Signal Process. 4(2): 435-444 (2010) - [j105]Alan S. Willsky:
Paths Ahead in the Science of Information and Decision Systems [In the Spotlight]. IEEE Signal Process. Mag. 27(2): 160-158 (2010) - [j104]Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky:
Bayesian Nonparametric Methods for Learning Markov Switching Processes. IEEE Signal Process. Mag. 27(6): 43-54 (2010) - [j103]O. Patrick Kreidl, Alan S. Willsky:
An Efficient Message-Passing Algorithm for Optimizing Decentralized Detection Networks. IEEE Trans. Autom. Control. 55(3): 563-578 (2010) - [j102]Myung Jin Choi, Venkat Chandrasekaran, Alan S. Willsky:
Gaussian multiresolution models: exploiting sparse Markov and covariance structure. IEEE Trans. Signal Process. 58(3): 1012-1024 (2010) - [j101]Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky:
Learning Gaussian tree models: analysis of error exponents and extremal structures. IEEE Trans. Signal Process. 58(5): 2701-2714 (2010) - [j100]Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher III, Alan S. Willsky:
Learning graphical models for hypothesis testing and classification. IEEE Trans. Signal Process. 58(11): 5481-5495 (2010) - [c115]Myung Jin Choi, Joseph J. Lim, Antonio Torralba, Alan S. Willsky:
Exploiting hierarchical context on a large database of object categories. CVPR 2010: 129-136 - [c114]Vincent Y. F. Tan, Matthew J. Johnson, Alan S. Willsky:
Necessary and sufficient conditions for high-dimensional salient feature subset recovery. ISIT 2010: 1388-1392 - [c113]Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky:
Error exponents for composite hypothesis testing of Markov forest distributions. ISIT 2010: 1613-1617 - [c112]Ying Liu, Venkat Chandrasekaran, Animashree Anandkumar, Alan S. Willsky:
Feedback message passing for inference in gaussian graphical models. ISIT 2010: 1683-1687 - [c111]Animashree Anandkumar, Joseph E. Yukich, Alan S. Willsky:
Limit laws for random spatial graphical models. ISIT 2010: 1728-1732 - [c110]Matthew J. Johnson, Alan S. Willsky:
The Hierarchical Dirichlet Process Hidden Semi-Markov Model. UAI 2010: 252-259 - [i9]Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Willsky:
Sequential Compressed Sensing. CoRR abs/1003.0219 (2010) - [i8]Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky:
Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates. CoRR abs/1005.0766 (2010) - [i7]Myung Jin Choi, Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky:
Learning Latent Tree Graphical Models. CoRR abs/1009.2722 (2010) - [i6]Venkat Chandrasekaran, Pablo A. Parrilo, Alan S. Willsky:
Convex Graph Invariants. CoRR abs/1012.0623 (2010)
2000 – 2009
- 2009
- [j99]Sujay Sanghavi, Devavrat Shah, Alan S. Willsky:
Message passing for maximum weight independent set. IEEE Trans. Inf. Theory 55(11): 4822-4834 (2009) - [c109]Zhexu Chen, Lei Chen, Müjdat Çetin, Alan S. Willsky:
An efficient message passing algorithm for multi-target tracking. FUSION 2009: 826-833 - [c108]Kush R. Varshney, Alan S. Willsky:
Learning dimensionality-reduced classifiers for information fusion. FUSION 2009: 1881-1888 - [c107]Marco A. Pravia, Olga Babko-Malaya, Michael K. Schneider, James V. White, Chee-Yee Chong, Alan S. Willsky:
Lessons learned in the creation of a data set for hard/soft information fusion. FUSION 2009: 2114-2121 - [c106]Myung Jin Choi, Venkat Chandrasekaran, Alan S. Willsky:
Exploiting sparse Markov and covariance structure in multiresolution models. ICML 2009: 177-184 - [c105]Vincent Y. F. Tan, Animashree Anandkumar, Lang Tong, Alan S. Willsky:
A large-deviation analysis for the maximum likelihood learning of tree structures. ISIT 2009: 1140-1144 - [c104]Animashree Anandkumar, Alan S. Willsky, Lang Tong:
Detection error exponent for spatially dependent samples in random networks. ISIT 2009: 2882-2886 - [c103]Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky:
Sharing Features among Dynamical Systems with Beta Processes. NIPS 2009: 549-557 - [i5]Vincent Y. F. Tan, Animashree Anandkumar, Lang Tong, Alan S. Willsky:
A Large-Deviation Analysis of the Maximum-Likelihood Learning of Markov Tree Structures. CoRR abs/0905.0940 (2009) - [i4]Vincent Y. F. Tan, Animashree Anandkumar, Alan S. Willsky:
Learning Gaussian Tree Models: Analysis of Error Exponents and Extremal Structures. CoRR abs/0909.5216 (2009) - 2008
- [j98]Erik B. Sudderth, Antonio Torralba, William T. Freeman, Alan S. Willsky:
Describing Visual Scenes Using Transformed Objects and Parts. Int. J. Comput. Vis. 77(1-3): 291-330 (2008) - [j97]Jason K. Johnson, Alan S. Willsky:
A Recursive Model-Reduction Method for Approximate Inference in Gaussian Markov Random Fields. IEEE Trans. Image Process. 17(1): 70-83 (2008) - [j96]Walter Sun, Müjdat Çetin, Raymond C. Chan, Alan S. Willsky:
Learning the Dynamics and Time-Recursive Boundary Detection of Deformable Objects. IEEE Trans. Image Process. 17(11): 2186-2200 (2008) - [j95]Venkat Chandrasekaran, Jason K. Johnson, Alan S. Willsky:
Estimation in Gaussian Graphical Models Using Tractable Subgraphs: A Walk-Sum Analysis. IEEE Trans. Signal Process. 56(5): 1916-1930 (2008) - [j94]Kush R. Varshney, Müjdat Çetin, John W. Fisher III, Alan S. Willsky:
Sparse Representation in Structured Dictionaries With Application to Synthetic Aperture Radar. IEEE Trans. Signal Process. 56(8-1): 3548-3561 (2008) - [j93]Dmitry M. Malioutov, Jason K. Johnson, Myung Jin Choi, Alan S. Willsky:
Low-Rank Variance Approximation in GMRF Models: Single and Multiscale Approaches. IEEE Trans. Signal Process. 56(10-1): 4621-4634 (2008) - [c102]Ayres C. Fan, John W. Fisher III, Jonathan Kane, Alan S. Willsky:
MCMC curve sampling and geometric conditional simulation. Computational Imaging 2008: 681407 - [c101]Vincent Y. F. Tan, John W. Fisher III, Alan S. Willsky:
Learning max-weight discriminative forests. ICASSP 2008: 1877-1880 - [c100]Myung Jin Choi, Venkat Chandrasekaran, Alan S. Willsky:
Maximum entropy relaxation for multiscale graphical model selection. ICASSP 2008: 1889-1892 - [c99]Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Willsky:
Compressed sensing with sequential observations. ICASSP 2008: 3357-3360 - [c98]Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky:
An HDP-HMM for systems with state persistence. ICML 2008: 312-319 - [c97]Walter Sun, Müjdat Çetin, Raymond C. Chan, Alan S. Willsky:
Segmentation of the evolving left ventricle by learning the dynamics. ISBI 2008: 229-232 - [c96]Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky:
Nonparametric Bayesian Learning of Switching Linear Dynamical Systems. NIPS 2008: 457-464 - [i3]Sujay Sanghavi, Devavrat Shah, Alan S. Willsky:
Message-passing for Maximum Weight Independent Set. CoRR abs/0807.5091 (2008) - 2007
- [j92]Junmo Kim, Müjdat Çetin, Alan S. Willsky:
Nonparametric shape priors for active contour-based image segmentation. Signal Process. 87(12): 3021-3044 (2007) - [j91]Emily B. Fox, John W. Fisher III, Alan S. Willsky:
Detection and Localization of Material Releases With Sparse Sensor Configurations. IEEE Trans. Signal Process. 55(5-1): 1886-1898 (2007) - [c95]Andy Tsai, Carl-Fredrik Westin, Alfred O. Hero III, Alan S. Willsky:
Fiber Tract Clustering on Manifolds With Dual Rooted-Graphs. CVPR 2007 - [c94]Erik Blasch, Randolph L. Moses, David A. Castañón, Alan S. Willsky, Alfred O. Hero III:
Integrated fusion, performance prediction, and sensor management for automatic target exploitation AFOSR MURI. FUSION 2007: 1 - [c93]Emily B. Fox, Erik B. Sudderth, Alan S. Willsky:
Hierarchical Dirichlet processes for tracking maneuvering targets. FUSION 2007: 1-8 - [c92]Jason L. Williams, John W. Fisher III, Alan S. Willsky:
Performance Guarantees for Information Theoretic Sensor Resource Management. ICASSP (3) 2007: 933-936 - [c91]Dmitry M. Malioutov, Jason K. Johnson, Alan S. Willsky:
GMRF Variance Approximation using Splicedwavelet Bases. ICASSP (3) 2007: 1101-1104 - [c90]Ayres C. Fan, John W. Fisher III, William M. Wells III, James J. Levitt, Alan S. Willsky:
MCMC Curve Sampling for Image Segmentation. MICCAI (2) 2007: 477-485 - [c89]Venkat Chandrasekaran, Jason K. Johnson, Alan S. Willsky:
Adaptive Embedded Subgraph Algorithms using Walk-Sum Analysis. NIPS 2007: 249-256 - [c88]Sujay Sanghavi, Dmitry M. Malioutov, Alan S. Willsky:
Linear programming analysis of loopy belief propagation for weighted matching. NIPS 2007: 1273-1280 - [c87]Sujay Sanghavi, Devavrat Shah, Alan S. Willsky:
Message Passing for Max-weight Independent Set. NIPS 2007: 1281-1288 - [c86]Erik B. Sudderth, Martin J. Wainwright, Alan S. Willsky:
Loop Series and Bethe Variational Bounds in Attractive Graphical Models. NIPS 2007: 1425-1432 - [c85]Jason K. Johnson, Venkat Chandrasekaran, Alan S. Willsky:
Learning Markov Structure by Maximum Entropy Relaxation. AISTATS 2007: 203-210 - [c84]Jason L. Williams, John W. Fisher III, Alan S. Willsky:
Performance Guarantees for Information Theoretic Active Inference. AISTATS 2007: 620-627 - [i2]Jason K. Johnson, Dmitry M. Malioutov, Alan S. Willsky:
Lagrangian Relaxation for MAP Estimation in Graphical Models. CoRR abs/0710.0013 (2007) - 2006
- [j90]Dmitry M. Malioutov, Jason K. Johnson, Alan S. Willsky:
Walk-Sums and Belief Propagation in Gaussian Graphical Models. J. Mach. Learn. Res. 7: 2031-2064 (2006) - [j89]Lei Chen, Martin J. Wainwright, Müjdat Çetin, Alan S. Willsky:
Data association based on optimization in graphical models with application to sensor networks. Math. Comput. Model. 43(9-10): 1114-1135 (2006) - [j88]Lakshminarayan Srinivasan, Uri T. Eden, Alan S. Willsky, Emery N. Brown:
A State-Space Analysis for Reconstruction of Goal-Directed Movements Using Neural Signals. Neural Comput. 18(10): 2465-2494 (2006) - [j87]Müjdat Çetin, Lei Chen, John W. Fisher III, Alexander T. Ihler, Randolph L. Moses, Martin J. Wainwright, Alan S. Willsky:
Distributed fusion in sensor networks. IEEE Signal Process. Mag. 23(4): 42-55 (2006) - [j86]Walter Sun, Müjdat Çetin, W. Carlisle Thacker, Toshio Mike Chin, Alan S. Willsky:
Variational approaches on discontinuity localization and field estimation in sea surface temperature and soil moisture. IEEE Trans. Geosci. Remote. Sens. 44(2): 336-350 (2006) - [c83]O. Patrick Kreidl, Alan S. Willsky:
An Efficient Message-Passing Algorithm for Optimizing Decentralized Detection Networks. CDC 2006: 6776-6783 - [c82]Erik B. Sudderth, Antonio Torralba, William T. Freeman, Alan S. Willsky:
Depth from Familiar Objects: A Hierarchical Model for 3D Scenes. CVPR (2) 2006: 2410-2417 - [c81]Dmitry M. Malioutov, Jason K. Johnson, Alan S. Willsky:
Low-Rank Variance Estimation in Large-Scale Gmrf Models. ICASSP (3) 2006: 676-679 - [c80]Emily B. Fox, Jason L. Williams, John W. Fisher III, Alan S. Willsky:
Detection and Localization of Material Releases with Sparse Sensor Configurations. ICASSP (4) 2006: 945-948 - 2005
- [j85]A. Ben Hamza, Yun He, Hamid Krim, Alan S. Willsky:
A multiscale approach to pixel-level image fusion. Integr. Comput. Aided Eng. 12(2): 135-146 (2005) - [j84]Alexander T. Ihler, John W. Fisher III, Alan S. Willsky:
Loopy Belief Propagation: Convergence and Effects of Message Errors. J. Mach. Learn. Res. 6: 905-936 (2005) - [j83]Alexander T. Ihler, John W. Fisher III, Randolph L. Moses, Alan S. Willsky:
Nonparametric belief propagation for self-localization of sensor networks. IEEE J. Sel. Areas Commun. 23(4): 809-819 (2005) - [j82]Andy Tsai, William M. Wells III, Simon K. Warfield, Alan S. Willsky:
An EM algorithm for shape classification based on level sets. Medical Image Anal. 9(5): 491-502 (2005) - [j81]Junmo Kim, John W. Fisher III, Anthony J. Yezzi, Müjdat Çetin, Alan S. Willsky:
A Nonparametric Statistical Method for Image Segmentation Using Information Theory and Curve Evolution. IEEE Trans. Image Process. 14(10): 1486-1502 (2005) - [j80]Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky:
A new class of upper bounds on the log partition function. IEEE Trans. Inf. Theory 51(7): 2313-2335 (2005) - [j79]Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky:
MAP estimation via agreement on trees: message-passing and linear programming. IEEE Trans. Inf. Theory 51(11): 3697-3717 (2005) - [j78]Ilya Pollak, Alan S. Willsky, Yan Huang:
Nonlinear evolution equations as fast and exact solvers of estimation problems. IEEE Trans. Signal Process. 53(2-1): 484-498 (2005) - [j77]Dmitry M. Malioutov, Müjdat Çetin, Alan S. Willsky:
A sparse signal reconstruction perspective for source localization with sensor arrays. IEEE Trans. Signal Process. 53(8-2): 3010-3022 (2005) - [c79]Junmo Kim, Müjdat Çetin, Alan S. Willsky:
Nonparametric shape priors for active contour-based image segmentation. EUSIPCO 2005: 1-4 - [c78]Dmitry M. Malioutov, Müjdat Çetin, Alan S. Willsky:
Homotopy continuation for sparse signal representation. ICASSP (5) 2005: 733-736 - [c77]Jason L. Williams, John W. Fisher III, Alan S. Willsky:
Optimization approaches to dynamic routing of measurements and models in a sensor network object tracking problem. ICASSP (5) 2005: 1061-1064 - [c76]Michael Siracusa, Kinh Tieu, Alexander T. Ihler, John W. Fisher III, Alan S. Willsky:
Estimating dependency and significance for high-dimensional data. ICASSP (5) 2005: 1085-1088 - [c75]Erik B. Sudderth, Antonio Torralba, William T. Freeman, Alan S. Willsky:
Learning Hierarchical Models of Scenes, Objects, and Parts. ICCV 2005: 1331-1338 - [c74]Walter Sun, Müjdat Çetin, Raymond C. Chan, Vivek Y. Reddy, Godtfred Holmvang, Venkat Chandar, Alan S. Willsky:
Segmenting and Tracking the Left Ventricle by Learning the Dynamics in Cardiac Images. IPMI 2005: 553-565 - [c73]Jason K. Johnson, Dmitry M. Malioutov, Alan S. Willsky:
Walk-Sum Interpretation and Analysis of Gaussian Belief Propagation. NIPS 2005: 579-586 - [c72]