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  1. Projects

European Learning and Intelligent Systems Excellence (ELISE)

Project
ELISE aims to make Europe competitive in AI through a network of excellence. The best European researchers in
machine learning and AI have worked together to attract talent, to foster research through collaboration, and to inspire
and be inspired by industry and society. While ELISE starts from machine learning as the current most prominent
method of AI, the network invites in all ways of reasoning, considering all types of data, applicable for almost all
sectors of science and industry. While being aware of data safety and security, and while striving to explainable and
trustworthy outcomes we aim to create a force to Europe.
ELISE will run a PhD student and a postdoc programme to attract and to educate world-class talents to Europe.
It will operate a Fellows programme for groundbreaking research and high-profile workshops to develop AI
methods applications further. Industry involvement is guaranteed by the many connections members of ELISE
have with industry, on average one for every member and one start-up for every second member of ELISE. ELISE
will demonstrate a fraction of their research in use cases to be implemented in AI4EU and the SME’s of Europe.
Additional impact will be created to SME’s through open calls. The current practice of ELISE members of spin-off
research in SME’s once a break-through is achieved will be stimulated through incubators. The current practice of
participating in dissemination and debate that many members of ELISE are used to will be continued to develop a
mature acceptance of AI throughout Europe for the benefit of all and in cooperation with all.
ELISE is built on 105 organisations in total, in which the 202 core contributors have actively indicated they will
help build and profit from the networks of PhD-students and scholars. ELISE includes 60 ERC grants of their active
supporters. By their citation and other accepted scores of scientific quality, ELISE is the network that combines in
Europe excellence in AI.
  • Overview
  • Research Areas
  • Publications

Overview

Contributors

CESA BIANCHI NICOLO' ANTONIO   Scientific Manager  

Departments involved

Dipartimento di Informatica Giovanni Degli Antoni   Principale  

Type

H20_RIA - Horizon 2020_Research & Innovation Action/Innovation Action

Funder

EUROPEAN COMMISSION
External Organization Funding Organization

Date/time interval

November 1, 2020 - October 31, 2023

Project duration

36 months

Research Areas

Concepts


Settore INF/01 - Informatica

Publications

Outputs (12)

  • ascending
  • descending
  • All
  • Academic Article
  • Conference Paper
Bilateral trade: A regret minimization perspective 
MATHEMATICS OF OPERATIONS RESEARCH
INFORMS
2024
Academic Article
Partially Open Access
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Sublinear Algorithms for Local Graph-Centrality Estimation 
SIAM JOURNAL ON COMPUTING
SOCIETY FOR INDUSTRIAL AND APPLIED MATHEMATICS
2023
Academic Article
Partially Open Access
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Multitask Online Mirror Descent 
TRANSACTIONS ON MACHINE LEARNING RESEARCH
OPENREVIEW.NET
2022
Academic Article
Open Access
A Near-Optimal Best-of-Both-Worlds Algorithm for Online Learning with Feedback Graphs 
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS
CURRAN ASSOCIATES
2022
Conference Paper
Reserved Access
A Regret-Variance Trade-Off in Online Learning 
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS
CURRAN ASSOCIATES
2022
Conference Paper
Reserved Access
Active Learning of Classifiers with Label and Seed Queries 
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS
CURRAN ASSOCIATES
2022
Conference Paper
Reserved Access
Learning on the Edge: Online Learning with Stochastic Feedback Graphs 
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS
CURRAN ASSOCIATES
2022
Conference Paper
Reserved Access
Nonstochastic Bandits and Experts with Arm-Dependent Delays 
PROCEEDINGS OF MACHINE LEARNING RESEARCH
PMLR
2022
Conference Paper
Open Access
An Algorithm for Stochastic and Adversarial Bandits with Switching Costs 
PROCEEDINGS OF MACHINE LEARNING RESEARCH
PMLR
2021
Conference Paper
Open Access
Beyond Bandit Feedback in Online Multiclass Classification 
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS
CURRAN ASSOCIATES
2021
Conference Paper
Open Access
Exact Recovery of Clusters in Finite Metric Spaces Using Oracle Queries 
PROCEEDINGS OF MACHINE LEARNING RESEARCH
PMLR
2021
Conference Paper
Open Access
ROI Maximization in Stochastic Online Decision-Making 
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS
CURRAN ASSOCIATES
2021
Conference Paper
Open Access
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