activity
20172023
most citedExponential tail bounds and Large Deviation Principle for Heavy-Tailed U-Statistics

1 citations · 2 across the 5 of their papers we have counts for

collaborators

6 papers

math.PR2023★ 1 cited

Exponential tail bounds and Large Deviation Principle for Heavy-Tailed U-Statistics

Milad Bakhshizadeh

We study deviation of U-statistics when samples have heavy-tailed distribution so the kernel of the U-statistic does not have bounded exponential moments at any positive point. We…

cs.CG2020

A practical algorithm to calculate Cap Discrepancy

Milad Bakhshizadeh, Ali Kamalinejad, Mina Latifi

Uniform distribution of the points has been of interest to researchers for a long time and has applications in different areas of Mathematics and Computer Science. One of the well-…

math.ST2020

Universality of Linearized Message Passing for Phase Retrieval with Structured Sensing Matrices

Rishabh Dudeja, Milad Bakhshizadeh

In the phase retrieval problem one seeks to recover an unknown dimensional signal vector from measurements of the form , whe…

math.PR2020★ 1 cited

Sharp Concentration Results for Heavy-Tailed Distributions

Milad Bakhshizadeh, Arian Maleki, Victor H. de la Pena

We obtain concentration and large deviation for the sums of independent and identically distributed random variables with heavy-tailed distributions. Our concentration results are…

cs.IT2019

Analysis of Spectral Methods for Phase Retrieval with Random Orthogonal Matrices

Rishabh Dudeja, Milad Bakhshizadeh, Junjie Ma +1

Phase retrieval refers to algorithmic methods for recovering a signal from its phaseless measurements. Local search algorithms that work directly on the non-convex formulation of t…

cs.IT2017

Using Black-box Compression Algorithms for Phase Retrieval

Milad Bakhshizadeh, Arian Maleki, Shirin Jalali

Compressive phase retrieval refers to the problem of recovering a structured -dimensional complex-valued vector from its phase-less under-determined linear measurements. The non…