Pietro Michiardi

Artificial Intelligence · 2002–2020

A researcher in the Science corpus: 8 papers; trusts 66 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 77 citations into it; #30,701 of 35,345 by trust here, #17,412 by citations
• Computer Networks and Communications — 40 citations into it
• Probabilistic & Bayesian Methods — 29 citations into it
• Information Systems — 19 citations into it; #7,703 of 8,771 by trust here, #5,942 by citations
• Computer Vision and Pattern Recognition — 18 citations into it; #19,073 of 21,575 by trust here, #18,266 by citations
• Signal Processing — 18 citations into it; #6,985 of 7,572 by trust here, #3,913 by citations
• Control and Systems Engineering — 16 citations into it
• Hardware and Architecture — 13 citations into it

Whom Pietro Michiardi trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Alex Graves
4. David John Cameron MacKay
5. Alex Krizhevsky
6. Radford M. Neal
7. Michael I. Jordan
8. Yoshua Bengio
9. Sepp Hochreiter
10. Yann LeCun

Who trusts Pietro Michiardi overall

1. Luzi Anderegg
2. Tiranuch Anantvalee
3. Zhu Han
4. Ismail Butun
5. Kevin J. Hoffman
6. Sonja Buchegger
7. Jean-Pierre Hubaux
8. Jie Wu
9. Stephan J. Eidenbenz
10. Dusist Niyato

Papers from Pietro Michiardi's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Learning Multiple Layers of Features from Tiny Images
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Random Feature Expansions for Deep Gaussian Processes (2016) — 153 citations
• A comparative evaluation of outlier detection algorithms: Experiments and analyses (2018) — 432 citations
• USAD: UnSupervised Anomaly Detection on Multivariate Time Series (2020) — 1,210 citations
• Calibrating Deep Convolutional Gaussian Processes (2018) — 45 citations
• Flexible Scheduling of Distributed Analytic Applications (2016) — 10 citations
• Password Strength: An Empirical Analysis (2010) — 315 citations
• Rarest first and choke algorithms are enough (2006) — 446 citations
• Core: a collaborative reputation mechanism to enforce node cooperation in mobile ad hoc networks (2002) — 1,890 citations