- Curvelets A Surprisingly Effective Nonadaptive Representation For Objects with Edges
- Continuous Curvelet Transform: I. Resolution of the Wavefront Set
- NESTA: A FAST AND ACCURATE FIRST-ORDER METHOD FOR SPARSE RECOVERY
- A Fast Butterfly Algorithm for the Computation of Fourier Integral Operators
- 706 IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 12, NO. 6, JUNE 2003 Gray and Color Image Contrast Enhancement
- Astronomy & Astrophysics manuscript no. November 5, 2002 Astronomical Image Representation by the Curvelet Transform
- Robust Uncertainty Principles: Exact Signal Reconstruction from Highly Incomplete
- Continuous Curvelet Transform: II. Discretization and Frames
- Ridgelets: a key to higher-dimensional intermittency?
- Curvelets and Fourier Integral Operators Emmanuel Cand`es , Laurent Demanet
- The Restricted Isometry Property and Its Implications for Compressed Sensing
- Dense Error Correction for Low-Rank Matrices via Principal Component Pursuit
- Near-ideal model selection by 1 minimization Emmanuel J. Cand`es and Yaniv Plan
- The Curvelet Representation of Wave Propagators is Optimally Sparse
- New Tight Frames of Curvelets and Optimal Representations of Objects with C2
- Compressive sampling Emamnuel J. Cands
- Submitted to the Annals of Statistics REJOINDER: THE DANTZIG SELECTOR: STATISTICAL
- New Multiscale Transforms, Minimum Total Variation Synthesis
- The Power of Convex Relaxation: Near-Optimal Matrix Completion
- arXiv:1001.3209v1[math.ST]19Jan2010 Detection of an Anomalous Cluster in a Network
- The Dantzig selector: statistical estimation when p is much larger than n
- A Probabilistic and RIPless Theory of Compressed Sensing Emmanuel J. Cand`es1 and Yaniv Plan2
- Sparsity and Incoherence in Compressive Sampling Emmanuel Cand`es
- arXiv:1104.5246v1[cs.IT]27Apr2011 How well can we estimate a sparse vector?
- Enhancing Sparsity by Reweighted 1 Minimization Emmanuel J. Cand`es
- Ridgelets: Estimating with Ridge Functions Emmanuel J. Cand`es
- Detecting Highly Oscillatory Signals by Chirplet Path Pursuit Emmanuel J. Cand`es
- Quantitative Robust Uncertainty Principles and Optimally Sparse Decompositions
- Multiresolution Representation, and Scaling Laws Emmanuel J. Cand`es and David L. Donoho
- Fast Computation of Fourier Integral Operators Emmanuel Cand`es, Laurent Demanet and Lexing Ying
- Compressed Sensing with Coherent and Redundant Dictionaries Emmanuel J. Cand`es1
- Harmonic Analysis of Neural Networks Emmanuel J. Cand`es
- Matrix Completion with Noise Emmanuel J. Cand`es and Yaniv Plan
- Ridgelets and the Representation of Mutilated Sobolev Functions Emmanuel J. Candes
- Near Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
- Recovering Edges in Ill-Posed Inverse Problems
- Phase Retrieval via Matrix Completion Emmanuel J. Cand`es
- Multiscale Chirplets and Near-Optimal Recovery of Chirps Emmanuel J. Cand`es
- Quantitative Robust Uncertainty Principles and Optimally Sparse Decompositions
- The Curvelet Transform for Image Denoising Jean-Luc Starck
- Error Correction via Linear Programming Emmanuel Candes
- Highly Robust Error Correction by Convex Programming Emmanuel J. Cand`es and Paige A. Randall
- Global Testing under Sparse Alternatives: ANOVA, Multiple Comparisons and the Higher Criticism
- Curvelets and Reconstruction of Images from Noisy Radon Data
- The Phase Flow Method Lexing Ying and Emmanuel J. Cand`es
- Ridgelets and Their Derivatives: Representation of Images with Edges
- Fast Geodesics Computation with the Phase Flow Method Lexing Ying and Emmanuel J. Cand`es
- Acta Numerica (2006), pp. 169 c Cambridge University Press, 2006 DOI: 10.1017/S0962492904000xxx Printed in the United Kingdom
- The Dantzig selector: statistical estimation when p is much larger than n
- Robust Principal Component Analysis? Emmanuel J. Cand`es1,2
- Robust Uncertainty Principles: Exact Signal Reconstruction from Highly Incomplete
- Searching for a Trail of Evidence in a Maze Ery Arias-Castro1
- New Ties between Computational Harmonic Analysis and Approximation Theory
- A SINGULAR VALUE THRESHOLDING ALGORITHM FOR MATRIX COMPLETION
- Simple Bounds for Low-complexity Model Reconstruction Emmanuel Cand`es and Benjamin Recht
- Recovering Edges in Ill-Posed Inverse Problems
- Curvelets and Curvilinear Integrals Emmanuel J. Cand es & David L. Donoho
- THEORY AND APPLICATIONS A DISSERTATION
- Very High Quality Image Restoration by Combining Wavelets and Curvelets
- Multiresolution Representation, and Scaling Laws Emmanuel J. Cand es and David L. Donoho
- Ridgelets: a key to higherdimensional intermittency?
- Digital Implementation of Ridgelet Packets A.G. Flesia, H. HelOr
- Curvelets --A Surprisingly E#ective Nonadaptive Representation For Objects with Edges
- New Multiscale Transforms, Minimum Total Variation Synthesis
- The Curvelet Transform for Image Denoising Jean-Luc Starck , Emmanuel J. Cand es y , David L. Donoho z
- New Ties between Computational Harmonic Analysis and Approximation Theory
- Ridgelets and the Representation of Mutilated Sobolev Functions Emmanuel J. Candes
- Harmonic Analysis of Neural Networks Emmanuel J. Cand es
- Monoscale Ridgelets for the Representation of Images with Edges Emmanuel J. Cand es
- Ridgelets and Their Derivatives: Representation of Images with Edges
- Curvelets and Reconstruction of Images from Noisy Radon Data
- Ridgelets: Estimating with Ridge Functions Emmanuel J. Cand es
- Curvelets and Curvilinear Integrals Emmanuel J. Cand`es & David L. Donoho
- Fast Discrete Curvelet Transforms Emmanuel Cand`es
- Templates for Convex Cone Problems with Applications to Sparse Signal Recovery
- 1-magic : Recovery of Sparse Signals via Convex Programming
- "People Hearing Without Listening:" An Introduction To Compressive Sampling
- Monoscale Ridgelets for the Representation of Images with Edges Emmanuel J. Cand`es
- Tight Oracle Bounds for Low-rank Matrix Recovery from a Minimal Number of Random Measurements
- Near Optimal Signal Recovery From Random Projections: Universal Encoding Strategies?
- On the Fundamental Limits of Adaptive Sensing Ery Arias-Castro
- Compressive Fluorescence Microscopy for Biological and Hyperspectral Imaging
- PhaseLift: Exact and Stable Signal Recovery from Magnitude Measurements via Convex Programming
- A Geometric Analysis of Subspace Clustering with Outliers Mahdi Soltanolkotabi1 and Emmanuel J. Cand`es2
