Publications

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(Publications reporting on research supported by this MURI)
(Publications reporting on research supported by this MURI)
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'''''2014'''''
 
'''''2014'''''
  
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* S. Ahmad, and A. J. Yu, "A social aware Bayesian model for competitive foraging",  ''Proceedings of the Cognitive Science Society Conference,'' 2014. [http://www.cogsci.ucsd.edu/~ajyu/Papers/cogsci14_compforage.pdf" .pdf]
  
* S. Ahmad, and A. J. Yu (2014). "A social aware Bayesian model for competitive foraging"''Proceedings of the Cognitive Science Society Conference''.
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* J. Ash, E. Ertin, L. C. Potter, and E. Zelnio, "Wide-Angle Synthetic Aperture Radar Imaging: Models and algorithms for anisotropic scattering" ''IEEE Signal Processing Magazine'', vol. 31, no. 4, pp 16-26, 2014. [http://www.ece.osu.edu/~ertine/AshErtin2014.pdf .pdf]
[http://www.cogsci.ucsd.edu/~ajyu/Papers/cogsci14_compforage.pdf" .pdf]
+
  
* J. Ash, E. Ertin, L. Potter, and E. Zelnio. "Wide-Angle Synthetic Aperture Radar Imaging: Models and algorithms for anisotropic scattering." Signal Processing Magazine, IEEE 31, no. 4  16-26, 2014.  
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* R. Cabezas, O. Freifeld, G. Rosman, J. W. Fisher III, "Aerial reconstructions via probabilistic data fusion," ''IEEE Computer Vision and Pattern Recognition Conference on Computer Vision,'' June 2014. [http://people.csail.mit.edu/rcabezas/pubs/cabezas14_aerial.pdf .pdf]
[http://www.ece.osu.edu/~ertine/AshErtin2014.pdf .pdf]
+
  
* R. Cabezas, O. Freifeld, G. Rosman, J. Fisher III, "Aerial Reconstructions via Probabilistic Data Fusion." IEEE Computer Vision and Pattern Recognition Conference on Computer Vision, 2014. [http://people.csail.mit.edu/rcabezas/pubs/cabezas14_aerial.pdf]
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* L. Crider and D. Cochran, "Effects of network topology on the conditional distributions of surrogated generalized coherence estimates," ''Proceedings of the Asilomar Conference on Signals, Systems, and Computers,'' November 2014 (to appear).
  
* J. Duchi, M. I. Jordan, and B. McMahan, "Estimation, optimization, and parallelism when data is sparse," (2014).  In L. Bottou, C. Burges, Z. Ghahramani and M. Welling (Eds.), Advances in Neural Information Processing (NIPS) 26, Red Hook, NY: Curran Associates. [http://www.cs.berkeley.edu/~jordan/papers/duchi-jordan-mcmahan-nips14.pdf]
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* J. Duchi, M. I. Jordan, and B. McMahan, "Estimation, optimization, and parallelism when data is sparse," (2014).  In L. Bottou, C. Burges, Z. Ghahramani and M. Welling (Eds.), Advances in Neural Information Processing (NIPS) 26, Red Hook, NY: Curran Associates. [http://www.cs.berkeley.edu/~jordan/papers/duchi-jordan-mcmahan-nips14.pdf .pdf]
  
* J. Duchi, M. I. Jordan, and M. Wainwright, "Local privacy and minimax bounds: Sharp rates for probability estimation," (2014).  In L. Bottou, C. Burges, Z. Ghahramani and M. Welling (Eds.), Advances in Neural Information Processing (NIPS) 26, Red Hook, NY: Curran Associates. [http://www.cs.berkeley.edu/~jordan/papers/duchi-jordan-wainwright-nips14.pdf]
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* J. Duchi, M. I. Jordan, and M. Wainwright, "Local privacy and minimax bounds: Sharp rates for probability estimation," (2014).  In L. Bottou, C. Burges, Z. Ghahramani and M. Welling (Eds.), Advances in Neural Information Processing (NIPS) 26, Red Hook, NY: Curran Associates. [http://www.cs.berkeley.edu/~jordan/papers/duchi-jordan-wainwright-nips14.pdf .pdf]
  
* E. Ertin, "Three Dimensional Imaging of Vehicles from Sparse Apertures in Urban Environment," in "Compressive Sensing for Urban Radars," edited by Moeness Amin, CRC Press, 2014.
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* J. C. Duchi, M. I. Jordan, M. J. Wainwright, and Y. Zhang, "Information-theoretic lower bounds for distributed statistical estimation with communication constraints," [http://arxiv.org/pdf/1405.0782.pdf .pdf]
  
* F. Lindsten, M. I. Jordan, and T. Schoen, "Particle Gibbs with ancestral sampling," Journal of Machine Learning Research, 15, 2145-2184. [http://jmlr.org/papers/volume15/lindsten14a/lindsten14a.pdf].
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* Z. Dzunic and J. Fisher III, "Bayesian switching interaction analysis under uncertainty," ''Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics,'' pp. 220-228, 2014.
  
* J. Duchi, M. I. Jordan, M. Wainwright and A. Wibisono, "Finite sample convergence rates of zero-order stochastic optimization methods," (2013).  In P. Bartlett, F. Pereira, L. Bottou, and C. Burges (Eds.), Advances in Neural Information Processing (NIPS) 25, Red Hook, NY: Curran Associates. [http://www.cs.berkeley.edu/~jordan/papers/duchi-jordan-wainwright-wibisono-nips13.pdf]
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* E. Ertin, "Three dimensional imaging of vehicles from sparse apertures in urban environment," in ''Compressive Sensing for Urban Radars,'' M. Amin, ed., CRC Press, 2014.
  
* V. Karasev, A. Ravichandran, S. Soatto, "Active Frame, Location, and Detector Selection for Automated and Manual Video Annotation," in Proc. of the IEEE Conf. on Comp. Vis. and Patt. Recog., 2014
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* E. Ertin, "Information geometry of radar targets," ''Information Theory and Applications Workshop,'' San Diego, 2014.
  
* L. Mackey, M. I. Jordan, R. Y. Chen, B. Farrell and J. A. Tropp, "Matrix concentration inequalities via the method of exchangeable pairs," Annals of Probability, 42, 906-945. [http://arxiv.org/abs/1201.6002].
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* B. W. Hong and S. Soatto, "Shape Matching using Multiscale Integral Invariants," ''IEEE Transactions on Pattern Recognition and Machine Intelligence,'' July 2014. [http://vision.ucla.edu/papers/hongS14.pdf .pdf]
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* S. D. Howard, W. Moran, and D. Cochran, "Intrinsic Fisher information on manifolds," ''Proceedings of the Asilomar Conference on Signals, Systems, and Computers,'' November 2014 (to appear).
  
* G. Marjanovic and A.O. Hero, "On lq Estimation of Sparse Inverse Covariance," Proc. of IEEE Conf. on Acoustics, Speech and Signal Processing (ICASSP) 2014.
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* S. D. Howard, D. Cochran, W. Moran, and F. Cohen, "Estimation and registration on graphs," ''IEEE Transactions on Signal Processing'' (in review).
  
* B. Moore, R. Nadakuditi and J. Fessler, " Improved robust {PCA} using low-rank denoising with optimal singular value shrinkage," Proc. of IEEE SSP Workshop, 2014. [https://www.dropbox.com/s/atxfwikz491jrkw/ssp14_v3.pdf]
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* V. Karasev, A. Ravichandran, and S. Soatto, "Active Frame, Location, and Detector Selection for Automated and Manual Video Annotation," ''Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,'' 2014. [http://vision.ucla.edu/papers/karasevRS14.pdf pdf]
  
* G. Papachristoudis and J. W. Fisher III, "Efficient information planning in Markov chains," (under review).
+
* F. Lindsten, M. I. Jordan, and T. Schoen, "Particle Gibbs with ancestral sampling," ''Journal of Machine Learning Research,'' vol. 15, pp. 2145 - 2184, 2014. [http://jmlr.org/papers/volume15/lindsten14a/lindsten14a.pdf .pdf]
  
* G. Papachristoudis and J. W. Fisher III, "Incremental belief propagation," (under review).
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* L. Mackey, M. I. Jordan, R. Chen, B. Farrell, and J. A. Tropp, "Matrix concentration inequalities via the method of exchangeable pairs," ''Annals of Probability,'' vol. 42, pp. 906 - 945, 2014. [http://arxiv.org/abs/1201.6002 .pdf]
  
* X. Zhang, R. Nadakuditi and M. E. J. Newman, "Spectra of random graphs with community structure and arbitrary degrees," Physical Review E., 89(4), 042816, 2014. [http://arxiv.org/pdf/1310.0046.pdf]
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* G. Marjanovic and A. O. Hero, "On lq Estimation of Sparse Inverse Covariance," ''Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing'' (ICASSP), May 2014.
* T. Tsiligkaridis, B. M. Sadler and A.O. Hero, "Collaborative 20 questions for localization," IEEE Trans on Information Theory. In press. Available as arXiv:1306.1922 [http://arxiv.org/pdf/1306.1922.pdf .pdf]
+
  
* D. Wei and A. O. Hero, "Multistage adaptive estimation of sparse signals," ''IEEE Journal of Selected Topics in Signal Processing'' (in press). [http://arxiv.org/pdf/1210.1473v2.pdf .pdf]
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* Z. Meng, B. Erikson, A.O. Hero, "Learning Latent Variable Gaussian Graphical Models," ''Proceedings of the International Conference on Machine Learning (ICML),'' Beijing, July 2014. [http://arxiv.org/pdf/1406.2721.pdf .pdf]
  
* F. Wauthier, N. Jojic, and M. I. Jordan, "A comparative framework for preconditioned Lasso algorithms," (2014). In L. Bottou, C. Burges, Z. Ghahramani and M. Welling (Eds.), Advances in Neural Information Processing (NIPS) 26, Red Hook, NY: Curran Associates.
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* Z. Meng, D. Wei, A. Wiesel, and A.O. Hero, "Distributed Learning of Gaussian Graphical Models via Marginal Likelihoods," ''IEEE Transactions on Signal Processing'' (to appear). [http://arxiv.org/pdf/1303.4756.pdf .pdf]
  
* G. T. Whipps, E. Ertin and R. L. Moses, “Distributed Detection of Binary Decisions with Collisions in a Large, Random Network,submitted to IEEE Transactions on SP (in review), 2014. [http://www.ece.osu.edu/~ertine/whipps2014a.pdf  .pdf]
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* B. Moore, R. R.~Nadakuditi, and J. Fessler, "Improved robust PCA using low-rank denoising with optimal singular value shrinkage," ''Proceedings of the IEEE Statistical Signal Processing Workshop, July 2014. [https://www.dropbox.com/s/atxfwikz491jrkw/ssp14_v3.pdf .pdf]
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* B. Mu, G. Chowdhary, and J. P. How, "Efficient distributed sensing using adaptive censoring-based inference," ''Automatica,'' vol. 50, no. 6, pp. 1590 - 1602, 2014.
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* B. Mu and J. P. How, "Learning Sparse Gaussian Graphical Model with l0-regularization," ''Advances in Neural Information Processing Systems 27'' (in review).
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* R. R. Nadakuditi, "OptShrink: An Algorithm for Improved Low-Rank Signal Matrix Denoising by Optimal, Data-Driven Singular Value Shrinkage," ''IEEE Transactions on Information Theory,'' vol. 60, no. 5, pp. 3002 - 3018, May 2014.
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* G. Newstadt, D. Wei and A. O. Hero, "Resource-Constrained Adaptive Search and Tracking for Sparse Dynamic Targets," ''IEEE Transactions on Signal Processing'' (in review). [http://arxiv.org/pdf/1404.2201.pdf .pdf]
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* G. E. Newstadt, B. Mu, D. Wei, A. O. Hero, and J. P. How, "Mission-weighted adaptive search for multi-class targets," ''IEEE Transaction on Signal Processing,'' (in preparation).
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* G. Papachristoudis and J. W. Fisher III, "Efficient information planning in Markov chains" (in  review). [http://people.csail.mit.edu/fisher/publications/papers/geopapa14infplntech.pdf .pdf]
 +
 
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* G. Papachristoudis and J. W. Fisher III, "Incremental belief propagation in Markov random trees" (in review). [http://people.csail.mit.edu/fisher/publications/papers/geopapa14incrbptech.pdf .pdf]
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* N. Sugavanam and E. Ertin, "Compressive measurement designs for structured signals in signal dependent noise," ''IEEE International Conference on Acoustics, Speech, and Signal Processing'' (submitted).
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* D. Teng and E. Ertin, "Optimal quantization of likelihood for sequential detection," ''IEEE Transactions on Signal Processing''(in review).
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* T. Tsiligkaridis, B. M. Sadler, and A. O. Hero, "Collaborative 20 questions for localization," ''IEEE Transactions on Information Theory.'' vol. 60, no. 4, pp 2233-2252, April 2014. [http://arxiv.org/pdf/1306.1922.pdf .pdf]
 +
 
 +
* T. Tsiligkaridis, B. M. Sadler and A. O. Hero III, "A collaborative 20 questions model for target search with human-machine interaction," ''IEEE Transactions on Signal Processing'' (in press) [http://arxiv.org/pdf/1306.1922.pdf .pdf]
 +
 
 +
* D. Wei and A. O. Hero, "Multistage adaptive estimation of sparse signals," ''IEEE Journal of Selected Topics in Signal Processing'' (in press). [http://arxiv.org/pdf/1210.1473v2.pdf .pdf]
  
* G. T. Whipps, E. Ertin and R. L. Moses, "A Consensus-based Decentralized EM for a Mixture of Factor Analyzers,"  IEEE International Workshop on Machine Learning for Signal Processing,  Sep 2014 [http://www.ece.osu.edu/~ertine/whipps2014b.pdf  .pdf]
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* G. T. Whipps, E. Ertin and R. L. Moses, "A Consensus-based Decentralized EM for a Mixture of Factor Analyzers,"  ''IEEE International Workshop on Machine Learning for Signal Processing'' (to appear) September 2014.
  
* T. Xie, N. Nasrabadi and A.O. Hero, "Learning to classify with possible sensor failures," Proc. of IEEE Conf. on Acoustics, Speech and Signal Processing (ICASSP) 2014.
+
* G. T. Whipps, E. Ertin and R. L. Moses, "Distributed detection of binary decisions with collisions in a large, random network," ''IEEE Transactions on Signal Processing''(in review).
  
* A. J. Yu, "Computational Models of Neuromodulation," ''Encyclopedia of Computational Neuroscience'', Springer, 2014.
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* T. Xie, N. Nasrabadi and A.O. Hero, "Learning to classify with possible sensor failures," ''Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),'' May 2014.
  
* A. J. Yu, "Decision Making Tasks," ''Encyclopedia of Computational Neuroscience'', Springer, 2014.
+
* X. Zhang, R. R. Nadakuditi, and M. Newman, "Spectra of random graphs with community structure and arbitrary degrees," ''Physical Review E,'' vol. 89, no. 4, 042816, 2014. [http://arxiv.org/pdf/1310.0046.pdf .pdf]
  
* Y. Zhang, J. Duchi, M. I. Jordan, and M. Wainwright, "Information-theoretic lower bounds for distributed statistical estimation with communication constraints," (2014).  In L. Bottou, C. Burges, Z. Ghahramani and M. Welling (Eds.), Advances in Neural Information Processing (NIPS) 26, Red Hook, NY: Curran Associates.
+
* Y. Zhang, X. Chen, D. Zhou, and M. I. Jordan, "Spectral methods meet EM: A provably optimal algorithm for crowdsourcing," ''Neural Information Processing Systems'' (in review).  http://arxiv.org/abs/1406.3824
  
* Y. Zhang, M. Wainwright, and M. I. Jordan," (2014),  "Lower bounds on the performance of polynomial-time algorithms for sparse linear regression," Annual Conference on Computational Learning Theory, Barcelona, Spain [http://arxiv.org/abs/1402.1918]
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* Y. Zhang, M. Wainwright, and M. I. Jordan, "Lower bounds on the performance of polynomial-time algorithms for sparse linear regression," ''Proceedings of the Annual Conference on Computational Learning Theory,'' 2014.  http://arxiv.org/abs/1402.1918
  
* Y. Zhang, X. Chen, D. Zhou, and M. I. Jordan," (2014),  "Spectral methods meet EM: A provably optimal algorithm for crowdsourcing," arXiv [http://arxiv.org/abs/1406.3824]
 
  
 
'''''2013'''''
 
'''''2013'''''

Revision as of 06:55, September 1, 2014

Publications 2012


Publications reporting on research supported by this MURI

publications: links to publications resulting from this program.


2014


2013

2012

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