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A. Shojaie

56 papers hereh-index 374.8k citations150 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author4
  • middle author15
  • last author36

Across the 56 of 56 papers where every author was matched, so the position is known.

fields
  • stat.ME37
  • stat.ML13
  • cs.LG2
  • math.ST2
  • math.OC1
  • stat.AP1
same name
  • A. Shojaie — 2 papers, h 1
  • A. Shojaie — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20092026
most citedNeural Granger Causality

284 citations · 587 across the 49 of their papers we have counts for

collaborators
Showing 2016Show all

4 papers · 1 filter

stat.ME2016★ 8 cited

Nonparametric Regression with Adaptive Truncation via a Convex Hierarchical Penalty

Asad Haris, Ali Shojaie, Noah Simon

We consider the problem of non-parametric regression with a potentially large number of covariates. We propose a convex, penalized estimation framework that is particularly well-su…

stat.ME2016

Network Reconstruction From High Dimensional Ordinary Differential Equations

Shizhe Chen, Ali Shojaie, Daniela M. Witten

We consider the task of learning a dynamical system from high-dimensional time-course data. For instance, we might wish to estimate a gene regulatory network from gene expression d…

stat.ME2016★ 8 cited

A Generalized Benjamini-Hochberg Procedure for Multivariate Hypothesis Testing

Kasra Alishahi, Ahmad Reza Ehyaei, Ali Shojaie

The introduction of the false discovery rate (FDR) by Benjamini and Hochberg has spurred a great interest in developing methodologies to control the FDR in various settings. The ma…

stat.ML2016★ 1 cited

Joint Estimation of Precision Matrices in Heterogeneous Populations

Takumi Saegusa, Ali Shojaie

We introduce a general framework for estimation of inverse covariance, or precision, matrices from heterogeneous populations. The proposed framework uses a Laplacian shrinkage pena…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.