Publications

Selected Publications from Machine Learning Faculty. For more detailed information, please visit specific faculty Google Scholar sites.

2017

Gutierrez-Barragan F, Ithapu VK, Hinrichs C, Maumet C, Johnson SC, Nichols TE, Singh VV, the ADNI. Accelerating Permutation Testing in Voxel-wise Analysis through Subspace Tracking: A new plugin for SnPM. Vol. stat.AP, arXiv.org. 2017.

Ithapu VK, Ravi SN, Singh V. On architectural choices in deep learning: From network structure to gradient convergence and parameter estimation. Vol. cs.LG, arXiv.org. 2017.

Jog V, Loh P-L. Analysis of Centrality in Sublinear Preferential Attachment Trees via the Crump-Mode-Jagers Branching Process. IEEE Transactions on Network Science and Engineering. 2017;4(1):1–12.

Wang S, Guo W, Huang T-Z, Raskutti G. Image inpainting using reproducing kernel Hilbert space and Heaviside functions. Journal of Computational and Applied Mathematics. 2017 Feb;311:551–64.

Xia D, Yuan M. On Polynomial Time Methods for Exact Low Rank Tensor Completion. Vol. stat.ML, arXiv.org. 2017.

Zhang A, Xia D. Guaranteed Tensor PCA with Optimality in Statistics and Computation. Vol. math.ST, arXiv.org. 2017.

2016

Bernstein MN, Doan A, Dewey CN. MetaSRA: normalized sample-specific metadata for the Sequence Read Archive. 2016.

Bhargava A, Ganti R, Nowak R. Bandit Approaches to Preference Learning Problems with Multiple Populations. arXiv preprint arXiv:160304118. 2016.

Burnside ES, Liu J, Wu Y, Onitilo AA, McCarty CA, Page CD, et al. Comparing Mammography Abnormality Features to Genetic Variants in the Prediction of Breast Cancer in Women Recommended for Breast Biopsy. Acad Radiol. 2016 Jan;23(1):62–9.

Cai TT, Zhang A. Minimax Rate-optimal Estimation of High-dimensional Covariance Matrices with Incomplete Data. Vol. stat.ME, arXiv.org. 2016.

Cai TT, Zhang A. Rate-Optimal Perturbation Bounds for Singular Subspaces with Applications to High-Dimensional Statistics. Vol. math.ST, arXiv.org. 2016.

Ellenberg J, Pierce LB, Wood MM. On $ ell $-torsion in class groups of number fields. arXiv preprint arXiv:160606103. 2016.

Ellenberg JS, Gijswijt D. On large subsets of F\q^ n with no three-term arithmetic progression. arXiv preprint arXiv:160509223. 2016.

Figueiredo MA, Nowak RD. Ordered Weighted l1 Regularized Regression with Strongly Correlated Covariates: Theoretical Aspects (Supplementary Material). 2016.

Figueiredo MA, Nowak RD. Ordered Weighted l1 Regularized Regression with Strongly Correlated Covariates: Theoretical Aspects. 2016. pp. 930–8.

Gitter A, Bar-Joseph Z. The SDREM Method for Reconstructing Signaling and Regulatory Response Networks: Applications for Studying Disease Progression. In: Comparative Genomics. New York, NY: Springer New York; 2016. pp. 493–506. (Methods in Molecular Biology; vol. 1303).

Gitter A, Huang F, Valluvan R, Fraenkel E, Anandkumar A. Unsupervised learning of transcriptional regulatory networks via latent tree graphical models. Vol. q-bio.MN, arXiv.org. 2016.

Hall EC, Raskutti G, Willett R. Inferring high-dimensional poisson autoregressive models. IEEE; 2016. pp. 1–5.

Hua R, Roy S. Organocatalytic Transformation of Carbon Dioxide. In: Recent Advances in Organocatalysis. InTech; 2016.

Jacobs RM, Booske JH, Morgan D. Intrinsic defects and conduction characteristics of Sc2O3 in thermionic cathode systems. Vol. cond-mat.mtrl-sci, arXiv.org. American Physical Society; 2016. p. 054106.

Jain L, Jamieson K, Nowak R. Finite Sample Prediction and Recovery Bounds for Ordinal Embedding. arXiv preprint arXiv:160607081. 2016.

Jun K-S, Jamieson K, Nowak R, Zhu X. Top Arm Identification in Multi-Armed Bandits with Batch Arm Pulls. The 19th International Conference on Artificial Intelligence and Statistics (AISTATS). 2016.

Jun K-S, Orabona F, Willett R, Wright S. Improved Strongly Adaptive Online Learning using Coin Betting. Vol. stat.ML, arXiv.org. 2016.

Knaack SA, Thompson DA, Roy S. Reconstruction and Analysis of the Evolution of Modular Transcriptional Regulatory Programs Using Arboretum. Methods Mol Biol. New York, NY: Springer New York; 2016;1361(Chapter 21):375–89.

Lee C-P, Wright SJ. Random Permutations Fix a Worst Case for Cyclic Coordinate Descent. Vol. math.OC, arXiv.org. 2016.

Lee K, Lam M, Pedarsani R, Papailiopoulos D, Ramchandran K. Speeding up distributed machine learning using codes. IEEE; 2016. pp. 1143–7.

 

Marais W, Holz R, Hu YH, Willett R. Atmospheric lidar imaging and poisson inverse problems. IEEE; 2016. pp. 983–7.

Marais WJ, Holz RE, Hu YH, Kuehn RE, Eloranta EE, Willett RM. A New Approach To Inverting Backscatter and Scatter from Photon-Limited Lidar Observations. arXiv preprint arXiv:160302075. 2016.

Meek C, Simard P, Zhu X. Analysis of a Design Pattern for Teaching with Features and Labels. Vol. cs.AI, arXiv.org. 2016.

Mueller JL, Gallagher JE, Chitalia R, Krieger M, Erkanli A, Willett RM, et al. Rapid staining and imaging of subnuclear features to differentiate between malignant and benign breast tissues at a point-of-care setting. Journal of cancer research and clinical oncology. Springer; 2016;:1–12.

Niu Z, Chasman D, Eisfeld AJ, Kawaoka Y, Roy S. Multi-task Consensus Clustering of Genome-wide Transcriptomes from Related Biological Conditions. Bioinformatics. 2016 Jan 21;32(10):1509–17.

Peherstorfer B, Cui T, Marzouk Y, Willcox K. Multifidelity importance sampling. Computer Methods in Applied Mechanics and Engineering. 2016 Mar;300:490–509.

Peherstorfer B, Willcox K. Data-driven operator inference for nonintrusive projection-based model reduction. Computer Methods in Applied Mechanics and Engineering. 2016 Jul;306:196–215.

Rao N, Ganti R, Balzano L, Willett R, Nowak R. On Learning High Dimensional Structured Single Index Models. arXiv preprint arXiv:160303980. 2016.

Rao N, Nowak R, Cox C, Rogers T. Classification With the Sparse Group Lasso. Signal Processing, IEEE Transactions on. IEEE; 2016 Jan 1;64(2):448–63.

Rawat AS, Papailiopoulos DS, Dimakis AG, Vishwanath S. Locality and Availability in Distributed Storage. Information Theory, IEEE Transactions on. 2016;62(8):4481–93.

Shi P, Zhang A, Li H. Regression Analysis for Microbiome Compositional Data. Vol. stat.AP, arXiv.org. 2016.

Siahpirani AF, Roy S. A prior-based integrative framework for functional transcriptional regulatory network inference. Nucleic Acids Res. 2016 Nov 28;45(4):2221–1.

Singh VV, Hemachandra N. Blackwell-Nash Equilibrium for Discrete and Continuous Time Stochastic Games. Vol. math.OC, arXiv.org. 2016.

Tamo I, Papailiopoulos DS, Dimakis AG. Optimal Locally Repairable Codes and Connections to Matroid Theory. Information Theory, IEEE Transactions on. 2016;62(12):6661–71.

Tuncbag N, Gosline SJC, Kedaigle A, Soltis AR, Gitter A, Fraenkel E. Network-Based Interpretation of Diverse High-Throughput Datasets through the Omics Integrator Software Package. Prlic A, editor. PLoS Comput Biol. Public Library of Science; 2016 Apr 20;12(4):e1004879.

Viswanathan D, Soni A, Shavlik J, Natarajan S. Learning Relational Dependency Networks for Relation Extraction. Vol. cs.AI, arXiv.org. 2016.

Wang S, Yuan M. Combined Hypothesis Testing on Graphs with Applications to Gene Set Enrichment Analysis. Vol. stat.ME, arXiv.org. 2016.

Zhang A, Brown LD, Cai TT. Semi-supervised Inference: General Theory and Estimation of Means. Vol. stat.ME, arXiv.org. 2016.

Zhang A. Cross: Efficient Low-rank Tensor Completion. Vol. stat.ME, arXiv.org. 2016.

2015

Berthet, Quentin, and Jordan S Ellenberg. 2015. “Detection of Planted Solutions for Flat Satisfiability Problems.” arXiv.org.

Cho, Juhee, Donggyu Kim, and Karl Rohe. 2015. “Asymptotic Theory for Estimating the Singular Vectors and Values of a Partially-Observed Low Rank Matrix with Noise.” arXiv.org.

Dasarathy, Gautam, Robert Nowak, and Xiaojin Zhu. 2015. “S2: an Efficient Graph Based Active Learning Algorithm with Application to Nonparametric Classification.” arXiv.org.

Dittenhafer-Reed, Kristin E, Alicia L Richards, Jing Fan, Michael J Smallegan, Alireza Fotuhi Siahpirani, Zachary A Kemmerer, Tomas A Prolla, Sushmita Roy, Joshua J Coon, and John M Denu. 2015. “SIRT3 Mediates Multi-Tissue Coupling for Metabolic Fuel Switching.” Cell Metabolism 21 (4): 637–46. doi:10.1016/j.cmet.2015.03.007.

Hwa Kim, Won, Barbara B Bendlin, Moo K Chung, Sterling C Johnson, and Vikas Singh. 2015. “Statistical Inference Models for Image Datasets with Systematic Variations,” 4795–4803.

Kim, Won Hwa, Nagesh Adluru, Moo K Chung, Ozioma C Okonkwo, Sterling C Johnson, Barbara B Bendlin, and Vikas Singh. 2015. “A Framework for Performing Multi-Resolution Statistical Analysis of Brain Connectivity Graphs for Preclinical Alzheimer’s Disease.” Alzheimer“S & Dementia: the Journal of the Alzheimer”S Association 11 (7). Elsevier: P882. doi:10.1016/j.jalz.2015.08.089.

Hwa Kim, Won, Sathya N Ravi, Sterling C Johnson, Ozioma C Okonkwo, and Vikas Singh. 2015. “On Statistical Analysis of Neuroimages with Imperfect Registration,” 666–74.

Kim, H, J Xu, B Vemuri, and V Singh. 2015. “Manifold-Valued Dirichlet Processes.” In.

Kim, Hyunwoo, Adluru, Nagesh, Banerjee, Monami, Vemuri, Baba C., and Singh, Vikas, Interpolation on the manifold of k component Gaussian Mixture Models (GMMs)Proceedings of International Conference on Computer Vision (ICCV) , December 2015

Ithapu, Vamsi K, Vikas Singh, Ozioma C Okonkwo, Richard J Chappell, N Maritza Dowling, and Sterling C Johnson. 2015. “Imaging-Based Enrichment Criteria Using Deep Learning Algorithms for Efficient Clinical Trials in Mild Cognitive Impairment.” Alzheimer’s & Dementia 11 (12): 1489–99. doi:10.1016/j.jalz.2015.01.010.

Jae Hwang, Seong, Maxwell D Collins, Sathya N Ravi, Vamsi K Ithapu, Nagesh Adluru, Sterling C Johnson, and Vikas Singh. 2015. “A Projection Free Method for Generalized Eigenvalue Problem with a Nonsmooth Regularizer,” 1841–49.

Leng, Ning, Yuan Li, Brian E McIntosh, Bao Kim Nguyen, Bret Duffin, Shulan Tian, James A Thomson, Colin N Dewey, Ron Stewart, and Christina Kendziorski. 2015. “EBSeq-HMM: a Bayesian Approach for Identifying Gene-Expression Changes in Ordered RNA-Seq Experiments.” Bioinformatics (Oxford, England) 31 (16): 2614–22. doi:10.1093/bioinformatics/btv193.

Li, Xiao, and Karl Rohe. 2015. “Central Limit Theorems for Network Driven Sampling.” arXiv.org.

Liu, Ji, and Xiaojin Zhu. 2015. “The Teaching Dimension of Linear Learners.” arXiv.org.

Mukherjee, Lopamudra, Sathya N Ravi, Vamsi K Ithapu, Tyler Holmes, and Vikas Singh. 2015. “An NMF Perspective on Binary Hashing,” 4184–92.

Plumb, G, D Pachauri, R Kondor, and V Singh. n.d. “SnFFT: a Julia Toolkit for Fourier Analysis of Functions Over Permutations.” Pages.Cs.Wisc.Edu.

Raskutti, Garvesh, and Ming Yuan. 2015. “Convex Regularization for High-Dimensional Tensor Regression.” arXiv.org.

Rohe, Karl. 2015. “Network Driven Sampling; a Critical Threshold for Design Effects.” arXiv.org.

Roy, Sushmita, Alireza Fotuhi Siahpirani, Deborah Chasman, Sara Knaack, Ferhat Ay, Ron Stewart, Michael Wilson, and Rupa Sridharan. 2015. “A Predictive Modeling Approach for Cell Line-Specific Long-Range Regulatory Interactions.” Nucleic Acids Research 43 (18). Oxford University Press: 8694–8712. doi:10.1093/nar/gkv865.

Tanimura, Nobuyuki, Eli Miller, Kazuhiko Igarashi, David Yang, Judith N Burstyn, Colin N Dewey, and Emery H Bresnick. 2015. “Mechanism Governing Heme Synthesis Reveals a GATA Factor/Heme Circuit That Controls Differentiation.” EMBO Reports, December. EMBO Press, e201541465. doi:10.15252/embr.201541465.

Tran, Khoa A, Steven A Jackson, Zachariah P G Olufs, Nur Zafirah Zaidan, Ning Leng, Christina Kendziorski, Sushmita Roy, and Rupa Sridharan. 2015. “Collaborative Rewiring of the Pluripotency Network by Chromatin and Signalling Modulating Pathways.” Nature Communications 6. Nature Publishing Group: 6188. doi:10.1038/ncomms7188.

Xu, Jia, Lopamudra Mukherjee, Yin Li, Jamieson Warner, James M Rehg, and Vikas Singh. 2015. “Gaze-Enabled Egocentric Video Summarization via Constrained Submodular Maximization,” 2235–44.

Zeng, Xin, Bo Li, Rene Welch, Constanza Rojo, Ye Zheng, Colin N Dewey, and Sündüz Keleş. 2015. “Perm-Seq: Mapping Protein-DNA Interactions in Segmental Duplication and Highly Repetitive Regions of Genomes with Prior-Enhanced Read Mapping.” Edited by Kevin Chen. PLoS Computational Biology 11 (10). Public Library of Science: e1004491. doi:10.1371/journal.pcbi.1004491.

2014

Binkiewicz, Norbert, Joshua T Vogelstein, and Karl Rohe. 2014. “Covariate-Assisted Spectral Clustering.” arXiv.org.

Cai, T Tony, and Ming Yuan. 2014. “Rate-Optimal Detection of Very Short Signal Segments.” arXiv.org.

Church, Thomas, Jordan S Ellenberg, Benson Farb, and Rohit Nagpal. 2014a. “FI-Modules Over Noetherian Rings.” Geometry & Topology 18 (5). Mathematical Sciences Publishers: 2951–84. doi:10.2140/gt.2014.18.2951.

Collins, Maxwell D, Ji Liu, Jia Xu, Lopamudra Mukherjee, and Vikas Singh. 2014. “Spectral Clustering with a Convex Regularizer on Millions of Images.” In Computer Vision – ECCV 2014, 8691:282–98. Lecture Notes in Computer Science. Cham: Springer International Publishing. doi:10.1007/978-3-319-10578-9_19.

Cui, Qiurong, Karl Rohe, and Zhengjun Zhang. 2014. “Discussion of ‘Estimating the Historical and Future Probabilities of Large Terrorist Events’ by Aaron Clauset and Ryan Woodard.” arXiv.org. doi:10.1214/13-AOAS614F.

Ellenberg, Jordan. 2014a. How Not to Be Wrong. Penguin Press, New York.

Gitter, Anthony, Alfredo Braunstein, Andrea Pagnani, Carlo Baldassi, Christian Borgs, Jennifer Chayes, Riccardo Zecchina, and Ernest Fraenkel. 2014. “Sharing Information to Reconstruct Patient-Specific Pathways in Heterogeneous Diseases.” Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing. NIH Public Access, 39–50.

Ithapu, Vamsi K, Vikas Singh, Ozioma Okonkwo, and Sterling C Johnson. 2014. “Randomized Denoising Autoencoders for Smaller and Efficient Imaging Based AD Clinical Trials.” In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014, 8674:470–78. Lecture Notes in Computer Science. Cham: Springer International Publishing. doi:10.1007/978-3-319-10470-6_59.

Ithapu, Vamsi, Vikas Singh, Christopher Lindner, Benjamin P Austin, Chris Hinrichs, Cynthia M Carlsson, Barbara B Bendlin, and Sterling C Johnson. 2014a. “Extracting and Summarizing White Matter Hyperintensities Using Supervised Segmentation Methods in Alzheimer’s Disease Risk and Aging Studies.” Human Brain Mapping 35 (8): 4219–35. doi:10.1002/hbm.22472.

Ithapu, Vamsi, Vikas Singh, Christopher Lindner, Benjamin P Austin, Chris Hinrichs, Cynthia M Carlsson, Barbara B Bendlin, and Sterling C Johnson. 2014b. “Extracting and Summarizing White Matter Hyperintensities Using Supervised Segmentation Methods in Alzheimer’s Disease Risk and Aging Studies.” Human Brain Mapping 35 (8): 4219–35. doi:10.1002/hbm.22472.

Jain, Siddhartha, Anthony Gitter, and Ziv Bar-Joseph. 2014. “Multitask Learning of Signaling and Regulatory Networks with Application to Studying Human Response to Flu..” Edited by Mona Singh. PLoS Computational Biology 10 (12). Public Library of Science: e1003943. doi:10.1371/journal.pcbi.1003943.

Kennedy, Rodney A, L Balzano, Stephen J Wright, and Camillo J Taylor. 2014. “Online Algorithms for Factorization-Based Structure From Motion.” Applications of Computer Vision (WACV), 2014 IEEE Winter Conference on. IEEE, 37–44. doi:10.1109/WACV.2014.6836120.

Kim, Hyunwoo J, Nagesh Adluru, Barbara B Bendlin, Sterling C Johnson, Baba C Vemuri, and Vikas Singh. 2014. “Canonical Correlation Analysis on Riemannian Manifolds and Its Applications.” In Computer Vision – ECCV 2014, 8690:251–67. Lecture Notes in Computer Science. Cham: Springer International Publishing. doi:10.1007/978-3-319-10605-2_17.

Kim, Won Hwa, Vikas Singh, Moo K Chung, Chris Hinrichs, Deepti Pachauri, Ozioma C Okonkwo, and Sterling C Johnson. 2014. “Multi-Resolutional Shape Features via Non-Euclidean Wavelets: Applications to Statistical Analysis of Cortical Thickness.” NeuroImage 93 (June): 107–23. doi:10.1016/j.neuroimage.2014.02.028.

Knaack, Sara A, Alireza Fotuhi Siahpirani, and Sushmita Roy. 2014. “A Pan-Cancer Modular Regulatory Network Analysis to Identify Common and Cancer-Specific Network Components.” Cancer Informatics 13 (Suppl 5). Libertas Academica: 69–84. doi:10.4137/CIN.S14058.

Kuusisto, Finn, Vitor Santos Costa, Houssam Nassif, Elizabeth Burnside, David Page, and Jude Shavlik. 2014. “Support Vector Machines for Differential Prediction.” Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD … : Proceedings. ECML PKDD (Conference) 8725 (Chapter 4). Berlin, Heidelberg: Springer Berlin Heidelberg: 50–65. doi:10.1007/978-3-662-44851-9_4.

Lantz, E, S Jha, S Lin, D Page, and T Ristenpart. 2014. “Privacy in Pharmacogenetics: an End-to-End Case Study of Personalized Warfarin Dosing.” In.

Li, Bo, Nathanael Fillmore, Yongsheng Bai, Mike Collins, James A Thomson, Ron Stewart, and Colin N Dewey. 2014. “Evaluation of De Novo Transcriptome Assemblies From RNA-Seq Data..” Genome Biology 15 (12): 553. doi:10.1186/s13059-014-0553-5.

Liu, Jie, Chunming Zhang, Elizabeth Burnside, and David Page. 2014. “Multiple Testing Under Dependence via Semiparametric Graphical Models.” Proceedings of the … International Conference on Machine Learning. International Conference on Machine Learning 2014 (December). NIH Public Access: 955.

Malloy, Matthew L, and Robert D Nowak. 2014. “Near-Optimal Adaptive Compressed Sensing.” Information Theory, IEEE Transactions on 60 (7). IEEE: 4001–12. doi:10.1109/TIT.2014.2321552.

Natarajan, Sriraam, Kristian Kersting, Tushar Khot, and Jude Shavlik. 2014. Boosted Statistical Relational Learners. Cham: Springer International Publishing. doi:10.1007/978-3-319-13644-8.

Pachauri, Deepti, Risi Kondor, Gautam Sargur, and Vikas Singh. 2014. “Permutation Diffusion Maps (PDM) with Application to the Image Association Problem in Computer Vision,” 541–49.

Pimentel, D, R Nowak, and L Balzano. 2014. “On the Sample Complexity of Subspace Clustering with Missing Data.” In, 280–83. IEEE. doi:10.1109/SSP.2014.6884630.

Plis, Sergey M, Jing Sui, Terran Lane, Sushmita Roy, Vincent P Clark, Vamsi K Potluru, Rene J Huster, et al. 2014. “High-Order Interactions Observed in Multi-Task Intrinsic Networks Are Dominant Indicators of Aberrant Brain Function in Schizophrenia.” NeuroImage 102 Pt 1 (November): 35–48. doi:10.1016/j.neuroimage.2013.07.041.

Rohe, Karl. 2014. “A Note Relating Ridge Regression and OLS P-Values to Preconditioned Sparse Penalized Regression.” arXiv.org.

Salmon, Joseph, Zachary Harmany, Charles-Alban Deledalle, and Rebecca Willett. 2014. “Poisson Noise Reduction with Non-Local PCA.” Journal of Mathematical Imaging and Vision 48 (2). Springer US: 279–94. doi:10.1007/s10851-013-0435-6.

Wahba, Grace. 2014a. Spline Function: Overview. Chichester, UK: John Wiley & Sons, Ltd. doi:10.1002/9781118445112.stat02388.

Wahba, Grace. 2014b. “Smoothing Splines.” In International Encyclopedia of Statistical Science, 1349–53. Berlin, Heidelberg: Springer Berlin Heidelberg. doi:10.1007/978-3-642-04898-2_527.

Wen, Bruce L, Molly A Brewer, Oleg Nadiarnykh, James Hocker, Vikas Singh, Thomas R Mackie, and Paul J Campagnola. 2014. “Texture Analysis Applied to Second Harmonic Generation Image Data for Ovarian Cancer Classification.” Journal of Biomedical Optics 19 (9). International Society for Optics and Photonics: 096007–7. doi:10.1117/1.JBO.19.9.096007.

Yuan, Ming, and Cun-Hui Zhang. 2014. “On Tensor Completion via Nuclear Norm Minimization.” arXiv.org.

Zhang, Luwan, Grace Wahba, and Ming Yuan. 2014. “Distance Shrinkage and Euclidean Embedding via Regularized Kernel Estimation.” arXiv.org.

2013

Balzano, Laura, and Stephen J Wright. 2013. “On GROUSE and Incremental SVD.” In, 1–4. IEEE. doi:10.1109/CAMSAP.2013.6713992.

Dai, Bin, Shilin Ding, and Grace Wahba. 2013. “Multivariate Bernoulli Distribution.” Bernoulli 19 (4). Bernoulli Society for Mathematical Statistics and Probability: 1465–83. doi:10.3150/12-BEJSP10.

Ellenberg, Jordan. 2013b. “The Beauty of Bounded Gaps: a Huge Discovery About Prime Numbers—and What It Means for the Future of Mathematics.” Math Horizons 21 (1): 5–7. doi:10.4169/mathhorizons.21.1.5.

Gao, Xin, Kirby D Johnson, Yuan-I Chang, Meghan E Boyer, Colin N Dewey, Jing Zhang, and Emery H Bresnick. 2013. “Gata2 Cis-Element Is Required for Hematopoietic Stem Cell Generation in the Mammalian Embryo.” The Journal of Experimental Medicine 210 (13). Rockefeller Univ Press: 2833–42. doi:10.1084/jem.20130733.

Gitter, Anthony, and Ziv Bar-Joseph. 2013. “Identifying Proteins Controlling Key Disease Signaling Pathways.” Bioinformatics (Oxford, England) 29 (13). Oxford University Press: i227–36. doi:10.1093/bioinformatics/btt241.

Gitter, Anthony, Miri Carmi, Naama Barkai, and Ziv Bar-Joseph. 2013. “Linking the Signaling Cascades and Dynamic Regulatory Networks Controlling Stress Responses.” Genome Research 23 (2). Cold Spring Harbor Lab: 365–76. doi:10.1101/gr.138628.112.

Hinrichs, Chris, Vamsi Ithapu, Qinyuan Sun, Sterling C Johnson, and Vikas Singh. 2013. “Speeding Up Permutation Testing in Neuroimaging,” 890–98.

Hwa Kim, Won, Moo K Chung, and Vikas Singh. 2013. “Multi-Resolution Shape Analysis via Non-Euclidean Wavelets: Applications to Mesh Segmentation and Surface Alignment Problems,” 2139–46.

Kim, Won Hwa, Nagesh Adluru, Moo K Chung, Sylvia Charchut, Johnson J GadElkarim, Lori Altshuler, Teena Moody, Anand Kumar, Vikas Singh, and Alex D Leow. 2013. “Multi-Resolutional Brain Network Filtering and Analysis via Wavelets on Non-Euclidean Space.” In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013, 8151:643–51. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer Berlin Heidelberg. doi:10.1007/978-3-642-40760-4_80.

LeGault, Laura H, and Colin N Dewey. 2013. “Inference of Alternative Splicing From RNA-Seq Data with Probabilistic Splice Graphs.” Bioinformatics (Oxford, England) 29 (18). Oxford University Press: 2300–2310. doi:10.1093/bioinformatics/btt396.

Li, Shijun, Wei Guo, Colin N Dewey, and Marion L Greaser. 2013. “Rbm20 Regulates Titin Alternative Splicing as a Splicing Repressor.” Nucleic Acids Research 41 (4). Oxford University Press: 2659–72. doi:10.1093/nar/gks1362.

Liu, Jie, and David Page. 2013. “Bayesian Estimation of Latently-Grouped Parameters in Undirected Graphical Models..” Advances in Neural Information Processing Systems 2013 (December). NIH Public Access: 1232–40.

Pachauri, Deepti, Risi Kondor, and Vikas Singh. 2013a. “Solving the Multi-Way Matching Problem by Permutation Synchronization,” 1860–68.

Pachauri, Deepti, Risi Kondor, and Vikas Singh. 2013b. “Solving the Multi-Way Matching Problem by Permutation Synchronization,” 1860–68.

Qin, Tai, and Karl Rohe. 2013b. “Regularized Spectral Clustering Under the Degree-Corrected Stochastic Blockmodel.” arXiv.org.

Roetker, Nicholas S, C David Page, James A Yonker, Vicky Chang, Carol L Roan, Pamela Herd, Taissa S Hauser, Robert M Hauser, and Craig S Atwood. 2013. “Assessment of Genetic and Nongenetic Interactions for the Prediction of Depressive Symptomatology: an Analysis of the Wisconsin Longitudinal Study Using Machine Learning Algorithms.” American Journal of Public Health 103 Suppl 1 (S1). American Public Health Association: S136–44. doi:10.2105/AJPH.2012.301141.

Rohe, Karl, and Tai Qin. 2013. “The Blessing of Transitivity in Sparse and Stochastic Networks.” arXiv.org.

Roy, Sushmita, Ilan Wapinski, Jenna Pfiffner, Courtney French, Amanda Socha, Jay Konieczka, Naomi Habib, Manolis Kellis, Dawn Thompson, and Aviv Regev. 2013. “Arboretum: Reconstruction and Analysis of the Evolutionary History of Condition-Specific Transcriptional Modules..” Genome Research 23 (6). Cold Spring Harbor Lab: 1039–50. doi:10.1101/gr.146233.112.

Roy, Sushmita, Stephen Lagree, Zhonggang Hou, James A Thomson, Ron Stewart, and Audrey P Gasch. 2013. “Integrated Module and Gene-Specific Regulatory Inference Implicates Upstream Signaling Networks.” Edited by Teresa M Przytycka. PLoS Computational Biology 9 (10). Public Library of Science: e1003252. doi:10.1371/journal.pcbi.1003252.

Thompson, Dawn A, Sushmita Roy, Michelle Chan, Mark P Styczynski, Jenna Pfiffner, Courtney French, Amanda Socha, et al. 2013. “Correction: Evolutionary Principles of Modular Gene Regulation in Yeasts.” eLife 2. eLife Sciences Publications Limited: e01114. doi:10.7554/eLife.01114.

Wright, Stephen J, Dimitri Kanevsky, Li Deng, Xiaodong He, Georg Heigold, and Haizhou Li. 2013. “Optimization Algorithms and Applications for Speech and Language Processing.” Audio, Speech, and Language Processing, IEEE Transactions on 21 (11). IEEE: 2231–43. doi:10.1109/TASL.2013.2283777.

Xu, Jia, Maxwell D Collins, and Vikas Singh. 2013. “Incorporating User Interaction and Topological Constraints Within Contour Completion via Discrete Calculus,” 1886–93.

Xu, Jia, Vamsi K Ithapu, Lopamudra Mukherjee, James M Rehg, and V Singh. 2013. “GOSUS: Grassmannian Online Subspace Updates with Structured-Sparsity.” 2013 IEEE International Conference on Computer Vision (ICCV). IEEE, 3376–83. doi:10.1109/ICCV.2013.419.

Xu, Jia, Vamsi K Ithapu, Lopamudra Mukherjee, James M Rehg, and Vikas Singh. 2013b. “GOSUS: Grassmannian Online Subspace Updates with Structured-Sparsity,” 3376–83.

Zhang, Yan, Amy Cooke, Sookhee Park, Colin N Dewey, Marvin Wickens, and Michael D Sheets. 2013. “Bicaudal-C Spatially Controls Translation of Vertebrate Maternal mRNAs.” RNA (New York, N.Y.) 19 (11). Cold Spring Harbor Lab: 1575–82. doi:10.1261/rna.041665.113.

Zhu, Xiaojin. 2013. “Machine Teaching for Bayesian Learners in the Exponential Family.” arXiv.org.

2012

Adluru, Nagesh, Vikas Singh, and Andrew L Alexander. 2012. “Adaptive Cuts for Extracting Specific White Matter Tracts.” 2012 IEEE 9th International Symposium on Biomedical Imaging (ISBI 2012). IEEE, 1393–96. doi:10.1109/ISBI.2012.6235828.

Bar-Joseph, Ziv, Anthony Gitter, and Itamar Simon. 2012. “Studying and Modelling Dynamic Biological Processes Using Time-Series Gene Expression Data..” Nature Reviews. Genetics 13 (8). Nature Publishing Group: 552–64. doi:10.1038/nrg3244.

Cai, T Tony, and Ming Yuan. 2012a. “Optimal Estimation of the Mean Function Based on Discretely Sampled Functional Data: Phase Transition.” arXiv.org. Institute of Mathematical Statistics. doi:10.1214/11-AOS898.

Cai, T Tony, and Ming Yuan. 2012b. “Adaptive Covariance Matrix Estimation Through Block Thresholding.” arXiv.org. Institute of Mathematical Statistics. doi:10.1214/12-AOS999.

Cheung, B L P, R Nowak, Hyong Chol Lee, W Drongelen, and B D Veen. 2012. “Cross Validation for Selection of Cortical Interaction Models From Scalp EEG or MEG.” IEEE Transactions on Biomedical Engineering 59 (2). IEEE: 504–14. doi:10.1109/TBME.2011.2174991.

Church, T, J S Ellenberg, and B Farb. 2012. “FI-Modules: a New Approach to Stability for Sn-Representations.” arXiv.org.

Collins, Maxwell D, Jia Xu, Leo Grady, and Vikas Singh. 2012. “Random Walks Based Multi-Image Segmentation: Quasiconvexity Results and GPU-Based Solutions.” 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 1656–63. doi:10.1109/CVPR.2012.6247859.

Dewey, Colin N. 2012. “Whole-Genome Alignment.” Methods in Molecular Biology (Clifton, N.J.) 855 (Chapter 8). Totowa, NJ: Humana Press: 237–57. doi:10.1007/978-1-61779-582-4_8.

Ellenberg, Jordan S, Chris Hall, and Emmanuel Kowalski. 2012c. “Expander Graphs, Gonality, and Variation of Galois Representations.” Duke Mathematical Journal 161 (7). Duke University Press: 1233–75. doi:10.1215/00127094-1593272.

Harmany, Zachary T, Roummel F Marcia, and Rebecca M Willett. 2012. “This Is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms—Theory and Practice.” Image Processing, IEEE Transactions on 21 (3). IEEE: 1084–96. doi:10.1109/TIP.2011.2168410.

Hinrichs, Chris, Vikas Singh, Jiming Peng, and Sterling Johnson. 2012a. “Q-MKL: Matrix-Induced Regularization in Multi-Kernel Learning with Applications to Neuroimaging,” 1421–29.

Hinrichs, Chris, Vikas Singh, Jiming Peng, and Sterling Johnson. 2012b. “Q-MKL: Matrix-Induced Regularization in Multi-Kernel Learning with Applications to Neuroimaging,” 1421–29.

Holby, Edward F, Jeff Greeley, and Dane Morgan. 2012. “Thermodynamics and Hysteresis of Oxide Formation and Removal on Platinum (111) Surfaces.” The Journal of Physical … 116 (18). American Chemical Society: 9942–46. doi:10.1021/jp210805z.

Jacobsen, Heather, Brian Puchala, Thomas F Kuech, and Dane Morgan. 2012. “<I>Ab Initio</I> Study of the Strain Dependent Thermodynamics of Bi Doping in GaAs.” Physical Review B 86 (8). American Physical Society: 085207. doi:10.1103/PhysRevB.86.085207.

Jia, Jinzhu, and Karl Rohe. 2012. “Preconditioning to Comply with the Irrepresentable Condition.” arXiv.org.

Kim, Won H, Deepti Pachauri, Charles Hatt, Moo K Chung, Sterling Johnson, and Vikas Singh. 2012a. “Wavelet Based Multi-Scale Shape Features on Arbitrary Surfaces for Cortical Thickness Discrimination,” 1241–49.

Kim, Won H, Deepti Pachauri, Charles Hatt, Moo K Chung, Sterling Johnson, and Vikas Singh. 2012b. “Wavelet Based Multi-Scale Shape Features on Arbitrary Surfaces for Cortical Thickness Discrimination,” 1241–49.

Koltchinskii, Vladimir, and Ming Yuan. 2012. “Sparsity in Multiple Kernel Learning.” arXiv.org. Institute of Mathematical Statistics. doi:10.1214/10-AOS825.

Mukherjee, Lopamudra, Vikas Singh, Jia Xu, and Maxwell D Collins. 2012. “Analyzing the Subspace Structure of Related Images: Concurrent Segmentation of Image Sets.” In Computer Vision – ECCV 2012, 7575:128–42. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer Berlin Heidelberg. doi:10.1007/978-3-642-33765-9_10.

Navlakha, Saket, Anthony Gitter, and Ziv Bar-Joseph. 2012. “A Network-Based Approach for Predicting Missing Pathway Interactions.” Edited by Costas D Maranas. PLoS Computational Biology 8 (8). Public Library of Science: e1002640. doi:10.1371/journal.pcbi.1002640.

Noto, Keith, and Mark Craven. 2012. “Learning Hidden Markov Models for Regression Using Path Aggregation.” arXiv.org.

Pachauri, Deepti, Maxwell Collins, Risi Kondor, and Vikas Singh. 2012. “Incorporating Domain Knowledge in Matching Problems via Harmonic Analysis..” Proceedings of the … International Conference on Machine Learning. International Conference on Machine Learning 2012. NIH Public Access: 1271–78.

Pachauri, Deepti, Maxwell Collins, Vikas Singh, and Risi Kondor. 2012. “Incorporating Domain Knowledge in Matching Problems via Harmonic Analysis.” arXiv.org.

Peng, Jiming, Lopamudra Mukherjee, Vikas Singh, Dale Schuurmans, and Linli Xu. 2012. “An Efficient Algorithm for Maximal Margin Clustering.” Journal of Global Optimization 52 (1). Springer US: 123–37. doi:10.1007/s10898-011-9691-4.

Rao, N S, B Recht, and R D Nowak. 2012. “Universal Measurement Bounds for Structured Sparse Signal Recovery.” International ….

Garvesh Raskutti, Martin J Wainwright, and Bin Yu. 2012. “Minimax-Optimal Rates for Sparse Additive Models Over Kernel Classes via Convex Programming.” The Journal of Machine Learning Research 13 (1). JMLR.org: 389–427.

Rohe, Karl, Tai Qin, and Bin Yu. 2012. “Co-Clustering for Directed Graphs: the Stochastic Co-Blockmodel and Spectral Algorithm Di-Sim.” arXiv.org.

Rohe, Karl, Tai Qin, and Haoyang Fan. 2012. “The Highest Dimensional Stochastic Blockmodel with a Regularized Estimator.” arXiv.org.

Samworth, Richard J, and Ming Yuan. 2012. “Independent Component Analysis via Nonparametric Maximum Likelihood Estimation.” arXiv.org.

Schulz, Marcel H, William E Devanny, Anthony Gitter, Shan Zhong, Jason Ernst, and Ziv Bar-Joseph. 2012. “DREM 2.0: Improved Reconstruction of Dynamic Regulatory Networks From Time-Series Expression Data.” BMC Systems Biology 6 (1). BioMed Central: 104. doi:10.1186/1752-0509-6-104.

Wegkamp, Marten, and Ming Yuan. 2012. “Support Vector Machines with a Reject Option.” arXiv.org. Bernoulli Society for Mathematical Statistics and Probability. doi:10.3150/10-BEJ320.

Werner-Washburne, M, Sushmita Roy, and George S Davidson. 2012. “Aging and the Survival of Quiescent and Non-Quiescent Cells in Yeast Stationary-Phase Cultures.” Sub-Cellular Biochemistry 57 (Chapter 6). Dordrecht: Springer Netherlands: 123–43. doi:10.1007/978-94-007-2561-4_6.

Xu, Jun-Ming, Aniruddha Bhargava, Robert Nowak, and Xiaojin Zhu. 2012. “Robust Spatio-Temporal Signal Recovery From Noisy Counts in Social Media.” arXiv.org.

Yankovich, Andrew B, Brian Puchala, Fei Wang, Jung-Hun Seo, Dane Morgan, Xudong Wang, Zhenqiang Ma, Alex V Kvit, and Paul M Voyles. 2012. “Stable P-Type Conduction From Sb-Decorated Head-to-Head Basal Plane Inversion Domain Boundaries in ZnO Nanowires.” Nano … 12 (3). American Chemical Society: 1311–16. doi:10.1021/nl203848t.

Yuan, Ming. 2012. “Discussion: Latent Variable Graphical Model Selection via Convex Optimization.” arXiv.org. doi:10.1214/12-AOS979.

Yuan, Ming, and T Tony Cai. 2012. “A Reproducing Kernel Hilbert Space Approach to Functional Linear Regression.” arXiv.org. Institute of Mathematical Statistics. doi:10.1214/09-AOS772.

2011

Austin, Benjamin, Erik Kastman, Yin Huang, Guofan Xu, Nayanjyoti Pathak, Vikas Singh, Sean Fain, et al. 2011. “The Relationship of White Matter Hyperintensities with Perfusion and Cognition in Middle-Aged Adults at Risk for Alzheimer’s Disease.” Alzheimer“S & Dementia: the Journal of the Alzheimer”S Association 7 (4). Elsevier: e33–e34. doi:10.1016/j.jalz.2011.09.094.

Dewey, Colin N. 2011. “Positional Orthology: Putting Genomic Evolutionary Relationships Into Context..” Briefings in Bioinformatics 12 (5). Oxford University Press: 401–12. doi:10.1093/bib/bbr040.

Gitter, Anthony, Judith Klein-Seetharaman, Anupam Gupta, and Ziv Bar-Joseph. 2011. “Discovering Pathways by Orienting Edges in Protein Interaction Networks..” Nucleic Acids Research 39 (4). Oxford University Press: e22–e22. doi:10.1093/nar/gkq1207.

Li, Bo, and Colin N Dewey. 2011. “RSEM: Accurate Transcript Quantification From RNA-Seq Data with or Without a Reference Genome.” BMC Bioinformatics 12 (1). BioMed Central: 1. doi:10.1186/1471-2105-12-323.

Mukherjee, Lopamudra, Vikas Singh, and Jiming Peng. 2011. “Scale Invariant Cosegmentation for Image Groups.” 2011 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 1881–88. doi:10.1109/CVPR.2011.5995420.

Rao, Nikhil S, Robert D NowakStephen J Wright, and Nick G Kingsbury. 2011. “Convex Approaches to Model Wavelet Sparsity Patterns.” In, 1917–20. IEEE. doi:10.1109/ICIP.2011.6115845.

Roy, Sushmita, Margaret Werner-Washburne, and Terran Lane. 2011. “A Multiple Network Learning Approach to Capture System-Wide Condition-Specific Responses.” Bioinformatics (Oxford, England) 27 (13). Oxford University Press: 1832–38. doi:10.1093/bioinformatics/btr270.

Willett, Rebecca M, Roummel F Marcia, and Jonathan M Nichols. 2011. “Compressed Sensing for Practical Optical Imaging Systems: a Tutorial.” Optical Engineering 50 (7). International Society for Optics and Photonics: 072601–072601–13. doi:10.1117/1.3596602.

2010
Bajwa, Waheed U, Jarvis Haupt, Akbar M Sayeed, and Robert Nowak. 2010. “Compressed Channel Sensing: a New Approach to Estimating Sparse Multipath Channels.” Proceedings of the IEEE 98 (6). IEEE: 1058–76. doi:10.1109/JPROC.2010.2042415.

Bennett, Michael A, Jordan S Ellenberg, and Nathan C Ng. 2010. “THE DIOPHANTINE EQUATION a 4+ 2 δB 2= C N.” International Journal of Number Theory 06 (02): 311–38. doi:10.1142/S1793042110002971.

Ellenberg, Jordan S, Richard Oberlin, and Terence Tao. 2010. “The Kakeya Set and Maximal Conjectures for Algebraic Varieties Over Finite Fields.” Mathematika 56 (01). Cambridge University Press: 1–25. doi:10.1112/S0025579309000400.

Haupt, Jarvis, Waheed U Bajwa, Gil Raz, and Robert Nowak. 2010. “Toeplitz Compressed Sensing Matrices with Applications to Sparse Channel Estimation.” Information Theory, IEEE Transactions on 56 (11). IEEE: 5862–75. doi:10.1109/TIT.2010.2070191.

Mukherjee, Lopamudra, Vikas Singh, Junbiao Peng, and Chris Hinrichs. 2010. “Learning Kernels for Variants of Normalized Cuts: Convex Relaxations and Applications.” 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 3145–52. doi:10.1109/CVPR.2010.5540076

Raskutti, Garvesh, Martin J Wainwright, and Bin Yu. 2010a. “Restricted Eigenvalue Properties for Correlated Gaussian Designs.” The Journal of Machine Learning Research 11 (March). JMLR.org: 2241–59.

Raskutti, Garvesh, Martin J Wainwright, and Bin Yu. 2010b. “Minimax-Optimal Rates for Sparse Additive Models Over Kernel Classes via Convex Programming.” arXiv.org.

Tropp, Joel A, and Stephen J Wright. 2010. “Computational Methods for Sparse Solution of Linear Inverse Problems.” Proceedings of the IEEE 98 (6). IEEE: 948–58. doi:10.1109/JPROC.2010.2044010.

Venkatesh, A, and J S Ellenberg. 2010. “Statistics of Number Fields and Function Fields.” International Congress of Mathematicians, Hyderabad, India 2010.

Yuan, Ming, V Roshan Joseph, and Hui Zou. 2010. “Structured Variable Selection and Estimation.” arXiv.org. doi:10.1214/09-AOAS254.