S. Mendelson

发表

Empirical minimization

P. Bartlett, S. Mendelson, 2006 .

Learning subgaussian classes : Upper and minimax bounds

S. Mendelson, G. Lecu'e, 2013, 1305.4825.

Local Rademacher complexities

P. Bartlett, O. Bousquet, S. Mendelson, 2005, math/0508275.

Performance of empirical risk minimization in linear aggregation

S. Mendelson, G. Lecu'e, 2014, 1402.5763.

Entropy and the combinatorial dimension

S. Mendelson, R. Vershynin, 2002, math/0203275.

Sub-Gaussian estimators of the mean of a random vector

G. Lugosi, S. Mendelson, 2017, The Annals of Statistics.

Robust covariance estimation under $L_{4}-L_{2}$ norm equivalence

S. Mendelson, Nikita Zhivotovskiy, 2018, The Annals of Statistics.

Risk minimization by median-of-means tournaments

G. Lugosi, S. Mendelson, 2016, Journal of the European Mathematical Society.

Robust multivariate mean estimation: The optimality of trimmed mean

G. Lugosi, S. Mendelson, 2019, The Annals of Statistics.

On weakly bounded empirical processes

S. Mendelson, 2005, math/0512554.

Reconstruction and Subgaussian Operators in Asymptotic Geometric Analysis

S. Mendelson, A. Pajor, N. Tomczak-Jaegermann, 2007 .

Uniform Uncertainty Principle for Bernoulli and Subgaussian Ensembles

S. Mendelson, A. Pajor, N. Tomczak-Jaegermann, 2006, math/0608665.

Minimax rate of convergence and the performance of empirical risk minimization in phase recovery

S. Mendelson, Guillaume Lecué, 2015 .

Bounding the smallest singular value of a random matrix without concentration

V. Koltchinskii, S. Mendelson, 2013, 1312.3580.

Sparse recovery under weak moment assumptions

S. Mendelson, G. Lecu'e, 2014, 1401.2188.

Rademacher and Gaussian Complexities: Risk Bounds and Structural Results

Peter L. Bartlett, Shahar Mendelson, P. Bartlett, 2003, J. Mach. Learn. Res..

ℓ-norm and its Application to Learning Theory

S. Mendelson, 2001 .

Local Complexities for Empirical Risk Minimization

Peter L. Bartlett, Shahar Mendelson, Petra Philips, 2004, COLT.

Empirical processes and random projections

S. Mendelson, B. Klartag, 2005 .

Empirical Processes with a Bounded Ψ1 Diameter

S. Mendelson, 2010 .

Compressed sensing under weak moment assumptions

S. Mendelson, Guillaume Lecué, 2014 .

Learning without concentration for general loss functions

S. Mendelson, 2014, 1410.3192.

A remark on the diameter of random sections of convex bodies

S. Mendelson, 2013, 1312.3608.

Subspaces and Orthogonal Decompositions Generated by Bounded Orthogonal Systems

S. Mendelson, A. Pajor, N. Tomczak-Jaegermann, 2007 .

A Few Notes on Statistical Learning Theory

Shahar Mendelson, S. Mendelson, 2002, Machine Learning Summer School.

Regularization, sparse recovery, and median-of-means tournaments

G. Lugosi, S. Mendelson, 2017, Bernoulli.

Geometric Parameters in Learning Theory

S. Mendelson, 2004 .

Regularization in kernel learning

S. Mendelson, Joe Neeman, 2010, 1001.2094.

Near-optimal mean estimators with respect to general norms

G. Lugosi, S. Mendelson, 2018, Probability Theory and Related Fields.

Rademacher averages and phase transitions in Glivenko-Cantelli classes

Shahar Mendelson, S. Mendelson, 2002, IEEE Trans. Inf. Theory.

Sharper lower bounds on the performance of the empirical risk minimization algorithm

S. Mendelson, G. Lecu'e, 2011, 1102.4983.

Complexity measures of sign matrices

Nathan Linial, Gideon Schechtman, Adi Shraibman, 2007, Comb..

Localized Rademacher Complexities

Peter L. Bartlett, Shahar Mendelson, Olivier Bousquet, 2002, COLT.

Minimax rate of convergence and the performance of ERM in phase recovery

S. Mendelson, G. Lecu'e, 2013, 1311.5024.

Extending the small-ball method

S. Mendelson, 2017, 1709.00843.

Regularization and the small-ball method I: sparse recovery

S. Mendelson, G. Lecu'e, 2016, 1601.05584.

Mean Estimation and Regression Under Heavy-Tailed Distributions: A Survey

Shahar Mendelson, Gabor Lugosi, G. Lugosi, 2019, Found. Comput. Math..

An optimal unrestricted learning procedure

S. Mendelson, 2017, 1707.05342.

ℓ1-regularized linear regression: persistence and oracle inequalities

P. Bartlett, S. Mendelson, Joe Neeman, 2012 .

On the singular values of random matrices

S. Mendelson, G. Paouris, 2014 .

On singular values of matrices with independent rows

S. Mendelson, A. Pajor, 2006 .

Aggregation via empirical risk minimization

S. Mendelson, Guillaume Lecué, 2009 .

Lower Bounds for the Empirical Minimization Algorithm

Shahar Mendelson, S. Mendelson, 2008, IEEE Transactions on Information Theory.

Improving the sample complexity using global data

Shahar Mendelson, S. Mendelson, 2002, IEEE Trans. Inf. Theory.

On Multiplier Processes Under Weak Moment Assumptions

S. Mendelson, 2016, 1601.06523.

Majorizing measures and proportional subsets of bounded orthonormal systems

S. Mendelson, A. Pajor, N. Tomczak-Jaegermann, 2008, 0801.3556.

Geometric Parameters of Kernel Machines

Shahar Mendelson, S. Mendelson, 2002, COLT.

A probabilistic approach to the geometry of the ℓᵨⁿ-ball

S. Mendelson, A. Naor, O. Guédon, 2005, math/0503650.

Entropy, Combinatorial Dimensions and Random Averages

Shahar Mendelson, Roman Vershynin, S. Mendelson, 2002, COLT.

Phase Retrieval: Stability and Recovery Guarantees pdf

Yonina C. Eldar, Shahar Mendelson, S. Mendelson, 2012, ArXiv.

On generic chaining and the smallest singular value of random matrices with heavy tails

S. Mendelson, G. Paouris, 2011, 1108.3886.

Oracle inequalities and the isomorphic method

S. Mendelson, 2012 .

Reconstruction and subgaussian operators

S. Mendelson, A. Pajor, N. Tomczak-Jaegermann, 2005, math/0506239.

Noise Tolerant Learnability via the Dual Learning Problem

Naftali Tishby, S. Mendelson, S. Fine, 2007 .

A note on the richness of convex hulls of VC classes

G. Lugosi, V. Koltchinskii, S. Mendelson, 2003 .

Suprema of Chaos Processes and the Restricted Isometry Property pdf

Holger Rauhut, Shahar Mendelson, Felix Krahmer, 2012, ArXiv.

Learning without Concentration

Shahar Mendelson, S. Mendelson, 2014, COLT.

Necessary moment conditions for exact reconstruction via basis pursuit

S. Mendelson, G. Lecu'e, 2014, 1404.3116.

On aggregation for heavy-tailed classes

S. Mendelson, 2015, Probability Theory and Related Fields.

Reconstruction and subgaussian processes

S. Mendelson, A. Pajor, N. Tomczak-Jaegermann, 2005 .

On the optimality of the aggregate with exponential weights for low temperatures

S. Mendelson, G. Lecu'e, 2013, 1303.5180.

DISCREPANCY, CHAINING AND SUBGAUSSIAN PROCESSES BY SHAHAR MENDELSON

S. Mendelson, 2011 .

Discrepancy, chaining and subgaussian processes

S. Mendelson, 2011, 1104.1508.

F eb 2 02 0 Learning bounded subsets of L p

S. Mendelson, 2020 .

Multivariate mean estimation with direction-dependent accuracy

G. Lugosi, S. Mendelson, 2020, Journal of the European Mathematical Society.

Upper bounds on product and multiplier empirical processes

S. Mendelson, 2014, 1410.8003.

`local' vs. `global' parameters -- breaking the gaussian complexity barrier

Shahar Mendelson, S. Mendelson, 2015, 1504.02191.

Generalized dual Sudakov minoration via dimension-reduction—a program

Shahar Mendelson, Grigoris Paouris, Emanuel Milman, 2016, Studia Mathematica.

Remarks on the geometry of coordinate projections in ℝn

S. Mendelson, R. Vershynin, S. Mendelson, 2003, math/0306314.

A subgaussian embedding theorem

Shahar Mendelson, Nicole Tomczak-Jaegermann, S. Mendelson, 2008 .

Aggregation versus Empirical Risk Minimization

S. Mendelson, Guillaume Lecué, 2007 .

Embedding with a Lipschitz function

Shahar Mendelson, S. Mendelson, 2005 .

Concentration of the spectral norm of Erdős–Rényi random graphs

G. Lugosi, S. Mendelson, Nikita Zhivotovskiy, 2020 .

Concentration of the spectral norm of Erdo\H{o}s-R\'enyi random graphs

G. Lugosi, S. Mendelson, Nikita Zhivotovskiy, 2018, 1801.02157.

The Information Of Observations And Application For Active Learning With Uncertainty

Naftali Tishby, Shahar Mendelson, Shai Fine, 2001 .

Fe b 20 15 On aggregation for heavy-tailed classes

S. Mendelson, 2018 .

Dvoretzky Type Theorems for Subgaussian Coordinate Projections

S. Mendelson, 2014, 1410.6914.

62 39 v 1 1 3 Ju n 20 05 Reconstruction and subgaussian operators

S. Mendelson, A. Pajor, N. Tomczak-Jaegermann, 2005 .

Lipschitz representations of subsets of the cube

S. Mendelson, 2007 .

Discussion of "2004 IMS Medallion Lecture: Local Rademacher complexities and oracle inequalities in risk minimization" by V. Koltchinskii

P. Bartlett, S. Mendelson, 2007, 0708.0089.

Stable recovery and the coordinate small-ball behaviour of random vectors

S. Mendelson, G. Paouris, 2019, 1904.08532.

An isomorphic Dvoretzky-Milman Theorem using general random ensembles

S. Mendelson, 2020, Journal of Functional Analysis.

On the optimality of the empirical risk minimization procedure for the Convex aggregation problem

S. Mendelson, Guillaume Lecué, 2013 .

Statistical Sufficiency for Classes in Empirical L2 Spaces

Naftali Tishby, Shahar Mendelson, Naftali Tishby, 2000, COLT.

Empirical processes with bounded \psi_1 diameter

S. Mendelson, 2010, 1005.0816.

Entropy, dimension and the Elton-Pajor Theorem

S. Mendelson, R. Vershynin, 2002, math/0201048.

Local Rademacher complexities and oracle inequalities in risk minimization

Peter L. Bartlett, Shahar Mendelson, P. Bartlett, 2006 .

Local Rademacher complexities

P. Bartlett, O. Bousquet, S. Mendelson, 2005, math/0508275.

Local Rademacher complexities and oracle inequalities in risk minimization

P. Bartlett, S. Mendelson, 2006 .

Local Rademacher complexities

P. Bartlett, O. Bousquet, S. Mendelson, 2005, math/0508275.

The shattering dimension of sets of linear functionals

S. Mendelson, G. Schechtman, 2004, math/0410096.

Entropy and the combinatorial dimension

S. Mendelson, R. Vershynin, 2002, math/0203275.

On weakly bounded empirical processes

S. Mendelson, 2005, math/0512554.

Fast metric embedding into the Hamming cube

S. Mendelson, S. Dirksen, A. Stollenwerk, 2022, ArXiv.

Structure preservation via the Wasserstein distance

S. Mendelson, Daniel Bartl, 2022, 2209.07058.

Modified Empirical CLT's under only pre-Gaussian conditions

S. Mendelson, J. Zinn, 2006, math/0612703.

Reconstruction and subgaussian operators

S. Mendelson, A. Pajor, N. Tomczak-Jaegermann, 2005, math/0506239.

Entropy, dimension and the Elton-Pajor Theorem

S. Mendelson, R. Vershynin, 2002, math/0201048.

A probabilistic approach to the geometry of the ℓᵨⁿ-ball

S. Mendelson, A. Naor, O. Guédon, 2005, math/0503650.

Mean Estimation and Regression Under Heavy-Tailed Distributions: A Survey

G. Lugosi, S. Mendelson, 2019, Foundations of Computational Mathematics.

ℓ1-regularized linear regression: persistence and oracle inequalities

P. Bartlett, S. Mendelson, Joe Neeman, 2011, Probability Theory and Related Fields.

Learning without concentration for general loss functions

S. Mendelson, 2017, Probability Theory and Related Fields.

On aggregation for heavy-tailed classes

S. Mendelson, 2016, Probability Theory and Related Fields.

Near-optimal mean estimators with respect to general norms

G. Lugosi, S. Mendelson, 2019, Probability Theory and Related Fields.

NON-EXACT ORACLE INEQUALITIES FOR CLASSES WITH A SUBEXPONENTIAL ENVELOPE

S. Mendelson, Guillaume Lecué, 2012 .

Column normalization of a random measurement matrix

S. Mendelson, 2017, 1702.06278.

Regularization and the small-ball method II: complexity dependent error rates

Shahar Mendelson, Guillaume Lecué, S. Mendelson, 2016, J. Mach. Learn. Res..

On the Importance of Small Coordinate Projections

Shahar Mendelson, Petra Philips, S. Mendelson, 2004, J. Mach. Learn. Res..

Random Subclass Bounds

Shahar Mendelson, Petra Philips, S. Mendelson, 2003, COLT.

On the geometry of polytopes generated by heavy-tailed random vectors pdf

Holger Rauhut, Shahar Mendelson, Felix Krahmer, 2019, Communications in Contemporary Mathematics.

On the Geometry of Random Polytopes

Shahar Mendelson, S. Mendelson, 2019, Lecture Notes in Mathematics.

The Geometry of Random {-1,1}-Polytopes

Shahar Mendelson, Mark Rudelson, Alain Pajor, 2005, Discret. Comput. Geom..

Approximating the covariance ellipsoid pdf

Shahar Mendelson, S. Mendelson, 2018, Communications in Contemporary Mathematics.

An Unrestricted Learning Procedure

Shahar Mendelson, S. Mendelson, 2019, J. ACM.

Robust one-bit compressed sensing with non-Gaussian measurements pdf

Sjoerd Dirksen, Shahar Mendelson, S. Mendelson, 2018, ArXiv.

A pr 2 01 8 Approximating the covariance ellipsoid

S. Mendelson, 2018 .

General nonexact oracle inequalities for classes with a subexponential envelope

Shahar Mendelson, Guillaume Lecu'e, S. Mendelson, 2012, 1206.0871.

On the Limitations of Embedding Methods

Shahar Mendelson, S. Mendelson, 2005, COLT.

On the Size of Convex Hulls of Small Sets

Shahar Mendelson, S. Mendelson, 2002, J. Mach. Learn. Res..

Obtaining fast error rates in nonconvex situations

Shahar Mendelson, S. Mendelson, 2008, J. Complex..

Embedding with a Lipschitz function

Shahar Mendelson, S. Mendelson, 2005, Random Struct. Algorithms.

2 2 Ju n 20 03 Remarks on the Geometry of Coordinate Projections in

S. Mendelson, R. Vershynin, 2004 .

Extending the scope of the small-ball method

Shahar Mendelson, S. Mendelson, 2017, Studia Mathematica.

Advanced Lectures on Machine Learning

Alexander J. Smola, Shahar Mendelson, S. Mendelson, 2003, Lecture Notes in Computer Science.

Optimal Sample-Based Estimates of the Expectation of the Empirical Minimizer

Peter L. Bartlett, Shahar Mendelson, Petra Philips, 2005 .

Improved bounds for sparse recovery from subsampled random convolutions pdf

Holger Rauhut, Rachel Ward, Shahar Mendelson, 2016, The Annals of Applied Probability.

On the Performance of Kernel Classes

Shahar Mendelson, S. Mendelson, 2003, J. Mach. Learn. Res..

Applied and Computational Harmonic Analysis Phase Retrieval: Stability and Recovery Guarantees

Yonina C. Eldar, S. Mendelson, 2022 .

Minimax rate of convergence and the performance of empirical risk minimization in phase retrieval *

Shahar Mendelson, Guillaume Lecué, S. Mendelson, 2015 .

On Monte-Carlo methods in convex stochastic optimization

Shahar Mendelson, Daniel Bartl, S. Mendelson, 2021, The Annals of Applied Probability.

Random embeddings with an almost Gaussian distortion

S. Mendelson, Daniel Bartl, 2021, Advances in Mathematics.

Sharp estimates on random hyperplane tessellations pdf

Sjoerd Dirksen, Shahar Mendelson, Alexander Stollenwerk, 2022, SIAM Journal on Mathematics of Data Science.

Robust one-bit compressed sensing with partial circulant matrices pdf

Sjoerd Dirksen, Shahar Mendelson, S. Mendelson, 2018, The Annals of Applied Probability.

Non-Gaussian hyperplane tessellations and robust one-bit compressed sensing

Sjoerd Dirksen, Shahar Mendelson, S. Mendelson, 2018, Journal of the European Mathematical Society.

The restricted isometry property for random convolutions

S. Mendelson, H. Rauhut, F. Krahmer, 2013 .

Fitting an ellipsoid to a quadratic number of random points

S. Mendelson, A. Bandeira, Elliot Paquette, 2023, arXiv.org.

Learnability in Hilbert Spaces with Reproducing Kernels

Shahar Mendelson, S. Mendelson, 2002, J. Complex..

Phase Retrieval: Stability and Recovery Guarantees

Yonina C. Eldar, S. Mendelson, 2012, ArXiv.

Gaussian averages of interpolated bodies and applications to approximate reconstruction

Shahar Mendelson, Alexander E. Litvak, Alain Pajor, 2007, J. Approx. Theory.

A New On-Line Learning Model

Shahar Mendelson, S. Mendelson, 2001, Neural Computation.

Ellipsoid Approximation Using Random Vectors

Shahar Mendelson, Alain Pajor, S. Mendelson, 2005, COLT.

M ay 2 01 0 Empirical processes with a bounded ψ 1 diameter

S. Mendelson, 2010 .

ec 2 00 5 On Weakly Bounded Empirical Processes

S. Mendelson, 2008 .

Geometric aspects of functional analysis : Israel Seminar 2006-2010

Gideon Schechtman, Vitali Milman, S. Mendelson, 2012 .

Dvoretzky Type Theorems for Subgaussian Coordinate Projections

S. Mendelson, Shahar Mendelson, 2015, Journal of Theoretical Probability.

Empirical processes and unconditional log-concave measures

S. Mendelson, G. Paouris, 2011 .