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Computer Science

D-Index
50
Citations
8455
World Ranking
5684
National Ranking
2583

Overview

Claudio Gentile is a researcher affiliated with Google in the United States, focusing primarily on the field of Computer Science with an emphasis on Artificial Intelligence. Their body of work spans 27 publications, reflecting a concentration in several key interdisciplinary subfields, including Artificial Intelligence, Management Science and Operations Research, Aerospace Engineering, Control and Systems Engineering, and Computer Networks and Communications.

The main topics addressed in Gentile's research encompass Machine Learning and Algorithms, Advanced Bandit Algorithms Research, Reinforcement Learning in Robotics, Algorithms and Data Compression, Machine Learning and Data Classification, Wireless Signal Modulation Classification, and Radar Systems and Signal Processing.

Several venues have been frequent platforms for publishing their research, notably arXiv (Cornell University) with thirteen publications, IEEE Communications Letters with one publication, along with contributions to the journals Stato Chiese e pluralismo confessionale and Mathematical Programming.

Their recent research outputs include:

  • "Batch Active Learning at Scale" (2021), arXiv (Cornell University)
  • "Transient-Based Internet of Things Emitter Identification Using Convolutional Neural Networks and Optimized General Linear Chirplet Transform" (2020), IEEE Communications Letters
  • "Regret Bound Balancing and Elimination for Model Selection in Bandits and RL" (2020), arXiv (Cornell University)
  • "Fast Rates in Pool-Based Batch Active Learning" (2022), arXiv (Cornell University)
  • "Adaptive Region-Based Active Learning" (2020), arXiv (Cornell University)

Gentile has collaborated frequently with researchers such as Christoph Dann, Travis Dick, Giulia DeSalvo, Aldo Pacchiano, and Zhilei Wang, indicating an active role in collaborative projects and multi-author investigations.

Best Publications

  • On the generalization ability of on-line learning algorithms

    N. Cesa-Bianchi;A. Conconi;C. Gentile

  • Collaborative Filtering Bandits

    Shuai Li;Alexandros Karatzoglou;Claudio Gentile

  • Regret Minimization for Reserve Prices in Second-Price Auctions

    Nicolò Cesa-Bianchi;Claudio Gentile;Yishay Mansour

  • Tighter Approximated MILP Formulations for Unit Commitment Problems

    A. Frangioni;C. Gentile;F. Lacalandra

  • Perspective cuts for a class of convex 0–1 mixed integer programs

    A. Frangioni;C. Gentile

  • A new approximate maximal margin classification algorithm

    Claudio Gentile

  • Adaptive and self-confident on-line learning algorithms

    Peter Auer;Nicolò Cesa-Bianchi;Claudio Gentile

  • Incremental Algorithms for Hierarchical Classification

    Nicolò Cesa-Bianchi;Claudio Gentile;Luca Zaniboni

  • A Second-Order Perceptron Algorithm

    Nicolò Cesa-Bianchi;Alex Conconi;Claudio Gentile

  • The Robustness of the p -Norm Algorithms

    Claudio Gentile

  • Hierarchical classification: combining Bayes with SVM

    Nicolò Cesa-Bianchi;Claudio Gentile;Luca Zaniboni

  • Linear Algorithms for Online Multitask Classification

    Giovanni Cavallanti;Nicolò Cesa-Bianchi;Claudio Gentile

  • Online Clustering of Bandits

    Claudio Gentile;Shuai Li;Giovanni Zappella

  • Tracking the best hyperplane with a simple budget Perceptron

    Giovanni Cavallanti;Nicolò Cesa-Bianchi;Claudio Gentile

  • Solving nonlinear single-unit commitment problems with ramping constraints

    Antonio Frangioni;Claudio Gentile

  • Linear Hinge Loss and Average Margin

    Claudio Gentile;Manfred K Warmuth

  • Worst-Case Analysis of Selective Sampling for Linear Classification

    Nicolò Cesa-Bianchi;Claudio Gentile;Luca Zaniboni

  • Tight MIP formulations of the power-based unit commitment problem

    Germán Morales-España;Claudio Gentile;Andres Ramos

  • Solving unit commitment problems with general ramp constraints

    Antonio Frangioni;Claudio Gentile;Fabrizio Lacalandra

  • A Gang of Bandits

    Nicolò Cesa-Bianchi;Claudio Gentile;Giovanni Zappella

  • Selective sampling and active learning from single and multiple teachers

    Ofer Dekel;Claudio Gentile;Karthik Sridharan

  • The robustness of the p-norm algorithms

    Claudio Gentile;Nick Littlestone

  • Tracking the best hyperplane with a simple budget perceptron

    Nicolò Cesa-Bianchi;Claudio Gentile

  • Incremental Algorithms for Hierarchical Classification

    Nicolò Cesa-bianchi;Claudio Gentile;Andrea Tironi;Luca Zaniboni

Frequent Co-Authors

Nicolò Cesa-Bianchi
Nicolò Cesa-Bianchi University of Milan
Yishay Mansour
Yishay Mansour Tel Aviv University
Mehryar Mohri
Mehryar Mohri Google (United States)
Corinna Cortes
Corinna Cortes Google (United States)
Alexandros Karatzoglou
Alexandros Karatzoglou Google (United States)
Noga Alon
Noga Alon Tel Aviv University
Francesco Orabona
Francesco Orabona King Abdullah University of Science and Technology
Shie Mannor
Shie Mannor Technion – Israel Institute of Technology
Gábor Lugosi
Gábor Lugosi Pompeu Fabra University
Peter Auer
Peter Auer University of Leoben

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