Mutual information for symmetric rank-one matrix estimation: a proof of the replica formula
Barbier, J., Dia, M., Macris, N., Krzakala, F., Lesieur, T. and Zdeborová, L. (2016) · 2016
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Asymptotic mutual information for the balanced binary stochastic block model
Deshpande, Y., Abbe, E. and Montanari, A. (2016) · 2016
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High dimensional robust M-estimation: asymptotic variance via approximate message passing
Donoho, D. and Montanari, A. (2016) · 2016
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Phase transitions and sample complexity in Bayes optimal matrix factorization
Kabashima, Y., Krzakala, F., Mézard, M., Sakata, A. and Zdeborová, L. (2016) · 2016
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Non-negative principal component analysis: Message passing algorithms and sharp asymptotics
Montanari, A. and Richard, E. (2016) · 2016
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A theory of solving TAP equations for Ising models with general invariant random matrices
Opper, M., Çakmak, B. and Winther, O. (2016) · 2016
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Fixed points of generalized approximate message passing with arbitrary matrices
Rangan, S., Schniter, P., Riegler, E., Fletcher, A. K. and Cevher, V. (2016) · 2016
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Vector approximate message passing for the generalized linear model
Schniter, P., Rangan, S. and Fletcher, A. K. (2016) · 2016
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SLOPE is adaptive to unknown sparsity and asymptotically minimax
Su, W. and Candès, E. (2016) · 2016
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Statistical physics of inference: thresholds and algorithms
Zdeborová, L. and Krzakala, F. (2016) · 2016
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Approximate message-passing decoder and capacity achieving sparse superposition codes
Barbier, J. and Krzakala, F. (2017) · 2017
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The LASSO risk for Gaussian matrices
Bayati, M. and Montanari, A. (2012) · 2017
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Constrained low-rank matrix estimation: phase transitions, approximate message passing and applications
Lesieur, T., Krzakala, F. and Zdeborová, L. (2017) · 2017
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Learned D-AMP: Principled neural network based compressive image recovery
Metzler, C., Mousavi, A. and Baraniuk, R. (2017) · 2017
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Capacity-achieving sparse superposition codes via approximate message passing decoding
Rush, C., Greig, A. and Venkataramanan, R. (2017) · 2017
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False discoveries occur early on the LASSO path
Su, W., Bogdan, M. and Candès, E. (2017) · 2017
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The likelihood ratio test in high-dimensional logistic regression is asymptotically a rescaled chi-square
Sur, P., Chen, Y. and Candès, E. J. (2017) · 2017
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SLOPE meets LASSO: improved oracle bounds and optimality
Bellec, P. C., Lecué, G. and Tsybakov, A. B. (2018) · 2018
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Shrinkage Estimation
Fourdrinier, D., Strawderman, W. E. and Wells, M. T. (2018) · 2018
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PCA in high dimensions: an orientation
Johnstone, I. M. and Paul, D. (2018) · 2018
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Kuchibhotla, A. and Chakrabortty A. (2018). Moving beyond sub-Gaussianity in high-dimensional statistics: applications in covariance estimation and linear regression. Available at https://arxiv.org/pdf/1804.02605.pdf
Original
2018
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The distribution of the Lasso: uniform control over sparse balls and adaptive parameter tuning
Original
Miolane, L. and Montanari, A. (2018) · 2018
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Consistent parameter estimation for LASSO and approximate message passing
Mousavi, A., Maleki, A., Baraniuk, R. G. (2018) · 2018
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Optimality and sub-optimality of PCA I: Spiked random matrix models
Perry, A., Wein, A. S., Bandeira, A. S. and Moitra, A. (2018) · 2018
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Iterative reconstruction of rank-one matrices in noise
Rangan, S. and Fletcher, A. K. (2018) · 2018
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IEEE Trans. Inf. Theory , 64
Rush, C. and Venkataramanan, R. (2018). Finite sample analysis of approximate message passing algorithms · 2018
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IEEE Trans. Inf. Theory , 64
Thrampoulidis, C., Abbasi, E. and Hassibi, B. (2018). Precise error analysis of regularized M M -estimators in high dimensions · 2018
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Optimal errors and phase transitions in high-dimensional generalized linear models
Barbier, J., Krzakala, F., Macris, N., Miolane, L., and Zdeborová, L. (2019) · 2019
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Memory-free dynamics for the Thouless–Anderson–Palmer equations of Ising models with arbitrary rotation-invariant ensembles of random coupling matrices
Çakmak, B. and Opper, M. (2019) · 2019
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Fundamental limits of symmetric low-rank matrix estimation
Lelarge, M. and Miolane, L. (2019) · 2019
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Optimization-based AMP for phase retrieval: the impact of initialization and ℓ 2 \ell_{2} regularization
Ma, J., Xu, J. and Maleki, A. (2019) · 2019
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Analysis of approximate message passing with non-separable denoisers and Markov random field priors
Ma, Y., Rush, C. and Baron, D. (2019) · 2019
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Asymptotics of MAP inference in deep networks
Pandit, P., Sahraee, M., Rangan, S. and Fletcher, A. K. (2019) · 2019
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The replica-symmetric prediction for random linear estimation with Gaussian matrices is exact
Reeves, G. and Pfister, H. D. (2019) · 2019
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State evolution for approximate message passing with non-separable functions
Berthier, R., Montanari, A. and Nguyen, P.-M. (2020) · 2020
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Ann. Statist. , 48
Candès, E. J. and Sur, P. (2020). The phase transition for the existence of the maximum likelihood estimate in high-dimensional logistic regression · 2020
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The estimation error of general first order methods
Celentano, M., Montanari, A. and Wu, Y. (2020) · 2020
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Generalization error of generalized linear models in high dimensions
Emami, M., Sahraee-Ardakan, M., Pandit, P., Rangan, S. and Fletcher, A. K. (2020) · 2020
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Sparse principal component analysis via axis-aligned random projections
Gataric, M., Wang, T. and Samworth, R. J. (2020) · 2020
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Proc. Mach. Learn. Res. , 130
Mondelli, M. and Venkataramanan, R. (2020). Approximate message passing with spectral initialization for generalized linear models · 2020
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Springer–Verlag, New York
Panaretos, V. M. and Zemel, Y. (2020). An Invitation to Statistics in Wasserstein Space · 2020
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Inference with deep generative priors in high dimensions
Pandit, P., Sahraee-Ardakan, M., Rangan, S., Schniter, P. and Fletcher, A. K. (2020) · 2020
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A simple derivation of AMP and its state evolution via first-order cancellation
Schniter, P. (2020) · 2020
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Rigorous dynamics of expectation-propagation-based signal recovery from unitarily invariant measurements
Takeuchi, K. (2020) · 2020
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Algorithmic analysis and statistical estimation of SLOPE via approximate message passing
Bu, Z., Klusowski, J., Rush, C. and Su, W. (2021) · 2021
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Universality of approximate message passing algorithms
Chen, W-K. and Lam, W-K. (2021) · 2021
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Bounding distributional errors via density ratios
Dümbgen, L., Samworth, R. J. and Wellner, J. A. (2021) · 2021
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Estimation of low-rank matrices via approximate message passing
Montanari, A. and Venkataramanan, R. (2021) · 2021
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Orthogonal AMP
Ma, J. and Ping, L. (2017) · 2033
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