676 citations · 1k across the 35 of their papers we have counts for
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Prediction Sets for High-Dimensional Mixture of Experts Models
Adel Javanmard, Simeng Shao, Jacob Bien
Large datasets make it possible to build predictive models that can capture heterogenous relationships between the response variable and features. The mixture of high-dimensional l…
Near-Optimal Procedures for Model Discrimination with Non-Disclosure Properties
Dmitrii M. Ostrovskii, Mohamed Ndaoud, Adel Javanmard +1
Let be the population risk minimizers associated to some loss and two distributions $\mathbb{P}_0,\mat…
Analysis of a Two-Layer Neural Network via Displacement Convexity
Adel Javanmard, Marco Mondelli, Andrea Montanari
Fitting a function by using linear combinations of a large number of `simple' components is one of the most fruitful ideas in statistical learning. This idea lies at the core o…
A Flexible Framework for Hypothesis Testing in High-dimensions
Adel Javanmard, Jason D. Lee
Hypothesis testing in the linear regression model is a fundamental statistical problem. We consider linear regression in the high-dimensional regime where the number of parameters…
Online Rules for Control of False Discovery Rate and False Discovery Exceedance
Adel Javanmard, Andrea Montanari
Multiple hypothesis testing is a core problem in statistical inference and arises in almost every scientific field. Given a set of null hypotheses $\mathcal{H}(n) = (H_1,\dotsc, H_…
De-biasing the Lasso: Optimal Sample Size for Gaussian Designs
Adel Javanmard, Andrea Montanari
Performing statistical inference in high-dimension is an outstanding challenge. A major source of difficulty is the absence of precise information on the distribution of high-dimen…
Nearly Optimal Sample Size in Hypothesis Testing for High-Dimensional Regression
Adel Javanmard, Andrea Montanari
We consider the problem of fitting the parameters of a high-dimensional linear regression model. In the regime where the number of parameters is comparable to or exceeds the sa…
Model Selection for High-Dimensional Regression under the Generalized Irrepresentability Condition
Adel Javanmard, Andrea Montanari
In the high-dimensional regression model a response variable is linearly related to covariates, but the sample size is smaller than . We assume that only a small subset…
The minimax risk of truncated series estimators for symmetric convex polytopes
Adel Javanmard, Li Zhang
We study the optimality of the minimax risk of truncated series estimators for symmetric convex polytopes. We show that the optimal truncated series estimator is within …
Localization from Incomplete Noisy Distance Measurements
Adel Javanmard, Andrea Montanari
We consider the problem of positioning a cloud of points in the Euclidean space , using noisy measurements of a subset of pairwise distances. This task has applicatio…