b'Yaniv Romano'

research

∙ 06/05/2023

Conformal Prediction with Missing Values

Conformal prediction is a theoretically grounded framework for construct...

0 Margaux Zaffran, et al. ∙

research

∙ 05/17/2023

Principal Uncertainty Quantification with Spatial Correlation for Image Restoration Problems

Uncertainty quantification for inverse problems in imaging has drawn muc...

0 Omer Belhasin, et al. ∙

research

∙ 02/14/2023

Derandomized Novelty Detection with FDR Control via Conformal E-values

Conformal prediction and other randomized model-free inference technique...

0 Meshi Bashari, et al. ∙

research

∙ 02/14/2023

Lightsolver challenges a leading deep learning solver for Max-2-SAT problems

Maximum 2-satisfiability (MAX-2-SAT) is a type of combinatorial decision...

0 Hod Wirzberger, et al. ∙

research

∙ 10/01/2022

Model-Free Sequential Testing for Conditional Independence via Testing by Betting

This paper develops a model-free sequential test for conditional indepen...

19 Shalev Shaer, et al. ∙

research

∙ 09/08/2022

Quantum Sparse Coding

The ultimate goal of any sparse coding method is to accurately recover f...

7 Yaniv Romano, et al. ∙

research

∙ 07/14/2022

From Shapley back to Pearson: Hypothesis Testing via the Shapley Value

Machine learning models, in particular artificial neural networks, are i...

13 Jacopo Teneggi, et al. ∙

research

∙ 07/03/2022

Learning to Increase the Power of Conditional Randomization Tests

The model-X conditional randomization test is a generic framework for co...

3 Shalev Shaer, et al. ∙

research

∙ 06/02/2022

Coordinated Double Machine Learning

Double machine learning is a statistical method for leveraging complex b...

18 Nitai Fingerhut, et al. ∙

research

∙ 05/30/2022

Fast Nonlinear Vector Quantile Regression

Quantile regression (QR) is a powerful tool for estimating one or more c...

55 Aviv A. Rosenberg, et al. ∙

research

∙ 05/12/2022

Training Uncertainty-Aware Classifiers with Conformalized Deep Learning

Deep neural networks are powerful tools to detect hidden patterns in dat...

34 Bat-Sheva Einbinder, et al. ∙

research

∙ 02/10/2022

Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging

Image-to-image regression is an important learning task, used frequently...

4 Anastasios N. Angelopoulos, et al. ∙

research

∙ 10/28/2021

An ℓ^p-based Kernel Conditional Independence Test

We propose a new computationally efficient test for conditional independ...

12 Meyer Scetbon, et al. ∙

research

∙ 10/02/2021

Calibrated Multiple-Output Quantile Regression with Representation Learning

We develop a method to generate predictive regions that cover a multivar...

0 Shai Feldman, et al. ∙

research

∙ 06/08/2021

Searching for consistent associations with a multi-environment knockoff filter

This paper develops a method based on model-X knockoffs to find conditio...

0 Shuangning Li, et al. ∙

research

∙ 06/01/2021

Improving Conditional Coverage via Orthogonal Quantile Regression

We develop a method to generate prediction intervals that have a user-sp...

0 Shai Feldman, et al. ∙

research

∙ 05/18/2021

Conformal histogram regression

This paper develops a conformal method to compute prediction intervals f...

0 Matteo Sesia, et al. ∙

research

∙ 04/16/2021

Testing for Outliers with Conformal p-values

This paper studies the construction of p-values for nonparametric outlie...

10 Stephen Bates, et al. ∙

research

∙ 06/08/2020

Achieving Equalized Odds by Resampling Sensitive Attributes

We present a flexible framework for learning predictive models that appr...

0 Yaniv Romano, et al. ∙

research

∙ 06/03/2020

Classification with Valid and Adaptive Coverage

Conformal inference, cross-validation+, and the jackknife+ are hold-out ...

0 Yaniv Romano, et al. ∙

research

∙ 08/15/2019

With Malice Towards None: Assessing Uncertainty via Equalized Coverage

An important factor to guarantee a fair use of data-driven recommendatio...

0 Yaniv Romano, et al. ∙

research

∙ 05/08/2019

Conformalized Quantile Regression

Conformal prediction is a technique for constructing prediction interval...

0 Yaniv Romano, et al. ∙

research

∙ 11/16/2018

Deep Knockoffs

This paper introduces a machine for sampling approximate model-X knockof...

0 Yaniv Romano, et al. ∙

research

∙ 06/26/2018

Improving Pursuit Algorithms Using Stochastic Resonance

Sparse Representation Theory is a sub-field of signal processing that ha...

0 Dror Simon, et al. ∙

research

∙ 05/29/2018

Classification Stability for Sparse-Modeled Signals

Despite their impressive performance, deep convolutional neural networks...

0 Yaniv Romano, et al. ∙

research

∙ 05/06/2018

Acceleration of RED via Vector Extrapolation

Models play an important role in inverse problems, serving as the prior ...

0 Tao Hong, et al. ∙

research

∙ 08/29/2017

Multi-Layer Convolutional Sparse Modeling: Pursuit and Dictionary Learning

The recently proposed Multi-Layer Convolutional Sparse Coding (ML-CSC) m...

0 Jeremias Sulam, et al. ∙

research

∙ 05/09/2017

Convolutional Dictionary Learning via Local Processing

Convolutional Sparse Coding (CSC) is an increasingly popular model in th...

0 Vardan Papyan, et al. ∙

research

∙ 02/11/2017

On the Global-Local Dichotomy in Sparsity Modeling

The traditional sparse modeling approach, when applied to inverse proble...

0 Dmitry Batenkov, et al. ∙

research

∙ 11/09/2016

The Little Engine that Could: Regularization by Denoising (RED)

Removal of noise from an image is an extensively studied problem in imag...

0 Yaniv Romano, et al. ∙

research

∙ 09/23/2016

Example-Based Image Synthesis via Randomized Patch-Matching

Image and texture synthesis is a challenging task that has long been dra...

0 Yi Ren, et al. ∙

research

∙ 07/27/2016

Convolutional Neural Networks Analyzed via Convolutional Sparse Coding

Convolutional neural networks (CNN) have led to many state-of-the-art re...

0 Vardan Papyan, et al. ∙

research

∙ 06/03/2016

RAISR: Rapid and Accurate Image Super Resolution

Given an image, we wish to produce an image of larger size with signific...

1 Yaniv Romano, et al. ∙

research

∙ 03/22/2016

Con-Patch: When a Patch Meets its Context

Measuring the similarity between patches in images is a fundamental buil...

0 Yaniv Romano, et al. ∙

research

∙ 02/22/2015

Boosting of Image Denoising Algorithms

In this paper we propose a generic recursive algorithm for improving ima...

0 Yaniv Romano, et al. ∙

Yaniv Romano

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