Giulia Zarpellon

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 21 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 17 citations into it; #25,206 of 35,345 by trust here, #29,412 by citations
• Computational Theory and Mathematics — 7 citations into it
• Computer Networks and Communications — 6 citations into it
• Management Science and Operations Research — 6 citations into it; #8,261 of 11,946 by trust here, #8,906 by citations
• Reinforcement Learning — 6 citations into it; #1,710 of 2,242 by trust here, #2,063 by citations
• Computer Vision and Pattern Recognition — 5 citations into it
• Statistical Learning Theory — 5 citations into it

Whom Giulia Zarpellon trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Thorsten Joachims
2. Claude E. Shannon
3. Tobias Achterberg
4. Jorge Nocedal
5. Matteo Fischetti
6. Levente Kocsis
7. Jeff T. Linderoth
8. Greg Hamerly
9. Gregory Z. Gutin
10. Csaba Szepesvari

Who trusts Giulia Zarpellon overall

1. Maxime Gasse
2. Eric Larsen

Papers from Giulia Zarpellon's perspective

Ordered by how strongly the researchers Giulia Zarpellon trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Learning
3. Branching rules revisited
4. Gradient-based learning applied to document recognition
5. Some aspects of the sequential design of experiments
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. Bandit Based Monte-Carlo Planning
8. Training linear SVMs in linear time
9. A Computational Study of Search Strategies for Mixed Integer Programming
10. Neuro-Dynamic Programming

Their papers

• On learning and branching: a survey (2017) — 212 citations