Publications

2017

Johnstone, IM; Nadler, B (2017). Roy's Largest Root Test Under Rank-One Alternatives.  Biometrika. 104:181-193.  Abstract
Amit Moscovich, Ariel Jaffe, Boaz Nadler (2017). Minimax-Optimal Semi-Supervised Regression on Unknown Manifolds.  Artificial Intelligence and Statistics. 20.
Wang, YQ; Trouve, A; Amit, Y; Nadler, B (2017). Detecting Curved Edges in Noisy Images in Sublinear Time.  Journal of Mathematical Imaging and Vision. 59:373-393.  Abstract
Moscovich, A; Nadler, B (2017). Fast Calculation of Boundary Crossing Probabilities For Poisson Processes.  Statistics & Probability Letters. 123:177-182.  Abstract
Amit Moscovich, Boaz Nadler (2017). Fast Calculation of Boundary Crossing Probabilities For Poisson Processes.  Statistics and Probability Letters. 123:177-182.

2016

Nadler, B (2016). Discussion of Influential Features Pca For High Dimensional Clustering".  Annals of Statistics. 44:2366-2371.
A. Jaffe, E. Fetaya, B. Nadler, T. Jiang, Y. Kluger (2016). Unsupervised Ensemble Learning With Dependent Classifiers.  19th International Conference on Artificial Intelligence and Statistics (Aistats), 2016.
Rosenblatt, JD; Nadler, B (2016). On the Optimality of Averaging in Distributed Statistical Learning.  Information and Inference-a Journal of the Ima. 5:379-404.  Abstract
Shwartz, O; Nadler, B (2016). Detecting the Large Entries of a Sparse Covariance Matrix in Sub-Quadratic Time.  Information and Inference-a Journal of the Ima. 5:304-330.  Abstract
Ofir, N; Galun, M; Nadler, B; Basri, R (2016). Fast Detection of Curved Edges at Low Snr.  2016 Ieee Conference on Computer Vision and Pattern Recognition (Cpvr). 213-221.  Abstract
Leshem, B; Xu, R; Miao, JW; Nadler, B; Oron, D; Dudovich, N; Raz, O (2016). Direct Single-Shot Phase Retrieval For Separated Objects (Conference Presentation).  Quantitative Phase Imaging II. 9718.
Moscovich, A; Nadler, B; Spiegelman, C (2016). On the Exact Berk-Jones Statistics and Their p-Value Calculation.  Electronic Journal of Statistics. 10:2329-2354.  Abstract
U. Shaham, X. Cheng, O. Dror, A. Jaffe, B. Nadler, J. Chang and Y. Kluger (2016). A Deep Learning Approach to Unsupervised Ensemble Learning.  International Conference on Machine Learning.
A. Moscovich, B. Nadler, C. Spiegelman (2016). On the Exact Berk-Jones Statistics and Their p-Value Calculation.  Electronic Journal of Statistics. 10:2329-2354.

For code see here

Leshem, B; Xu, R; Dallal, Y; Miao, JW; Nadler, B; Oron, D; Dudovich, N; Raz, O (2016). Direct Single-Shot Phase Retrieval from the Diffraction Pattern of Separated Objects.  Nature Communications. 7.  Abstract
Yi-Qing Wang, Alain Trouve, Yali Amit, Boaz Nadler (2016). Detecting Curved Edges in Noisy Images in Sublinear Time.  Journal of Mathematical Imaging and Vision. 1-21.

2015

R. Weiss and B. Nadler (2015). Learning Parametric Output Hmms With Two Aliased States.  International Conference on Machine Learning (Icml), 2015.
A. Jaffe, B. Nadler, Y. Kluger (2015). Estimating the Accuracies of Multiple Classifiers Without Labeled Data.  Aistats-2015.
Horev, I; Nadler, B; Arias-Castro, E; Galun, M; Basri, R (2015). Detection of Long Edges on a Computational Budget: a Sublinear Approach.  SIAM Journal on Imaging Sciences. 8:458-483.  Abstract
Krauthgamer, R; Nadler, B; Vilenchik, D (2015). Do Semidefinite Relaxations Solve Sparse Pca up to the Information Limit?.  Annals of Statistics. 43:1300-1322.  Abstract

2014

Raz, O; Leshem, B; Miao, JW; Nadler, B; Oron, D; Dudovich, N (2014). Direct Phase Retrieval in Double Blind Fourier Holography.  Optics Express. 22:24935-24950.  Abstract
Parisi, F; Strino, F; Nadler, B; Kluger, Y (2014). Ranking and Combining Multiple Predictors Without Labeled Data.  Proceedings of the National Academy of Sciences of the United States of America. 111:1253-1258.  Abstract

2013

Raz, O; Dudovich, N; Nadler, B (2013). Vectorial Phase Retrieval of 1-D Signals.  Ieee Transactions on Signal Processing. 61:1632-1643.  Abstract
A. Kontorovich, B. Nadler and R. Weiss (2013). On Learning Parametric-Output Hmms.  Icml, 2013.
N. Efrat, D. Glasner, A. Apartsin, B. Nadler, A. Levin (2013). Accurate Blur Models vs. Image Priors in Single Image Super-Resolution.  Iccv, 2013.
Birnbaum, A; Johnstone, IM; Nadler, B; Paul, D (2013). Minimax Bounds For Sparse Pca With Noisy High-Dimensional Data.  Annals of Statistics. 41:1055-1084.  Abstract
Gavish, M; Nadler, B (2013). Normalized Cuts Are Approximately Inverse Exit Times.  SIAM Journal on Matrix Analysis and Applications. 34:757-772.  Abstract

2012

A. Levin, B. Nadler, F. Durand, W. Freeman, (2012). Patch Complexity, Finite Pixel Correlations and Optimal Denoising.  European Conference Computer Vision (Eccv), 2012.
J. Roeder, B. Nadler, K. Kunzmann and F.A. Hamprecht (2012). Active Learning With Distributional Estimates.  Conference on Uncertainty in Artificial Intelligence (Uai), 2012.

2011

Levin, A; Nadler, B (2011). Natural Image Denoising: Optimality and Inherent Bounds.  2011 Ieee Conference on Computer Vision and Pattern Recognition (Cvpr). -40.  Abstract
Raz, O; Schwartz, O; Austin, D; Wyatt, AS; Schiavi, A; Smirnova, O; Nadler, B; Walmsley, IA; Oron, D; Dudovich, N (2011). Vectorial Phase Retrieval For Linear Characterization of Attosecond Pulses.  Physical Review Letters. 107.  Abstract
Nadler, B (2011). On the Distribution of the Ratio of the Largest Eigenvalue to the Trace of a Wishart Matrix.  Journal of Multivariate Analysis. 102:363-371.  Abstract
Nadler, B; Johnstone, IM (2011). Detection Performance of Roy's Largest Root Test When the Noise Covariance Matrix is Arbitrary.  2011 Ieee Statistical Signal Processing Workshop (Ssp). 681-684.  Abstract
B. Nadler and I. M. Johnstone (2011). On the Distribution of Roy's Largest Root Test in Manova and in Signal Detection in Noise.  Technical Report, Department of Statistics, Stanford University, 2011.
Nadler, B; Kontorovich, A (2011). Model Selection For Sinusoids in Noise: Statistical Analysis and a New Penalty Term.  Ieee Transactions on Signal Processing. 59:1333-1345.  Abstract
Nadler, B; Penna, F; Garello, R (2011). Performance of Eigenvalue-Based Signal Detectors With Known and Unknown Noise Level.  2011 Ieee International Conference on Communications (Icc).  Abstract

2010

Alpert, S; Galun, M; Nadler, B; Basri, R (2010). Detecting Faint Curved Edges in Noisy Images.  Computer Vision-Eccv 2010, pt iv. 6314:750-763.  Abstract
Nadler, B (2010). Nonparametric Detection of Signals by Information Theoretic Criteria: Performance Analysis and an Improved Estimator.  Ieee Transactions on Signal Processing. 58:2746-2756.  Abstract
Haddad, R; Weiss, T; Khan, R; Nadler, B; Mandairon, N; Bensafi, M; Schneidman, E; Sobel, N (2010). Global Features of Neural Activity in the Olfactory System Form a Parallel Code That Predicts Olfactory Behavior and Perception.  Journal of Neuroscience. 30:9017-9026.  Abstract
N. Arkind, B. Nadler (2010). Parametric Joint Detection-Estimation of the Number of Sources in Array Processing.  Sixth Ieee Sensor Array and Multichannel Signal Processing Workshop, 2010.
M. Gavish, B. Nadler, R.R. Coifman (2010). Multiscale Wavelets on Trees, Graphs and High Dimensional Data: Theory and Applications to Semi Supervised Learning.  International Conference on Machine Learning, 2010.
Xu, R; Damelin, S; Nadler, B; Wunsch, DC (2010). Clustering of High-Dimensional Gene Expression Data With Feature Filtering Methods and Diffusion Maps.  Artificial Intelligence in Medicine. 48:91-8.  Abstract

2009

Kritchman, S; Nadler, B (2009). Non-Parametric Detection of the Number of Signals: Hypothesis Testing and Random Matrix Theory.  Ieee Transactions on Signal Processing. 57:3930-3941.  Abstract
Kontorovich, L; Nadler, B (2009). Universal Kernel-Based Learning With Applications to Regular Languages.  Journal of Machine Learning Research. 10:1095-1129.  Abstract
Modlin, IM; Gustafsson, BI; Drozdov, I; Nadler, B; Pfragner, R; Kidd, M (2009). Principal Component Analysis, Hierarchical Clustering, and Decision Tree Assessment of Plasma Mrna and Hormone Levels as an Early Detection Strategy For Small Intestinal Neuroendocrine (Carcinoid) Tumors.  Annals of Surgical Oncology. 16:487-498.  Abstract
Nadler, B (2009). On Consistency and Sparsity For Principal Components Analysis in High Dimensions Discussion.  Journal of the American Statistical Association. 104:694-697.
B. Nadler, N. Srebro and X. Zhou (2009). Semi-Supervised Learning With the Graph-Laplacian: the Limit of Infinite Unlabelled Data.  Neural Information Processing Systems (Nips), Vol. 22, 2009.
Drozdov, I; Kidd, M; Nadler, B; Camp, RL; Mane, SM; Hauso, O; Gustafsson, BI; Modlin, IM (2009). Predicting Neuroendocrine Tumor (Carcinoid) Neoplasia Using Gene Expression Profiling and Supervised Machine Learning.  Cancer. 115:1638-1650.  Abstract
Singer, A; Shkolnisky, Y; Nadler, B (2009). Diffusion Interpretation of Nonlocal Neighborhood Filters For Signal Denoising.  SIAM Journal on Imaging Sciences. 2:118-139.  Abstract
Ipsen, ICF; Nadler, B (2009). Refined Perturbation Bounds For Eigenvalues of Hermitian and Non-Hermitian Matrices.  SIAM Journal on Matrix Analysis and Applications. 31:40-53.  Abstract

2008

Lee, AB; Nadler, B; Wasserman, L (2008). Rejoinder of: Treelets - an Adaptive Multi-Scale Basis For Spare Unordered Data.  Annals of Applied Statistics. 2:494-500.
Lee, AB; Nadler, B; Wasserman, L (2008). Treelets - an Adaptive Multi-Scale Basis For Sparse Unordered Data.  Annals of Applied Statistics. 2:435-471.  Abstract
Nadler, B (2008). Finite Sample Approximation Results For Principal Component Analysis: a Matrix Perturbation Approach.  Annals of Statistics. 36:2791-2817.  Abstract
Kemelmacher-Shlizerman, I; Basri, R; Nadler, B (2008). 3D Shape Reconstruction of Mooney Faces.  2008 Ieee Conference on Computer Vision and Pattern Recognition, Vols 1-12. 3323-3330.  Abstract
Coifman, RR; Kevrekidis, IG; Lafon, S; Maggioni, M; Nadler, B (2008). Diffusion Maps, Reduction Coordinates, and Low Dimensional Representation of Stochastic Systems.  Multiscale Modeling & Simulation. 7:842-864.  Abstract
Kritchman, S; Nadler, B (2008). Determining the Number of Components in a Factor Model from Limited Noisy Data.  Chemometrics and Intelligent Laboratory Systems. 94:19-32.  Abstract
Kritchman, S; Nadler, B (2008). Nonparametric Detection of the Number of Signals and Random Matrix Theory.  2008 42nd Asilomar Conference on Signals, Systems and Computers, Vols 1-4. 1680-1683.  Abstract

2007

B. Nadler, S. Lafon, R. R. Coifman, I. G. Kevrekidis (2007). Diffusion Maps - a Probabilistic Interpretation For Spectral Embedding and Clustering Algorithms.  In Principal Manifolds For Data Visualization and Dimension Reduction, a.n. Gorban, b. Kegl, D.c. Wunsch and a. Zinovyev (Eds), Springer, 2007.
Erban, R; Frewen, TA; Wang, X; Elston, TC; Coifman, R; Nadler, B; Kevrekidis, IG (2007). Variable-Free Exploration of Stochastic Models: a Gene Regulatory Network Example.  Journal of Chemical Physics. 126.  Abstract
Kidd, M; Nadler, B; Mane, S; Eick, G; Malfertheiner, M; Champaneria, M; Pfragner, R; Modlin, I (2007). Genechip, Genorm, and Gastrointestinal Tumors: Novel Reference Genes For Real-Time Pcr.  Physiological Genomics. 30:363-370.  Abstract

2006

Nadler, B; Lafon, S; Coifman, RR; Kevrekidis, IG (2006). Diffusion Maps, Spectral Clustering and Reaction Coordinates of Dynamical Systems.  Applied and Computational Harmonic Analysis. 21:113-127.  Abstract
B. Nadler, M. Galun (2006). Fundamental Limitations of Spectral Clustering.  Neural Information Processing Systems, Vol. 19, 2006.

2005

B. Nadler, R. R. Coifman (2005). The Prediction Error in Cls and Pls: the Importance of Feature Selection Prior to Multivariate Calibration.  Preprint of an Article Published in Journal of Chemometrics, 19(2):107-118 (2005).
B. Nadler, R. R. Coifman (2005). Partial Least Squares, Beer's Law and the Net Analyte Signal: Statistical Modeling and Analysis.  Preprint of an Article Published in Journal of Chemometrics, 19(1):45-54 (2005).

The final version can be accessed at the publisher's website by clicking here

This paper was awarded the Kowalski prize for best theoretical paper in J. Chemometrics in 2004-5.

B. Nadler, Z. Schuss, A. Singer (2005). Langevin Trajectories Between Fixed Concentrations.  Physical Review Letters, 94 (2005) 218101.
B. Nadler, S. Lafon, R. R. Coifman, I. G. Kevrekidis (2005). Diffusion Maps, Spectral Clustering and Eigenfunctions of Fokker-Planck Operators.  Neural Information Processing Systems (Nips), Vol 18, 2005.
R. R. Coifman, S. Lafon, A.B. Lee, M. Maggioni,B. Nadler, F. Warner, S. Zucker (2005). Geometric Diffusion as a Tool For Harmonic Analysis and Structure Definition of Data, Part i: Diffusion Maps.  Proceedings of the National Academy of Sciences, 102(21):7426-31 (2005).
R. R. Coifman, S. Lafon, A.B. Lee, M. Maggioni,B. Nadler, F. Warner, S. Zucker (2005). Geometric Diffusion as a Tool For Harmonic Analysis and Structure Definition of Data, Part II: Multiscale Methods.  Proceedings of the National Academy of Sciences, 102(21):7432-37 (2005).

2004

B. Nadler, Z. Schuss, U. Hollerbach, R.S. Eisenberg, (2004). Saturation of Conductance in Single Ion Channels: the Blocking Effect of the Near Reaction Field.  Physical Review E, 70 (2004) 051912.
A. Singer, Z. Schuss, B. Nadler, R.S. Eisenberg (2004). Memoryless Control of Boundary Concentrations of Diffusing Particles.  Physical Review E, 70 (2004) 061106.
B. Nadler, Z. Schuss, A. Singer, R.S. Eisenberg (2004). Ionic Diffusion Through Confined Geometries: from Langevin Equations to Partial Differential Equations.  Journal of Physics: Condensed Matter, 16(22) (2004) S2153-S2165.

2003

B. Nadler, U. Hollerbach and R.S. Eisenberg (2003). Dielectric Boundary Force and Its Crucial Role in Gramicidin.  Physical Review E, 68 (2003) 021905.
B. Nadler, T. Naeh, Z. Schuss (2003). Connecting a Discrete Ionic Simulation to a Continuum.  SIAM Journal on Applied Mathematics, 63, Number 3 (2003), pp. 850-873.

2001

Z. Schuss, B. Nadler, R.S. Eisenberg (2001). Derivation of Poisson and Nernst-Planck Equations in a Bath and Channel from a Molecular Model.  Physical Review E, 64 (2001) 036116.
B. Nadler, T. Naeh, Z. Schuss (2001). The Stationary Arrival Process of Independent Diffusers from a Continuum to an Absorbing Boundary is Poissonian.  SIAM Journal on Applied Mathematics, 62(2) (2001), pp. 433-447.

1999

B. Nadler, G. Fibich, S. Lev-Yehudi, Daniel Cohen-Or (1999). A Qualitative and Quantitative Visibility Analysis in Urban Scenes.  Computers and Graphics, 23(5):655-666 (1999).