# Publications by Type: Conference Paper

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Construction of optimal spectral methods in phase retrieval,” in Mathematical and Scientific Machine Learning, 2021. arXiv:2012.04524 [cs.IT]Abstract

, “ Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization,” in Conference on Neural Information Processing Systems (NeurIPS), 2020. arXiv:2006.06560 [stat.ML]Abstract

, “ The role of regularization in classification of high-dimensional noisy Gaussian mixture,” in International Conference on Machine Learning (ICML), 2020. arXiv:2002.11544 [stat.ML]Abstract

, “ A Solvable High-Dimensional Model of GAN,” in Proc. Thirty-third Conference on Neural Information Processing Systems (NeurIPS), 2019. arXiv:1805.08349 [cs.LG]Abstract

, “ Generalized Approximate Survey Propagation for High-Dimensional Estimation,” in Proc. International Conference on Machine Learning (ICML), 2019. arXiv:1905.05313 [cond-mat.dis-nn]Abstract

, “ Asymptotics and optimal designs of SLOPE for sparse linear regression,” in Prof. International Symposium on Information Theory (ISIT), 2019. Longer version with full technical detailsAbstract

, “ Phase Retrieval via Linear Programming: Fundamental Limits and Algorithmic Improvements,” in 55th Annual Allerton Conference on Communication, Control, and Computing, 2017. arXiv:1710.05234 [cs.IT]Abstract

, “ The Scaling Limit of High-Dimensional Online Independent Component Analysis,” in Conference on Neural Information Processing Systems (NIPS), 2017.Abstract nips_2017.pdf

, “*(acceptance rate: 112/3240 = 3.5%)*

**Spotlight paper** Fundamental Limits of PhaseMax for Phase Retrieval: A Replica Analysis,” in the 7th IEEE Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2017. arXiv:1708.03355Abstract

, “This paper won the Best Student Paper Award (First Prize) at the 2017 IEEE CAMSAP Workshop.

The predictions made in this paper via the non-rigorous replica method has since been rigorously established in our latest work.

Spectral Initialization for Nonconvex Estimation: High-Dimensional Limit and Phase Transitions,” in IEEE International Symposium on Information Theory (ISIT), 2017.Abstract sp_init_isit.pdf

, “ Subspace Estimation from Incomplete Observations: A Precise High-Dimensional Analysis,” in Signal Processing with Adaptive Structured Representatives (SPARS) Workshop, 2017.Abstract sparse17_ode.pdf

, “ Online Learning for Sparse PCA in High Dimensions: Exact Dynamics and Phase Transitions,” in IEEE Information Theory Workshop (ITW), 2016.Abstract spca.pdf

, “ ProSparse denoise: Prony's based sparsity pattern recovery in the presence of noise,” in Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016.

, “ Phase Retrieval Using Iterative Projections: Dynamics in the Large Systems Limit,” in Allerton Conference on Communications, Control, and Computing, 2015.Abstract phase_dynamics.pdf

, “ Understanding symmetric smoothing filters via Gaussian mixtures,” in IEEE International Conference on Image Processing, 2015.

, “ Sparsity according to Prony, Average Performance Analysis,” in Signal Processing with Adaptive Sparse Structured Representations (SPARS) Workshop, Cambridge, England, 2015. 2015_spars.pdf

, “ Optimal hypothesis testing with combinatorial structure: Detecting random walks on graphs,” in Proc. of Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, 2014.Abstract

, “ Efficient image reconstruction for gigapixel quantum image sensors,” in IEEE Global Conference on Signal and Information Processing (GlobalSIP), Atlanta, GA, 2014.Abstract qis_image_reconstruction.pdf

, “ Randomized Kaczmarz algorithms: Exact MSE analysis and optimal sampling probabilities,” in IEEE Global Conference on Signal and Information Processing (GlobalSIP), Atlanta, GA, 2014.Abstract randkac_globalsip14.pdf

, “(This paper received the **Best Student Paper Award** of GlobalSIP)