◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Vittorio Murino

58 papers hereh-index 6218.9k citations517 works total

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

author position
  • middle author27
  • last author30

Across the 57 of 58 papers where every author was matched, so the position is known.

fields
  • cs.CV49
  • cs.LG4
  • cs.MS1
  • cs.NE1
  • cs.SD1
  • q-bio.NC1
same name
  • Vittorio Murino — 10 papers, h 3
  • Vittorio Murino — 8 papers, h 5
  • Vittorio Murino — 1 paper, h 2

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
20112026
most citedGeneralizing to Unseen Domains via Adversarial Data Augmentation

361 citations · 944 across the 48 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2019

Addressing Model Vulnerability to Distributional Shifts over Image Transformation Sets

Riccardo Volpi, Vittorio Murino

We are concerned with the vulnerability of computer vision models to distributional shifts. We formulate a combinatorial optimization problem that allows evaluating the regions in…

cs.LG2017★ 20 cited

Dropout as a Low-Rank Regularizer for Matrix Factorization

Jacopo Cavazza, Pietro Morerio, Benjamin Haeffele +3

Regularization for matrix factorization (MF) and approximation problems has been carried out in many different ways. Due to its popularity in deep learning, dropout has been applie…

cs.LG2017★ 2 cited

An Analysis of Dropout for Matrix Factorization

Jacopo Cavazza, Connor Lane, Benjamin D. Haeffele +2

Dropout is a simple yet effective algorithm for regularizing neural networks by randomly dropping out units through Bernoulli multiplicative noise, and for some restricted problem…

cs.LG2016★ 3 cited

Active Regression with Adaptive Huber Loss

Jacopo Cavazza, Vittorio Murino

This paper addresses the scalar regression problem through a novel solution to exactly optimize the Huber loss in a general semi-supervised setting, which combines multi-view learn…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.