Publications

Revision as of 20:11, January 14, 2017 (view source) Hyechung (Talk | contribs) (→Publications reporting on research supported by this MURI) ← Older edit		Latest revision as of 21:55, January 14, 2017 (view source) Hyechung (Talk | contribs) (→Publications reporting on research supported by this MURI)
(5 intermediate revisions by one user not shown)
Line 17:		Line 17:
	'''''2016'''''		'''''2016'''''
−
	* A. El Alaoui, X. Cheng, A. Ramdas, M. Wainwright, and M. I. Jordan, "Asymptotic behavior of $\ell_p$-based Laplacian regularization in semi-supervised learning",  Proceedings of the Conference on Computational Learning Theory (COLT), New York, NY, June 2016. [https://arxiv.org/pdf/1603.00564v1.pdf .pdf].		* A. El Alaoui, X. Cheng, A. Ramdas, M. Wainwright, and M. I. Jordan, "Asymptotic behavior of $\ell_p$-based Laplacian regularization in semi-supervised learning",  Proceedings of the Conference on Computational Learning Theory (COLT), New York, NY, June 2016. [https://arxiv.org/pdf/1603.00564v1.pdf .pdf].
Line 27:		Line 26:
	* H.-W. Chung, L. Zheng, B. Sadler, A.O. Hero, "Unequal Error Protection Coding Approaches to the Noisy 20 Questions Problem," IEEE Intl Conf. on Information Theory (ISIT), July 2016, Barcelona Spain. [http://web.eecs.umich.edu/~hero/Preprints/UEP_ISIT2016_final.pdf .pdf].		* H.-W. Chung, L. Zheng, B. Sadler, A.O. Hero, "Unequal Error Protection Coding Approaches to the Noisy 20 Questions Problem," IEEE Intl Conf. on Information Theory (ISIT), July 2016, Barcelona Spain. [http://web.eecs.umich.edu/~hero/Preprints/UEP_ISIT2016_final.pdf .pdf].
−	* K. Greenewald, E. Zelnio, A.O. Hero III, "Kronecker PCA Based Robust SAR STAP," IEEE Trans on Aerospace and Electronic Systems (AES), 2016. [http://arxiv.org/pdf/1502:07481 .pdf].	+	* X. Gong, J. Zhang, D. Cochran, and K. Xing, "Optimal placement for barrier coverage in bistatic radar sensor networks,'' IEEE/ACM Transactions on Networking}, vol. 24, no. 1, pp. 259--271, 2016. [http://cochran.faculty.asu.edu/papers/2014_Gong_Barrier_IEEEToN.pdf .pdf]
−	*K. Greenewald, E. Zelnio and A.O. Hero, "Kronecker STAP and SAR GMTI," Proceedings of SPIE Symposium on Defense, Sensing and Security April 2016. [https://arxiv.org/pdf/1604.03622.pdf .pdf].	+	* K. Greenewald, E. Zelnio, A.O. Hero III, "Kronecker PCA Based Robust SAR STAP," IEEE Trans on Aerospace and Electronic Systems (AES), 2016. [https://arxiv.org/pdf/1501.07481v3.pdf .pdf].
		+
		+	*K. Greenewald, E. Zelnio and A.O. Hero, "Kronecker STAP and SAR GMTI," Proceedings of SPIE Symposium on Defense, Sensing and Security April 2016. [https://arxiv.org/pdf/1604.03622v1.pdf .pdf].
	*N. Halay, K. Todros and A.O. Hero, "Measure transformed quasi-likelihood ratio test for Bayesian binary hypothesis testing," IEEE Workshop on Statistical Signal Processing (SSP), Pamplona Spain, June 2016. [http://web.eecs.umich.edu/~hero/Preprints/SSP16_Todros_PAPER.pdf .pdf].		*N. Halay, K. Todros and A.O. Hero, "Measure transformed quasi-likelihood ratio test for Bayesian binary hypothesis testing," IEEE Workshop on Statistical Signal Processing (SSP), Pamplona Spain, June 2016. [http://web.eecs.umich.edu/~hero/Preprints/SSP16_Todros_PAPER.pdf .pdf].
Line 36:		Line 37:
	* J. Lee, M. Simchowitz, B. Recht, and M. I. Jordan, "Gradient descent only converges to minimizers,"  Proceedings of the Conference on Computational Learning Theory (COLT), New York, NY, June 2016. [https://arxiv.org/abs/1602.04915v2.pdf .pdf].		* J. Lee, M. Simchowitz, B. Recht, and M. I. Jordan, "Gradient descent only converges to minimizers,"  Proceedings of the Conference on Computational Learning Theory (COLT), New York, NY, June 2016. [https://arxiv.org/abs/1602.04915v2.pdf .pdf].
		+
		+	*  L. Li, V. Malave, A. Song, and A. J. Yu, "Extracting human face similarity judgments: Pairs or triplets?," Proceedings of the Thirty-Eighth Annual Conference of the Cognitive Science Society, 2016. [https://mindmodeling.org/cogsci2016/papers/0253/paper0253.pdf .pdf].
		+
		+	* Q. Liu, J.D. Lee, M.I. Jordan, "A kernelized Stein discrepancy for goodness-of-fit tests," In Proceedings of the International Conference on Machine Learning (ICML) Sep 2016. [http://www.jmlr.org/proceedings/papers/v48/liub16.pdf .pdf].
		+
		+	* B. Moore and R. R. Nadakuditi, “Robust pca: Low rank matrix estimation with hard or soft thresholding based outlier rejection,'' in Proceedings of IEEE GlobalSIP conference, 2016. [http://www.ieeeglobalsip.org/Papers/ViewPapers.asp?PaperNum=1526 .html].
		+
		+	* B. Mu, S.-Y. Liu, L. Paull, J. Leonard, and J. P. How, “Slam with objects using a nonparametric pose graph,'' in Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on, Oct 2016. [http://ieeexplore.ieee.org/document/7759677/ .html].
		+
		+	* B. Mu, L. Paull, A. Akbar Agha-mohammadi, J. How, and J. Leonard, “Two-stage focused inference for resource-constrained minimal collision navigation,'' IEEE Transactions on Robotics, 2016 (conditionally accepted).  [http://www.roboticsproceedings.org/rss11/p04.pdf .pdf].
		+
		+	* G. E. Newstadt, B. Mu, D. Wei, J. P. How, A. O. Hero III, "Importance-weighted adaptive search for multi-class targets," IEEE Trans on Signal Processing, vol. 63, no. 23, 6299-6314, Dec. 2015.  [https://arxiv.org/pdf/1603.00564v1.pdf .pdf].
		+
		+	* S. Ravishankar, B. E. Moore, R. R. Nadakuditi, and J. A. Fessler, “Lassi: A low-rank and adaptive sparse signal model for highly accelerated dynamic imaging,'' in IEEE Image, Video, and Multidimensional Signal Processing Workshop (IVMSP), pp. 1–5,  2016. [https://arxiv.org/pdf/1611.04069v2.pdf  .pdf].
		+
		+	* S. Ravishankar, R. R. Nadakuditi, and J. A. Fessler, “Efficient learning of dictionaries with low rank atoms,'' in  Proceedings of IEEE GlobalSIP conference, 2016. [http://www.ieeeglobalsip.org/Papers/ViewPapers.asp?PaperNum=1471  .pdf].
		+
		+	* S. Ravishankar, R. R. Nadakuditi, and J. A. Fessler, “Sum of outer products dictionary learning for inverse problems,'' in Proceedings of IEEE GlobalSIP conference, 2016. [https://arxiv.org/pdf/1511.08842v1.pdf  .pdf].
		+
		+	* S. Soatto, “Visual inertial semantic scene representation,'' UCLA TR CSD160005, May 20, 2016. [https://arxiv.org/pdf/1606.03968v1.pdf .pdf].
		+
		+	* S. Soatto and A. Chiuso, “Visual representations: Defining properties and deep approximations,'' Proc. of the Intl. Conf. on Learning Representations (ICLR); ArXiv: 1411.7676, May 2016. [https://arxiv.org/pdf/1411.7676v9.pdf .pdf].
		+
		+	* N. Sugavanam, S. Baskar, and E. Ertin, “Recovery guarantees for high resolution radar sensing with compressive illumination,”€ Fourth International Conference on Compressive Sensing applied to Radar (COSERA2016), Sep 2016. [https://arxiv.org/pdf/1508.07969.pdf .pdf].
		+
		+	* N. Sugavanam and E. Ertin, “Recovery guarantees for high resolution radar sensing with compressive illumination,” chapter in Compressive Sensing of Earth Observations,edited by C. Chen,  CRC Press, 2016. [https://arxiv.org/pdf/1508.07969.pdf .pdf].
		+
		+	*  D. Teng and E. Ertin, “Wald-kernel: A method for learning sequential detectors,” in Proceedings of IEEE Statistical Signal Processing (SSP2016), June 2016. [http://ieeexplore.ieee.org/document/7551760/  .pdf].
		+
		+	* D. Wang, J. Fisher III, and Q. Liu, “Efficient observation selection in probabilistic graphical models using bayesian lower bounds,'' in Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, pp.  755--764. AUAI Press, 2016. [http://auai.org/uai2016/proceedings/papers/83.pdf .html].
		+
		+	* G. T. Whipps, E. Ertin, and R. L. . Moses, “Constrained fisher scoring for a mixture of factor analyzers,” Army Research Labaratory, Tech. Rep. ARL-TR-7836, 2016.
	* T.-P. Xie, N. Nasrabadi, A.O. Hero, "Learning to classify with possible sensor failures,"  IEEE Transactions on Signal Processing, 2016.  [http://arxiv.org/pdf/1507.04540 .pdf].		* T.-P. Xie, N. Nasrabadi, A.O. Hero, "Learning to classify with possible sensor failures,"  IEEE Transactions on Signal Processing, 2016.  [http://arxiv.org/pdf/1507.04540 .pdf].
Line 69:		Line 102:
	* B. Farrell and R. Nadakuditi, " Local spectrum of truncations of Kronecker products of Haar distributed unitary matrices", Random Matrices: Theory and Applications, vol. 4, no. 1, 1550001, 2015. [http://arxiv.org/pdf/1311.6783v1.pdf]		* B. Farrell and R. Nadakuditi, " Local spectrum of truncations of Kronecker products of Haar distributed unitary matrices", Random Matrices: Theory and Applications, vol. 4, no. 1, 1550001, 2015. [http://arxiv.org/pdf/1311.6783v1.pdf]
		+
		+	* O. Freifeld, K. Batmanghelich, J. W. Fisher, et al., “Highly-expressive spaces of well-behaved transformations: Keeping it simple,'' in IEEE International Conference on Computer Vision (ICCV), pp.  2911--2919. 2015. [http://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Freifeld_Highly-Expressive_Spaces_of_ICCV_2015_paper.pdf  .pdf].
	* G. Georgiadis, A. Chiuso and S. Soatto, "Texture representations for image and video texture synthesis", ''Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition'', 2015. [http://vision.ucla.edu/papers/georgiadisCS15.pdf .pdf]		* G. Georgiadis, A. Chiuso and S. Soatto, "Texture representations for image and video texture synthesis", ''Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition'', 2015. [http://vision.ucla.edu/papers/georgiadisCS15.pdf .pdf]
Line 75:		Line 110:
	* S. Gogineni, P. Setlur, R. Nadakuditi and M. Rangaswamy, "Random matrix theory inspired passive bistatic radar detection of low-rank signals," Proceedings of IEEE Radar Conference, pp. 1656-1659, 2015. [http://dx.doi.org/10.1109/RADAR.2015.7131264] [http://cochran.faculty.asu.edu/papers/Gogineni_Radar.pdf .pdf]		* S. Gogineni, P. Setlur, R. Nadakuditi and M. Rangaswamy, "Random matrix theory inspired passive bistatic radar detection of low-rank signals," Proceedings of IEEE Radar Conference, pp. 1656-1659, 2015. [http://dx.doi.org/10.1109/RADAR.2015.7131264] [http://cochran.faculty.asu.edu/papers/Gogineni_Radar.pdf .pdf]
		+
		+	* M. Graham, J. How, and D. Gustafson, “Robust incremental {SLAM} with consistency-checking,'' in Intelligent Robots and Systems (IROS), IEEE/RSJ International Conference on, pp.  117--124, Sept 2015. [http://ieeexplore.ieee.org/document/7353363/?reload=true&arnumber=7353363  .html].
	* K. Greenewald, E. Zelnio, A.O. Hero III, "Kronecker PCA Based Robust SAR STAP," submitted Jan 2015. [http://arxiv.org/pdf/1501.07481 .pdf]		* K. Greenewald, E. Zelnio, A.O. Hero III, "Kronecker PCA Based Robust SAR STAP," submitted Jan 2015. [http://arxiv.org/pdf/1501.07481 .pdf]
Line 87:		Line 124:
	* K.J. Hsiao, J. Calder and A.O. Hero, "Pareto-depth for Multiple-query Image Retrieval," IEEE Trans on Image Processing, vol. 24, no. 2, pp. 583-594, 2015. [http://web.eecs.umich.edu/~hero/Preprints/hsiao-tip2015_final.pdf .pdf]		* K.J. Hsiao, J. Calder and A.O. Hero, "Pareto-depth for Multiple-query Image Retrieval," IEEE Trans on Image Processing, vol. 24, no. 2, pp. 583-594, 2015. [http://web.eecs.umich.edu/~hero/Preprints/hsiao-tip2015_final.pdf .pdf]
		+
		+	* Q. Liu, J. W. Fisher III, and A. T. Ihler, “Probabilistic variational bounds for graphical models,'' in Advances in Neural Information Processing Systems, pp.  1432--1440, 2015. [http://www.cs.dartmouth.edu/~qliu/PDF/NIPS15TRW.pdf .pdf].
	* Q. Liu, A. Ihler, J. W. Fisher III, "Boosting Crowdsourcing With Expert Labels: Local vs. Global Effects", International Conference on Information Fusion (Fusion), 2015. [http://www.cs.dartmouth.edu/~qliu/PDF/FusionCrowd15.pdf]		* Q. Liu, A. Ihler, J. W. Fisher III, "Boosting Crowdsourcing With Expert Labels: Local vs. Global Effects", International Conference on Information Fusion (Fusion), 2015. [http://www.cs.dartmouth.edu/~qliu/PDF/FusionCrowd15.pdf]

---

Latest revision as of 21:55, January 14, 2017

Publications since 2012

Publications reporting on research supported by this MURI

publications: links to publications resulting from this program.

2017

• Y. Altmann, S. McLaughlin, A. O. Hero, "Robust linear spectral unmixing using outlier detection," IEEE Trans on Computational Imaging, to appear 2017. .pdf.

• K. Greenewald, E. Zelnio, A.O. Hero III, "Kronecker PCA Based Robust SAR STAP," to appear in IEEE Trans on Aerospace and Electronic Systems (AES), 2017. .pdf.

• T.-P. Xie, N. Nasrabadi, and A.O. Hero, “Learning to classify with possible sensor failures," to appear in IEEE Transactions on Signal Processing, 2017. .pdf.

• Y. Yilmaz and Alfred Hero, "Multimodal Event Detection in Twitter Hashtag Networks," to appear in Journ. of Signal Processing Systems, 2017. .pdf.

2016

• A. El Alaoui, X. Cheng, A. Ramdas, M. Wainwright, and M. I. Jordan, "Asymptotic behavior of $\ell_p$-based Laplacian regularization in semi-supervised learning", Proceedings of the Conference on Computational Learning Theory (COLT), New York, NY, June 2016. .pdf.

• Y. Altmann, S. McLaughlin, A.O. Hero, "Robust linear spectral unmixing using outlier detection," IEEE Trans on Computational Imaging, 2016. .pdf.

• V. Berisha, A. Wisler, A.O. Hero, and A. Spanias, "Empirically Estimable Classification Bounds Based on a Nonparametric Divergence Measure" IEEE Transactions on Signal Processing, vol. 64, no. 3, pp.580-591, Feb. 2016. .pdf

• H.-W. Chung, L. Zheng, B. Sadler, A.O. Hero, "Unequal Error Protection Coding Approaches to the Noisy 20 Questions Problem," IEEE Intl Conf. on Information Theory (ISIT), July 2016, Barcelona Spain. .pdf.

• X. Gong, J. Zhang, D. Cochran, and K. Xing, "Optimal placement for barrier coverage in bistatic radar sensor networks, IEEE/ACM Transactions on Networking}, vol. 24, no. 1, pp. 259--271, 2016. .pdf

• K. Greenewald, E. Zelnio, A.O. Hero III, "Kronecker PCA Based Robust SAR STAP," IEEE Trans on Aerospace and Electronic Systems (AES), 2016. .pdf.

• K. Greenewald, E. Zelnio and A.O. Hero, "Kronecker STAP and SAR GMTI," Proceedings of SPIE Symposium on Defense, Sensing and Security April 2016. .pdf.

• N. Halay, K. Todros and A.O. Hero, "Measure transformed quasi-likelihood ratio test for Bayesian binary hypothesis testing," IEEE Workshop on Statistical Signal Processing (SSP), Pamplona Spain, June 2016. .pdf.

• A.O. Hero and B. Rajaratnam, "Foundational principles for large-scale inference: illustrations through correlation mining," Proceedings of the IEEE, vol. 104, no. 1, pp. 93-110, Jan 2016. .pdf.

• J. Lee, M. Simchowitz, B. Recht, and M. I. Jordan, "Gradient descent only converges to minimizers," Proceedings of the Conference on Computational Learning Theory (COLT), New York, NY, June 2016. .pdf.

• L. Li, V. Malave, A. Song, and A. J. Yu, "Extracting human face similarity judgments: Pairs or triplets?," Proceedings of the Thirty-Eighth Annual Conference of the Cognitive Science Society, 2016. .pdf.

• Q. Liu, J.D. Lee, M.I. Jordan, "A kernelized Stein discrepancy for goodness-of-fit tests," In Proceedings of the International Conference on Machine Learning (ICML) Sep 2016. .pdf.

• B. Moore and R. R. Nadakuditi, “Robust pca: Low rank matrix estimation with hard or soft thresholding based outlier rejection, in Proceedings of IEEE GlobalSIP conference, 2016. .html.

• B. Mu, S.-Y. Liu, L. Paull, J. Leonard, and J. P. How, “Slam with objects using a nonparametric pose graph, in Intelligent Robots and Systems (IROS), 2016 IEEE/RSJ International Conference on, Oct 2016. .html.

• B. Mu, L. Paull, A. Akbar Agha-mohammadi, J. How, and J. Leonard, “Two-stage focused inference for resource-constrained minimal collision navigation, IEEE Transactions on Robotics, 2016 (conditionally accepted). .pdf.

• G. E. Newstadt, B. Mu, D. Wei, J. P. How, A. O. Hero III, "Importance-weighted adaptive search for multi-class targets," IEEE Trans on Signal Processing, vol. 63, no. 23, 6299-6314, Dec. 2015. .pdf.

• S. Ravishankar, B. E. Moore, R. R. Nadakuditi, and J. A. Fessler, “Lassi: A low-rank and adaptive sparse signal model for highly accelerated dynamic imaging, in IEEE Image, Video, and Multidimensional Signal Processing Workshop (IVMSP), pp. 1–5, 2016. .pdf.

• S. Ravishankar, R. R. Nadakuditi, and J. A. Fessler, “Efficient learning of dictionaries with low rank atoms, in Proceedings of IEEE GlobalSIP conference, 2016. .pdf.

• S. Ravishankar, R. R. Nadakuditi, and J. A. Fessler, “Sum of outer products dictionary learning for inverse problems, in Proceedings of IEEE GlobalSIP conference, 2016. .pdf.

• S. Soatto, “Visual inertial semantic scene representation, UCLA TR CSD160005, May 20, 2016. .pdf.

• S. Soatto and A. Chiuso, “Visual representations: Defining properties and deep approximations, Proc. of the Intl. Conf. on Learning Representations (ICLR); ArXiv: 1411.7676, May 2016. .pdf.

• N. Sugavanam, S. Baskar, and E. Ertin, “Recovery guarantees for high resolution radar sensing with compressive illumination,”€ Fourth International Conference on Compressive Sensing applied to Radar (COSERA2016), Sep 2016. .pdf.

• N. Sugavanam and E. Ertin, “Recovery guarantees for high resolution radar sensing with compressive illumination,” chapter in Compressive Sensing of Earth Observations,edited by C. Chen, CRC Press, 2016. .pdf.

• D. Teng and E. Ertin, “Wald-kernel: A method for learning sequential detectors,” in Proceedings of IEEE Statistical Signal Processing (SSP2016), June 2016. .pdf.

• D. Wang, J. Fisher III, and Q. Liu, “Efficient observation selection in probabilistic graphical models using bayesian lower bounds, in Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, pp. 755--764. AUAI Press, 2016. .html.

• G. T. Whipps, E. Ertin, and R. L. . Moses, “Constrained fisher scoring for a mixture of factor analyzers,” Army Research Labaratory, Tech. Rep. ARL-TR-7836, 2016.

• T.-P. Xie, N. Nasrabadi, A.O. Hero, "Learning to classify with possible sensor failures," IEEE Transactions on Signal Processing, 2016. .pdf.

• Y. Yilmaz and A.O. Hero, "Multimodal Event Detection in Twitter Hashtag Networks," Journ. of Signal Processing Systems, 2016. .pdf.

2015

• T. Abdelrahman and E. Ertin, "Mixture of factor analyzers models of appearance manifolds for resolved SAR targets,’’ in Proceedings of SPIE 9475, Algorithms for Synthetic Aperture Radar Imagery XXII, May 2015. .pdf

• S. Ahmad and A. J. Yu, "A rational model for individual differences in preference choice," Proceedings of the Thirty-Seventh Annual Meeting of the Cognitive Science Society .pdf

• Y. Altmann, S. McLaughlin, A.O. Hero, "Robust linear spectral unmixing using outlier detection," IEEE Intl Conf on Acoustics, Speech, and Signal Processing (ICASSP), Brisbane, April 2015. .pdf

• S. Baskar and E. Ertin, "A software defined radar platform for waveform adaptive MIMO radar research’’ IEEE Radar Conference (RadarCon), pp.1590--1594, May 2015. .pdf

• K. Beaudet and D. Cochran, "Estimation of subspace occupancy," Proceedings of the Asilomar Conference on Signals, Systems, and Computers, pp. 1599—1603, November 2014, .pdf

• V. Berisha and A. O. Hero, "Empirical non-parametric estimation of the Fisher Information," IEEE Signal Processing Letters, vol. 22, no. 7, pp. 988-992, 2015. .pdf

• Visar Berisha, Alan Wisler, Alfred O. Hero, and Andreas Spanias, "Empirically Estimable Classification Bounds Based on a New Divergence Measure," January 2015. .pdf

• P-Y Chen and A. O. Hero, "Phase transitions in spectral community detection of large noisy networks," IEEE Intl Conf on Acoustics, Speech, and Signal Processing (ICASSP), Brisbane, April 2015. .pdf

• H.-W. Chung, B. M. Sadler, and A. O. Hero, "Bounds on variance for symmetric unimodal distributions," Allerton Conference, Oct. 2015. .pdf

• J. Dong, N. Karianakis, D. Davis, J. Hernandez, J. Balzer and S. Soatto, "Multi-view feature engineering and learning", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015. .pdf

• J. Dong and S. Soatto, "Domain-size pooling in local descriptors: DSP-SIFT", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015. .pdf

• J. C. Duchi, M. I. Jordan, M. J. Wainwright, and A. Wibisono, "Optimal rates for zero-order optimization: the power of two function evaluations," "IEEE Transactions on Information Theory", to appear. .pdf

• B. Farrell and R. Nadakuditi, " Local spectrum of truncations of Kronecker products of Haar distributed unitary matrices", Random Matrices: Theory and Applications, vol. 4, no. 1, 1550001, 2015. [1]

• O. Freifeld, K. Batmanghelich, J. W. Fisher, et al., “Highly-expressive spaces of well-behaved transformations: Keeping it simple, in IEEE International Conference on Computer Vision (ICCV), pp. 2911--2919. 2015. .pdf.

• G. Georgiadis, A. Chiuso and S. Soatto, "Texture representations for image and video texture synthesis", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015. .pdf

• S. Gogineni, P. Setlur, R. Nadakuditi and M. Rangaswamy, "Random matrix theory inspired passive bistatic radar detection with noisy reference signal," Proceedings of IEEE ICASSP, pp. 2754-2758, 2015. [2].pdf

• S. Gogineni, P. Setlur, R. Nadakuditi and M. Rangaswamy, "Random matrix theory inspired passive bistatic radar detection of low-rank signals," Proceedings of IEEE Radar Conference, pp. 1656-1659, 2015. [3] .pdf

• M. Graham, J. How, and D. Gustafson, “Robust incremental {SLAM} with consistency-checking, in Intelligent Robots and Systems (IROS), IEEE/RSJ International Conference on, pp. 117--124, Sept 2015. .html.

• K. Greenewald, E. Zelnio, A.O. Hero III, "Kronecker PCA Based Robust SAR STAP," submitted Jan 2015. .pdf

• A.O. Hero, "Sparsity regularized image reconstruction," in Review of Progress in Quantitative Nondestructive Evaluation, Vol. 34, edited by Dale E. Chimenti and L. J. Bond, published by American Institute of Physics, Melville, NY, 2015. .pdf

• A.O. Hero and B. Rajaratnam, "Foundational principles for large scale inference: Illustrations through correlation mining," IEEE Proceedings. In press 2015. .pdf. Also available as Stanford University Dept of Statistics Technical Report 2015-13 May 2015 .html.

• S. D. Howard, D. Cochran, and W. Moran, "Gauge-invariant registration in networks," Proceedings of the International Conference on Information Fusion, July 2015. .pdf

• K.J. Hsiao, J. Calder, A.O. Hero, "Multi-criteria Anomaly Detection using Pareto Depth Analysis," IEEE Journ on Neural Network Learning Systems, no. 6, vol. 27, pp. 1307-1321, Aug. 2015. .pdf.

• K.J. Hsiao, J. Calder and A.O. Hero, "Pareto-depth for Multiple-query Image Retrieval," IEEE Trans on Image Processing, vol. 24, no. 2, pp. 583-594, 2015. .pdf

• Q. Liu, J. W. Fisher III, and A. T. Ihler, “Probabilistic variational bounds for graphical models, in Advances in Neural Information Processing Systems, pp. 1432--1440, 2015. .pdf.

• Q. Liu, A. Ihler, J. W. Fisher III, "Boosting Crowdsourcing With Expert Labels: Local vs. Global Effects", International Conference on Information Fusion (Fusion), 2015. [4]

• G. Marjanovic, M. Ulfarsson, A.O. Hero, "MIST: L0 sparse linear regression with momentum," IEEE Intl Conf on Acoustics, Speech, and Signal Processing (ICASSP), Brisbane, April 2015. .pdf

• B. Mu, G. Newstadt, D. Wei, A.O. Hero, J.P. How, "Adaptive Search for Multi-class Targets with Heterogeneous Importance," Fusion 2015. .pdf

• H. Nayar and R. Nadakuditi, "OptFuse:Low-rank factor estimation by optimal data-driven linear fusion of multiple signal-plus-noise matrices," Proceedings of the 2015 Fusion Conference, [5]

• H. Nayar and R. Nadakuditi, "Theoretical performance analysis of Tucker Higher Order SVD in extracting structure from multiple signal-plus-noise matrices," Proceedings of the IEEE Asilomar Conference on Signals & Systems, pp. 755-759, 2015. [6] .pdf

• Gregory E. Newstadt, Beipeng Mu, Dennis Wei, Jonathan P. How, Alfred O. Hero III, "Importance-weighted adaptive search for multi-class targets," IEEE Trans on Signal Processing, vol. 63, no. 23, 6299-6314, Dec. 2015. .pdf.

• G. Newstadt, D. Wei, A.O. Hero, "Adaptive Search and Tracking of Sparse Dynamic Targets under Resource Constraints," to appear in IEEE Trans. Signal Processing 2015. .pdf

• R. Nishihara, L. Lessard, B. Recht, A. Packard and M. I. Jordan, "A general analysis of the convergence of ADMM," International Conference on Machine Learning, to appear. .pdf

• S. Olver, R. Nadakuditi and T. Trogdon, "Sampling unitary ensembles," Random Matrices: Theory and Applications, vol. 4, no. 1, 1550002, 2015. [7]

• G. Papachristoudis, J. W. Fisher III, "On the Complexity of Information Planning in Gaussian Models", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2015. [8]

• G. Papachristoudis, J. W. Fisher III, "Efficient Information Planning in Gaussian MRFs", International Conference on Information Fusion (Fusion), 2015. [9]

• G. Papachristoudis, J. W. Fisher III, "Adaptive Belief Propagation", In International Conference on Machine Learning (ICML), 2015. [10]

• S. Soatto and A. Chiuso, "Visual Scene Representations: sufficiency, minimality, invariance and deep approximation", International Conference on Learning Representations, 2015. .pdf

• J. Straub, J. Chang, O. Freifeld, J. W. Fisher III, "A Dirichlet Process Mixture Model for Spherical Data", International Conference on Artificial Intelligence and Statistics (AISTATS), 2015. [11]

• J. Straub, T. Campbell, J. P. How, J. W. Fisher III, "Small-Variance Nonparametric Clustering on the Hypersphere", In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. [12]

• R. T. Suryaprakash and R. Nadakuditi, "Consistency and MSE Performance of MUSIC-based DOA of a Single Source in White Noise with Randomly Missing Data," IEEE Transactions on Signal Processing, vol. 63, no. 18, pp. 4756-4770, September 2015. [13] .pdf

• N. Sugavanam and E. Ertin, "Recovery guarantees for multifrequency chirp waveforms in compressed radar sensing,’’ submitted Jul 2015 .pdf

• R. T. Suryaprakash, B. Moore and R. Nadakuditi,"Algorithms and performance analysis for estimation of low-rank matrices with Kronecker structured singular vectors," Proceedings of IEEE ICASSP, pp. 3776 - 3780, 2015. [14] .pdf

• D. Teng and E. Ertin, "Learning to Aggregate Information for Sequential Inferences,’’ submitted May 2015. .pdf

• T. Tsiligkaridis, B. M. Sadler and A. O. Hero III, "On decentralized estimation with active queries," IEEE Trans on Signal Processing. In press 2015. .pdf

• D. Wei and A.O. Hero, "Performance Guarantees for Adaptive Estimation of Sparse Signals," IEEE Trans. on Information Theory, vol. 61, no. 4, pp. 2043-2059, 2015. .pdf

• G. T. Whipps, E. Ertin and R. L. Moses, "Distributed sensing for Quickest Change Detection of Point Radiation Sources,’’ International Conference on Information Fusion (FUSION), July 2015. .pdf

• 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, Vol 63, No 1, 2015. .pdf

• T. Xie, N. Nasrabadi, A.O. Hero, "Multi-sensor classification via consensus-based multi-view maximum entropy discrimination," IEEE Intl Conf on Acoustics, Speech, and Signal Processing (ICASSP), Brisbane, April 2015. .pdf

• Y. Yilmaz and A. O. Hero, "Multimodal factor analysis," Proc. of IEEE Workshop on Machine Learning and Signal Processing, Boston, 2015. .pdf.

• Y. Zhang, M. J. Wainwright, and M. I. Jordan, "Distributed estimation of generalized matrix rank: Efficient algorithms and lower bounds," International Conference on Machine Learning, to appear. .pdf

• Y. Zhang, X. Chen, D. Zhou, and M. I. Jordan, "Spectral methods meet EM: A provably optimal algorithm for crowdsourcing," Advances in Neural Information Processing Systems, 2015. .pdf

2014

• S. Ahmad, and A. J. Yu, "A socially aware Bayesian model for competitive foraging", Proceedings of the Cognitive Science Society Conference, 2014. " .pdf

• 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. .pdf

• J. Balzer, D. Acevedo-Feliz, S. Soatto, S. Hofer, M. Hadwiger and J. Beyerer, "Cavlectometry: Towards holistic reconstruction of large mirror objects", The International Conference on 3D Vision, 2014. .pdf

• 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. .pdf

• 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. .pdf

• 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. .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. .pdf

• J. C. Duchi, M. I. Jordan, M. J. Wainwright, and Y. Zhang, "Information-theoretic lower bounds for distributed statistical estimation with communication constraints," .pdf

• 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. .pdf

• 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 .pdf

• E. Ertin, "Information geometry of radar targets," Information Theory and Applications Workshop, San Diego, 2014.

• B. W. Hong and S. Soatto, "Shape Matching using Multiscale Integral Invariants," IEEE Transactions on Pattern Recognition and Machine Intelligence, July 2014. .pdf

• 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).

• S. D. Howard, D. Cochran, W. Moran, and F. Cohen, "Estimation and registration on graphs," IEEE Transactions on Signal Processing (in review). .pdf

• 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. pdf

• F. Lindsten, M. I. Jordan, and T. Schoen, "Particle Gibbs with ancestral sampling," Journal of Machine Learning Research, vol. 15, pp. 2145 - 2184, 2014. .pdf

• 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. .pdf

• 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. .pdf

• 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. .pdf

• Z. Meng, D. Wei, A. Wiesel, and A.O. Hero, "Distributed Learning of Gaussian Graphical Models via Marginal Likelihoods," IEEE Transactions on Signal Processing, vol 62, no 20, pp. 5425-5438. 2014. .pdf

• 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. .pdf

• 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. .pdf

• B. Mu and J. P. How, "Learning Sparse Gaussian Graphical Model with l0-regularization," Advances in Neural Information Processing Systems 27 (in review). .html

• 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. .pdf

• 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). .pdf

• 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 review).

• G. Papachristoudis and J. W. Fisher III, "Efficient information planning in Markov chains" (in review). .pdf

• G. Papachristoudis and J. W. Fisher III, "Incremental belief propagation in Markov random trees" (in review). .pdf

• D. Teng and E. Ertin, "Optimal quantization of likelihood for sequential detection," (in review) .pdf.

• 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. .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 review) .pdf

• D. Wei and A. O. Hero, "Multistage adaptive estimation of sparse signals," IEEE Journal of Selected Topics in Signal Processing (in press). .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 (to appear) September 2014. .pdf

• 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) .pdf.

• 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. .pdf

• 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. .pdf

• 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. .pdf

2013

• S. Ahmad, H. Huang and A. J. Yu, "Context-sensitivity in human active sensing," Advances in Neural Information Processing Systems, 26. MIT Press, Cambridge, MA, 2013. .pdf

• K. Beaudet and D. Cochran, "Multiple-channel detection in active sensing," Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, June 2013. .pdf

• K. Beaudet, L. Crider, and D. Cochran, "Detection in networked radar," Proc. SPIE 8746, Algorithms for Synthetic Aperture Radar Imagery XX, May 2013. .pdf

• V. Chandrasekaran and M. I. Jordan, "Computational and statistical tradeoffs via convex relaxation," Proceedings of the National Academy of Sciences, 2013. .pdf

• D. Cochran and A. O. Hero, "Information-driven sensor planning: Navigating a statistical manifold," Proceedings of the IEEE Global Conference on Signal and Information Processing, pp. 1049-1052, December 2013. .pdf

• J. Duchi, L. Mackey, and M. I. Jordan, "The asymptotics of ranking algorithms," Annals of Statistics 41(5):2292-2323, 2013. .pdf

• J. Duchi, M. I. Jordan, and M. Wainwright, "Privacy aware learning," Proceedings of NIPS, December 2013. .pdf

• J. Duchi, M. I. Jordan and M. Wainwright, "Local privacy and statistical minimax rates", 54th Annual Symposium on Foundations of Computer Science (FOCS), October 2013. .pdf

• 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.

• E. Ertin, "Manifold learning methods for wide-angle SAR ATR," Proceedings of the 2013 International Conference on Radar, pp. 500-504, September 2013. .pdf

• B. Farrell and R. Nadakuditi,"Local spectrum of truncations of Kronecker products of Haar distributed unitary matrices" (preprint) .pdf

• J. Gao, E. Ertin, S. Kumar, and M. al'Absi, "Contactless sensing of physiological signals using wideband RF probes," Proceedings of the 46th Asilomar Conference on Signals, Systems, and Computers, pp. 86-90, November 2013 .pdf

• K. Greenwald, T. Tsiligkaridis and A. O. Hero III, "Kronecker Sum Decompositions of Space-Time Data," Proceedings of IEEE Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), pp. 65-68, 2013. .pdf

• M. I. Jordan, "On statistics, computation, and scalability," Bernoulli, 19, 1378-1390, (2013). .pdf

• A. Kleiner, A. Talwalkar, S. Agarwal, M. I. Jordan, and I. Stoica, "A general bootstrap performance diagnostic," Proceedings of the 19th ACM Conference on Knowledge Discovery and Data Mining (SIGKKD), Chicago 2013. .pdf

• A. Kleiner, A. Talwalkar, P. Sarkar, and M. I. Jordan, "A scalable bootstrap for massive data," Journal of the Royal Society, Series B (in press). .pdf

• F. Lindsten, M. I. Jordan, T. Schoen, "Bayesian semiparametric Wiener system identification", Automatica, 2013, 49, 2053-2063.

• Z. Meng, D. Wei, A. Wiesel, and A. Hero III, "Distributed learning of Gaussian graphical models via marginal likelihoods," Proceedings of AISTATS, 2013. (Received Notable Paper Award) .pdf

• Z. Meng, D. Wei, A, Wiesel A. O. Hero III, "Marginal Likelihoods for Distributed Estimation of Graphical Model Parameters," Proceedings of IEEE CAMSAP, pp. 73-76, March 2013. (Received Best Student Paper Award) .pdf

• Z. Meng, D.Wei, A. Wiesel, and A. O. Hero III, "Marginal likelihoods for distributed parameter estimation of Gaussian graphical models," to appear in IEEE Trans on Signal Processing. ArXiv e-prints, March 2013. .pdf

• B. Moran, S. Howard, and D. Cochran, "Positive-operator-valued measures: A general Setting for frames," in Excursions in Harmonic Analysis, T. Andrews, R. Balan, W. Czaja, K. Okoudjou, and J. Benedetto, eds., vol. 2, pp. 49—64, Springer 2013. .pdf

• B. Mu, G. Chowdhary, and J. P. How, "Efficient distributed inference using adaptive censoring algorithms," Automatica (provisionally accepted).

• B. Mu, G. Chowdhary, and J. P. How, "Efficient distributed information fusion using adaptive decentralized censoring algorithms," Proceedings of the American Control Conference (ACC), Washington DC, July 2013.

• B. Mu, G. Chowdhary, and J. P. How, "Value-of-information aware active task assignment," Proceedings of the AIAA Guidance, Navigation, and Control Conference, Boston, August 2013.

• B. Mu, G. Chowdhary, and J. P. How, "Value-of-information aware active task assignment," Proceedings of SPIE Defense, Security, and Sensing Symposium, Baltimore 2013.

• R. Nadakuditi, "OptShrink: An algorithm for improved low-rank signal matrix denoising by optimal, data-driven singular value shrinkage," IEEE Transactions on Information Theory, Accepted for publication .pdf

• R. Nadakuditi, "When are the most informative components for inference also the principal components," .pdf

• R. Nadakuditi and M. Newman, "Spectra of random graphs with arbitrary expected degrees," Phys. Rev. E 87, 012803 (2013), .pdf

• G. Papachristoudis and J. W. Fisher III, "Efficient information planning in Markov chains," (submitted for publication).

• G. Papachristoudis and J. W. Fisher III, "Incremental belief propagation," (submitted for publication).

• M. R. Riedl, L. C. Potter, and E. Ertin, "Augmenting synthetic aperture radar with space time adaptive processing," Proceedings of SPIE, vol. 8746, Baltimore, May 2013...pdf

• P. Shearer, A. Gilbert and A. O. Hero, "Correcting camera shake by incremental sparse approximation," Proceedings of IEEE ICIP 2013. (Best Paper Award) .pdf

• N. Sugavanam and E. Ertin, "Sensor selection and placement in adversarial environments," Proceedings of the IEEE Global Conference on Signal and Information Processing, pp. 185-188, December 2013. .pdf

• S. Suvorova, B. Moran, S. D. Howard, and D. Cochran, "Control of sensing by navigation on information gradients,” Proceedings of the IEEE Global Conference on Signal and Information Processing, pp. 197—200, December 2013. .pdf

• D. Teng and E. Ertin, "Optimal quantization of likelihood for low complexity sequential testing," Proceedings of the IEEE Global Conference on Signal and Information Processing, pp. 675-678, December 2013. .pdf

• T. Tsiligkaridis, B. Sadler, A.O. Hero, "Blind Collaborative 20 Questions for Target Localization," Proceedings of the IEEE Global Conference on Signal and Information Processing, pp. 161-164. .pdf

• T. Tsiligkaridis and A. O. Hero III, "Covariance estimation in high dimensions via Kronecker product expansions," IEEE Transactions on Signal Processing, vol. 61, no. 21, pp. 5347 - 5360, Nov 2013. .pdf

• T. Tsiligkaridis and A. Hero, "Low separation rank covariance estimation using Kronecker product expansions," Proceedings of the IEEE International Symposium on Information Theory (ISIT), Istanbul, 2013. .pdf

• T. Tsiligkaridis and A. Hero, and S. Zhou, "On convergence of Kronecker graphical lasso algorithms," IEEE Transactions on Signal Processing, vol. 61, no. 9, pp. 1743--1755, 2013. .html

• T. Tsiligkaridis, B. Sadler, and A. Hero, "A collaborative 20 questions model for target search with human-machine interaction," Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, June 2013. .pdf

• T. Tsiligkaridis, B. M. Sadler and A. O. Hero III, "On decentralized estimation with active queries" (preprint) .pdf

• F. Wauthier, M. I. Jordan and N. Jojic, "Efficient ranking from pairwise comparisons", International Conference on Machine Learning (ICML), 2013. .pdf

• D. Wei and A.O. Hero, "Multistage Adaptive Estimation of Sparse Signals," IEEE Journal of Selected Topics in Signal Processing, vol. 7, no. 5, pp. 783-796, October 2013. .pdf

• D. Wei and A.O. Hero, "A Performance Guarantee for Adaptive Estimation of Sparse Signals," Proceedings of IEEE GlobalSIP 2013, pp. 189-192, December 2013. .pdf

• D. Wei and A. O. Hero, "Adaptive spectrum sensing and estimation," Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) May 2013. .pdf

• G. Whipps, E. Ertin and R. Moses, "Distributed detection with collisions in a random, single-hop wireless sensor network," Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, June 2013. .pdf

• Y. Zeng, C. Wang, S. Soatto, and S.-T. Yau, "Nonlinearly constrained MRFs: Exploring the intrinsic dimensions of higher-order cliques," Proc. IEEE International Conference on Computer Vision and Pattern Recognition, June 2013. .pdf

• S. Zhang and A. J. Yu. "Forgetful Bayes and myopic planning: Human learning and decision-making in a bandit setting," Advances in Neural Information Processing Systems, 26. MIT Press, Cambridge, MA, 2013. .pdf

2012

• D. Cochran, S. D. Howard, and B. Moran, "Operator-theoretic modeling and waveform design for radar in the presence of Doppler," in Proceedings of IEEE-AESS RadarCon, pp. 774-777, May 2012. .pdf

• D. Cochran, S.D. Howard, B. Moran, and H.A. Schmitt, “Maximum-entropy Surrogation in Network Signal Detection,” Proceedings of the IEEE Statistical Signal Processing Workshop, August 2012. .pdf

• J.C. Duchi, L. Mackey, and M.I. Jordan, "The asymptotics of ranking algorithms," Apr. 2012. .pdf

• E. Ertin, "Sensor selection in adversarial setting," Proceedings of the IEEE Statistical Signal Processing Workshop, August 2012. .pdf

• G. Georgiadis, A. Ayvaci, and S. Soatto, "Actionable saliency detection," in Proc. of the IEEE Intl. Conf. on Comp. Vis. and Patt. Recog., 2012. .pdf

• V. Karasev, A. Chiuso, and S. Soatto, "Controlled recognition bounds for visual learning and exploration," Proceedings of NIPS, December 2012..pdf

• A. Kleiner, A. Talwalkar, P. Sarkar, M. Jordan, "The Big Data Bootstrap," Proceedings of the 29th International Conference on Machine Learning, Edinburgh, UK, 2012. .pdf

• Z. Meng, A. Wiesel, and A. O. Hero, "Distributed principal component analysis on networks via directed graphical models," IEEE ICASSP 2012. Author preprint .pdf

• T. Moldovan, P. Abbeel, "Safe Exploration in Markov Decision Processes," Proceedings of the 29th International Conference on Machine Learning, Edinburgh, UK, 2012. .pdf

• B. Moran, S. D. Howard, and D. Cochran, ``An information-geometric approach to sensor scheduling” (Invited paper), Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, April 2012. .pdf

• W. Moran, S. D. Howard, D. Cochran, and S. Suvorova, "Sensor Management via Riemannian Geometry," Proceedings of the Fiftieth Annual Asilomar Conference on Communication, Control and Computing,, October 2012. .pdf

• B. Mu, G. Chowdhary, and J. P. How, "Efficient distributed information fusion using value of information based censoring," Aerospace control laboratory technical report, Massachusetts Institute of Technology, July 2012. .html.

• S. Olver and R. Nadakuditi, "Numerical computation of convolutions in free probability theory," Arxiv preprint arXiv:1203.1958, 2012. [15]

• G. Papachristoudis and J. W. Fisher III, "Theoretical guarantees on penalized information gathering," Proceedings of the IEEE Statistical Signal Processing Workshop, August 2012. .pdf

• A. Ravichandran and S. Soatto, "Modeling stationarity at multiple time-scales for applications in fire detection and traffic monitoring," Proc. of the Eur. Conf. on Comp. Vision, 2012. .pdf

• A. Ravichandran and C. Wang and S. Soatto, "SuperFloxels: A Mid-Level Representation for Video Sequences," Proc. of ARTEMIS, October 2012. .pdf

• C. Rossler, E. Ertin, and R. L. Moses, "Waveform diversity and optimal change detection," Proceedings of the 46th Asilomar Conference on Signals, Sysyems, and Computers, November 2012.

• T. Tsiligkardis and A.O. Hero, "Sparse covariance estimation under Kronecker product structure," Proc. IEEE ICASSP, March 2012. .pdf

• T. Tsiligkardis, A.O. Hero, and S. Zhou, "Convergence properties of Kronecker graphical lasso algorithms," Proceedings of the IEEE Statistical Signal Processing Workshop, Ann Arbor MI, August 2012..pdf

• L. Valente, R. Tsai, and S. Soatto, "Information gathering control via exploratory path planning," Proc. of the Conf. on Information Sciences and Systems (CISS), March 2012. .pdf

• F. L. Wauthier and M. I. Jordan, "Bayesian bias mitigation for crowdsourcing," In P. Bartlett, F. Pereira, J. Shawe-Taylor and R. Zemel (Eds.), Advances in Neural Information Processing Systems (NIPS) 24, 2012..pdf

• D. Wei and A. Hero, "Multistage adaptive estimation of sparse signals," in Proceedings of the IEEE Statistical Signal Processing Workshop, Ann Arbor MI, August 2012. .pdf

• G. T. Whipps, E. Ertin, and R. L. Moses, “Threshold considerations in distributed detection in a network of sensors,” in Proceedings of SPIE Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR III, volume 8389, Baltimore, MD, May 2012. .pdf

• Z. Yi and S. Soatto, "Information Forests," Proc. ITA, Information Theory and Applications, Feb. 2012. Technical Report UCLA CSD 120002. .pdf

• Z. Zhang, S. Wang, D. Liu and M. I. Jordan, "EP-GIG priors and applications in Bayesian sparse learning," Journal of Machine Learning Research, 13, 2031-2061, 2012. .pdf