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收听数0性别保密听众数45最后登录2025-9-19QQUID2265阅读权限40帖子1416精华0在线时间391 小时注册时间2012-12-24
 
 
 科研币66 速递币12 娱乐币214 文献值40 资源值0 贡献值0 
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| 本帖最后由 colimae 于 2021-5-11 20:01 编辑 
 InfInf(2012-2020):
 2012.
 Dear Information and Inference Reader
 Calderbank, Donoho, Shawe-Taylor, Tanner
 he masked sample covariance estimator: an analysis using matrix concentration inequalities
 Richard Y. Chen, Alex Gittens, Joel A. Tropp
 Eigenvector synchronization, graph rigidity and the molecule problem
 Mihai Cucuringu, Amit Singer, David Cowburn
 Semi-supervised single- and multi-domain regression with multi-domain training
 Michaeli, Eldar, Sapiro
 2013.
 Approximation of points on low-dimensional manifolds via random linear projections
 Mark A. Iwen, Mauro Maggioni
 Compressive principal component pursuit
 John Wright, Arvind Ganesh, Kerui Min, Yi Ma
 Tangent space estimation for smooth embeddings of Riemannian manifolds
 Hemant Tyagi, Elif Vural, Pascal Frossard
 State evolution for general approximate message passing algorithms, with applications to spatial coupling
 Javanmard, Montanari
 Exact and stable recovery of rotations for robust synchronization
 Lanhui Wang, Amit Singer
 2014.
 Cramér–Rao bounds for synchronization of rotations
 Nicolas Boumal, Amit Singer, P.-A. Absil, Vincent D. Blondel
 Sigma–Delta quantization of sub-Gaussian frame expansions and its application to compressed sensing
 Felix Krahmer, Rayan Saab, Özgür Yilmaz
 Higher order Sobol' indices........................Art B. Owen, Josef Dick, Su Chen
 Phase retrieval from power spectra of masked signals
 Afonso S. Bandeira, Yutong Chen, Dustin G. Mixon
 Finite sample posterior concentration in high-dimensional regression
 Nate Strawn, Artin Armagan, Rayan Saab, Lawrence Carin, David Dunson
 Non-asymptotic analysis of tangent space perturbation
 Daniel N. Kaslovsky, François G. Meyer
 1-Bit matrix completion
 Davenport, Plan, van den Berg, Wootters
 Living on the edge: phase transitions in convex programs with random data
 Dennis Amelunxen, Martin Lotz, Michael B. McCoy, Joel A. Tropp
 Scaling law for recovering the sparsest element in a subspace
 Laurent Demanet, Paul Hand
 Persistent homology transform for modeling shapes and surfaces
 Katharine Turner, Sayan Mukherjee, Doug M. Boyer
 Deterministic Bayesian information fusion and the analysis of its performance
 Gaurav Thakur
 2015.
 Graph connection Laplacian and random matrices with random blocks
 El Karoui, Hau-tieng Wu
 Disparity and optical flow partitioning using extended Potts priors
 Xiaohao Cai, Jan Henrik Fitschen, Mila Nikolova, Gabriele Steidl, Martin Storath
 On spectral properties for graph matching and graph isomorphism problems
 Fiori, Sapiro
 Compressed subspace matching on the continuum
 Mantzel, Romberg
 Riemannian metrics for neural networks I: feedforward networks
 Riemannian metrics for neural networks II: recurrent networks and learning symbolic data sequences
 Yann Ollivier
 Tensor sparsification via a bound on the spectral norm of random tensors
 Nam H. Nguyen, Petros Drineas, Trac D. Tran
 Model selection with low complexity priors
 Samuel Vaiter, Mohammad Golbabaee, Jalal Fadili, Gabriel Peyré
 CGIHT: conjugate gradient iterative hard thresholding for compressed sensing and matrix completion
 Jeffrey D. Blanchard, Jared Tanner, Ke Wei
 Guarantees of total variation minimization for signal recovery
 Jian-Feng Cai, Weiyu Xu
 Replication procedure for grouped Sobol' indices estimation in dependent uncertainty spaces
 Laurent Gilquin, Clémentine Prieur, Elise Arnaud
 ERRATUM--------Finite sample posterior concentration in high-dimensional regression
 N. Strawn, A. Armagan, R. Saab, L. Carin, D. Dunson
 2016.
 Robust subspace recovery by Tyler's M-estimator
 Teng Zhang
 Super-resolution radar.......................Heckel, Morgenshtern, Soltanolkotabi
 A null-space-based weighted l1 minimization approach to compressed sensing
 Shenglong Zhou, Naihua Xiu, Yingnan Wang, Lingchen Kong, Hou-Duo Qi
 Super-resolution of point sources via convex programming
 Carlos Fernandez-Granda
 Detecting the large entries of a sparse covariance matrix in sub-quadratic time
 Ofer Shwartz, Boaz Nadler
 Near-optimal estimation of simultaneously sparse and low-rank matrices from nested linear measurements
 Bahmani, Romberg
 Total variation regularization on Riemannian manifolds by iteratively reweighted minimization
 Philipp Grohs, Markus Sprecher
 On the optimality of averaging in distributed statistical learning
 Jonathan D. Rosenblatt, Boaz Nadler
 Stable low-rank matrix recovery via null space properties
 Maryia Kabanava, Richard Kueng, Holger Rauhut, Ulrich Terstiege
 2016s.
 Special issue: Deep learning....................Francis Bach, Tomaso Poggio
 Deep Haar scattering networks
 Xiuyuan Cheng, Xu Chen, Stéphane Mallat
 On invariance and selectivity in representation learning
 Fabio Anselmi, Lorenzo Rosasco, Tomaso Poggio
 A theoretical framework for deep transfer learning
 Tomer Galanti, Lior Wolf, Tamir Hazan
 GSNs: generative stochastic networks
 Guillaume Alain, Yoshua Bengio, Li Yao, Jason Yosinski,
 Éric Thibodeau-Laufer, Saizheng Zhang,  Pascal Vincent
 2017.
 
 2018.
 Superresolution without separation
 Geoffrey Schiebinger, Elina Robeva, Benjamin Recht
 Quantized minimax estimation over Sobolev ellipsoids
 Yuancheng Zhu, John Lafferty
 One-bit compressive sensing of dictionary-sparse signals
 Baraniuk, Foucart, Needell, Plan, Wootters
 Demixing sines and spikes: Robust spectral super-resolution in the presence of outliers
 Carlos Fernandez-Granda, Gongguo Tang, Xiaodong Wang, Le Zheng
 When is non-trivial estimation possible for graphons and stochastic block models?‡
 Audra McMillan, Adam Smith
 Algorithms for learning sparse additive models with interactions in high dimensions*
 Hemant Tyagi, Anastasios Kyrillidis, Bernd Gärtner, Andreas Krause
 Weighted mining of massive collections of P-values by convex optimization
 Edgar Dobriban
 Fast, robust and non-convex subspace recoverygraphic
 Gilad Lerman, Tyler Maunu
 Universality laws for randomized dimension reduction, with applications
 Samet Oymak, Joel A Tropp
 Sketching for large-scale learning of mixture models
 Nicolas Keriven, Anthony Bourrier, Rémi Gribonval, Patrick Pérez
 Gaussian approximation of general non-parametric posterior distributions
 Zuofeng Shang, Guang Cheng
 Iterative reconstruction of rank-one matrices in noise
 Alyson K Fletcher, Sundeep Rangan
 A convex program for mixed linear regression with a recovery guarantee for well-separated datagraphic
 Paul Hand, Babhru Joshi
 MC2: a two-phase algorithm for leveraged matrix completion
 Armin Eftekhari, Michael B Wakin, Rachel A Ward
 New approach to Bayesian high-dimensional linear regression
 Shirin Jalali, Arian Maleki
 Structured sampling and fast reconstruction of smooth graph signals
 Gilles Puy, Patrick Pérez
 A spectral assignment approach for the graph isomorphism problemgraphic
 Stefan Klus, Tuhin Sahai
 Isometric sketching of any set via the Restricted Isometry Property
 Oymak, Recht, Soltanolkotabi
 Conditional expectation estimation through attributable components
 Esteban G Tabak, Giulio Trigila
 Gradient descent with non-convex constraints: local concavity determines convergencegraphic
 Rina Foygel Barber, Wooseok Ha
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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