← Search

Daniel Reichman

7 accepted papers

2025

The Computational Complexity of Counting Linear Regions in ReLU Neural Networks

NeurIPS 2025poster

An established measure of the expressive power of a given ReLU neural network is the number of linear regions into which it partitions the input space. There exist many different, non-equivalent definitions of what a linear region actually is. We systematically assess which papers use which definiti…

Cited by 0SourceScholar
2022

Size and depth of monotone neural networks: interpolation and approximation

NeurIPS 2022accept

Monotone functions and data sets arise in a variety of applications. We study the interpolation problem for monotone data sets: The input is a monotone data set with $n$ points, and the goal is to find a size and depth efficient monotone neural network with \emph{non negative parameters} and thresho…

2019

Cognitive model priors for predicting human decisions

ICML 2019oral

Human decision-making underlies all economic behavior. For the past four decades, human decision-making under uncertainty has continued to be explained by theoretical models based on prospect theory, a framework that was awarded the Nobel Prize in Economic Sciences. However, theoretical models of th…

Cited by 127SourcePDFScholar
2018

Inference in Sparse Graphs with Pairwise Measurements and Side Information

AISTATS 2018poster

We consider the statistical problem of recovering a hidden "ground truth" binary labeling for the vertices of a graph up to low Hamming error from noisy edge and vertex measurements. We present new algorithms and a sharp finite-sample analysis for this problem on trees and sparse graphs with poor e…

Cited by 0SourcePDFScholar
2017

A graph-theoretic approach to multitasking

NeurIPS 2017oral

A key feature of neural network architectures is their ability to support the simultaneous interaction among large numbers of units in the learning and processing of representations. However, how the richness of such interactions trades off against the ability of a network to simultaneously carry ou…

Cited by 18SourcePDFScholar
2015

On the Limitation of Spectral Methods: From the Gaussian Hidden Clique Problem to Rank-One Perturbations of Gaussian Tensors

NeurIPS 2015poster

We consider the following detection problem: given a realization of asymmetric matrix $X$ of dimension $n$, distinguish between the hypothesisthat all upper triangular variables are i.i.d. Gaussians variableswith mean 0 and variance $1$ and the hypothesis that there is aplanted principal submatrix $…

Cited by 71SourcePDFScholar