Google
Google Scholar
Semantic Scholar
MS Academic
CiteSeerX
ORCIDAlan S. Willsky
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
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
- [j120]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) - [j119]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
- [j118]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
- [j117]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
- [j116]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) - [j115]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) - [j114]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) - [j113]Myung Jin Choi, Antonio Torralba, Alan S. Willsky:
Context models and out-of-context objects. Pattern Recognit. Lett. 33(7): 853-862 (2012) - [j112]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) - [j111]Venkat Chandrasekaran, Pablo A. Parrilo, Alan S. Willsky:
Convex Graph Invariants. SIAM Rev. 54(3): 513-541 (2012) - [j110]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
- [j109]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) - [j108]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) - [j107]Venkat Chandrasekaran, Sujay Sanghavi, Pablo A. Parrilo, Alan S. Willsky:
Rank-Sparsity Incoherence for Matrix Decomposition. SIAM J. Optim. 21(2): 572-596 (2011) - [j106]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) - [j105]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) - [j104]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) - [j103]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-ECE 2011: 187-192 - [c118]James Saunderson, Venkat Chandrasekaran, Pablo A. Parrilo, Alan S. Willsky:
Tree-structured statistical modeling via convex optimization. CDC-ECE 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
- [j102]Erik B. Sudderth, Alexander T. Ihler, Michael Isard, William T. Freeman, Alan S. Willsky:
Nonparametric belief propagation. Commun. ACM 53(10): 95-103 (2010) - [j101]Kush R. Varshney, Alan S. Willsky:
Classification Using Geometric Level Sets. J. Mach. Learn. Res. 11: 491-516 (2010) - [j100]Dmitry M. Malioutov, Sujay Sanghavi, Alan S. Willsky:
Sequential Compressed Sensing. IEEE J. Sel. Top. Signal Process. 4(2): 435-444 (2010) - [j99]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) - [j98]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) - [j97]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) - [j96]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) - [j95]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) - [j94]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
- [j93]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
- [j92]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) - [j91]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) - [j90]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) - [j89]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) - [j88]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) - [j87]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
- [j86]Junmo Kim, Müjdat Çetin, Alan S. Willsky:
Nonparametric shape priors for active contour-based image segmentation. Signal Process. 87(12): 3021-3044 (2007) - [j85]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
- [j84]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) - [j83]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) - [j82]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) - [j81]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
- [j80]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) - [j79]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) - [j78]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) - [j77]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) - [j76]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) - [j75]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) - [j74]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) - [j73]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) - [j72]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]O. Patrick Kreidl, Alan S. Willsky:
Inference with Minimal Communication: a Decision-Theoretic Variational Approach. NIPS 2005: 675-682 - [c71]Erik B. Sudderth, Antonio Torralba, William T. Freeman, Alan S. Willsky:
Describing Visual Scenes using Transformed Dirichlet Processes. NIPS 2005: 1297-1304 - [i1]Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky:
MAP estimation via agreement on (hyper)trees: Message-passing and linear programming. CoRR abs/cs/0508070 (2005) - 2004
- [j71]Andy Tsai, William M. Wells III, Clare M. Tempany, Eric Grimson, Alan S. Willsky:
Mutual information in coupled multi-shape model for medical image segmentation. Medical Image Anal. 8(4): 429-445 (2004) - [j70]Martin J. Wainwright, Tommi S. Jaakkola, Alan S. Willsky:
Tree consistency and bounds on the performance of the max-product algorithm and its generalizations. Stat. Comput. 14(2): 143-166 (2004) - [j69]Alexander T. Ihler, John W. Fisher III, Alan S. Willsky:
Nonparametric hypothesis tests for statistical dependency.