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Computer Science
Italy
2025

D-Index & Metrics

Computer Science

D-Index
73
Citations
28868
World Ranking
1554
National Ranking
19

Research.com Recognitions

  • 2025 - Research.com Computer Science in Italy Leader Award
  • 2023 - Research.com Computer Science in Italy Leader Award
  • 2022 - Research.com Computer Science in Italy Leader Award

Overview

Massimiliano Pontil is affiliated with the Italian Institute of Technology in Italy, where they have contributed extensively to research in computer science, particularly focusing on artificial intelligence and related subfields.

Their published works span a variety of topics including domain adaptation and few-shot learning, sparse and compressive sensing techniques, stochastic gradient optimization techniques, advanced bandit algorithms research, model reduction and neural networks, machine learning and data classification, as well as Gaussian processes and Bayesian inference.

Frequent co-authors collaborating with Pontil include Carlo Ciliberto, Karim Lounici, Pietro Novelli, Vladimir Kostić, and Riccardo Grazzi.

The scholar has published predominantly in the venue arXiv (Cornell University), with a tally of 59 publications. Other publication venues include:

  • Proceedings of the International AAAI Conference on Web and Social Media
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Pattern Recognition Letters
  • Scientific Reports

Recent papers authored or co-authored by Pontil are listed below:

  • "An Empirical Study of Geographic User Activity Patterns in Foursquare", 2021, Proceedings of the International AAAI Conference on Web and Social Media
  • "Machine Learning for Cultural Heritage: A Survey", 2020, Pattern Recognition Letters
  • "Exploiting Semantic Annotations for Clustering Geographic Areas and Users in Location-based Social Networks", 2021, Proceedings of the International AAAI Conference on Web and Social Media
  • "Identifying the signature of prospective motor control in children with autism", 2021, Scientific Reports
  • "General Fair Empirical Risk Minimization", 2020, CINECA IRIS Institutional Research Information System (University of Genoa)

Massimiliano Pontil's research covers the following main fields and subfields:

  • Computer Science
  • Artificial Intelligence
  • Computational Mechanics
  • Management Science and Operations Research
  • Statistical and Nonlinear Physics
  • Computer Vision and Pattern Recognition

Their expertise extends across a spectrum of specialized topics including:

  • Domain Adaptation and Few-Shot Learning
  • Sparse and Compressive Sensing Techniques
  • Stochastic Gradient Optimization Techniques
  • Advanced Bandit Algorithms Research
  • Model Reduction and Neural Networks
  • Machine Learning and Data Classification
  • Gaussian Processes and Bayesian Inference

Best Publications

  • Convex multi-task feature learning

    Andreas Argyriou;Theodoros Evgeniou;Massimiliano Pontil

  • Regularized multi--task learning

    Theodoros Evgeniou;Massimiliano Pontil

  • Multi-Task Feature Learning

    Andreas Argyriou;Theodoros Evgeniou;Massimiliano Pontil

  • Regularization Networks and Support Vector Machines

    Theodoros Evgeniou;Massimiliano Pontil;Tomaso A. Poggio

  • Feature Selection for SVMs

    Jason Weston;Sayan Mukherjee;Olivier Chapelle;Massimiliano Pontil

  • Support vector machines for 3D object recognition

    M. Pontil;A. Verri

  • Learning Multiple Tasks with Kernel Methods

    Theodoros Evgeniou;Charles A. Micchelli;Massimiliano Pontil

  • PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments.

    David T. Jones;Daniel W. A. Buchan;Domenico Cozzetto;Massimiliano Pontil

  • A tale of many cities: universal patterns in human urban mobility.

    Anastasios Noulas;Salvatore Scellato;Renaud Lambiotte;Massimiliano Pontil

  • An Empirical Study of Geographic User Activity Patterns in Foursquare.

    Anastasios Noulas;Salvatore Scellato;Cecilia Mascolo;Massimiliano Pontil

  • On Learning Vector-Valued Functions

    Charles A. Micchelli;Massimiliano A. Pontil

  • Optimal kernel choice for large-scale two-sample tests

    Arthur Gretton;Dino Sejdinovic;Heiko Strathmann;Sivaraman Balakrishnan

  • Learning the Kernel Function via Regularization

    Charles A. Micchelli;Massimiliano Pontil

  • Quantum machine learning: a classical perspective.

    Carlo Ciliberto;Mark Herbster;Alessandro Davide Ialongo;Alessandro Davide Ialongo;Massimiliano Pontil;Massimiliano Pontil

  • Support vector machines: theory and applications

    Theodoros Evgeniou;Massimiliano Pontil

  • Oracle Inequalities and Optimal Inference under Group Sparsity

    Karim Lounici;Massimiliano Pontil;Sara van de Geer;Alexandre B. Tsybakov

  • Unsupervised Cross-Dataset Transfer Learning for Person Re-identification

    Peixi Peng;Tao Xiang;Yaowei Wang;Massimiliano Pontil

  • Empirical Bernstein Bounds and Sample Variance Penalization

    Andreas Maurer;Massimiliano Pontil

  • Properties of Support Vector Machines

    Massimiliano Pontil;Alessandro Verri

  • Face Detection in Still Gray Images

    Bernd Heisele;Tomaso poggio;Massimilinao Pontil

  • On Spectral Learning

    Andreas Argyriou;Charles A. Micchelli;Massimiliano Pontil

Frequent Co-Authors

Paolo Frasconi
Paolo Frasconi University of Florence
Alessandro Verri
Alessandro Verri University of Genoa
Luca Oneto
Luca Oneto University of Genoa
John Shawe-Taylor
John Shawe-Taylor University College London
Janaina Mourao-Miranda
Janaina Mourao-Miranda University College London
Arthur Gretton
Arthur Gretton University College London
Cristina Becchio
Cristina Becchio Italian Institute of Technology
David T. Jones
David T. Jones University College London

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