Francesco Bonchi

Artificial Intelligence · 2008–2017

A researcher in the Science corpus: 11 papers; trusts 71 researchers and is trusted by 33 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 111 citations into it; #8,839 of 35,345 by trust here, #6,911 by citations
• Statistical and Nonlinear Physics — 93 citations into it; #3,925 of 10,127 by trust here, #2,437 by citations
• Information Systems — 52 citations into it
• Sociology and Political Science — 49 citations into it; #6,089 of 22,756 by trust here, #10,781 by citations
• Computer Networks and Communications — 35 citations into it
• Management Science and Operations Research — 33 citations into it
• AI Ethics, Fairness & Society — 32 citations into it; #76 of 494 by trust here, #96 by citations
• Safety Research — 29 citations into it; #605 of 5,829 by trust here, #695 by citations

Whom Francesco Bonchi trusts overall

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

1. Salvatore Ruggieri
2. Dino Pedreschi
3. Faisal Kamiran
4. Sara Hajian
5. Indrė Žliobaitė
6. Franco Turini
7. Toon Calders
8. Mark Newman
9. Duncan J. Watts
10. Jon M. Kleinberg

Who trusts Francesco Bonchi overall

1. Lu Zhang
2. Yongkai Wu
3. Xintao Wu
4. Silvia Chiappa
5. Indrė Žliobaitė
6. Charu C. Aggarwal
7. Dino Pedreschi
8. Youze Tang
9. Sara Hajian
10. Yu Zheng

Papers from Francesco Bonchi's perspective

Ordered by how strongly the researchers Francesco Bonchi 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Et al
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• FA*IR: A Fair Top-k Ranking Algorithm (2017) — 547 citations
• Learning influence probabilities in social networks (2010) — 1,146 citations
• Exposing the probabilistic causal structure of discrimination (2015) — 78 citations
• Denser than the densest subgraph: extracting optimal quasi-cliques with quality guarantees (2013) — 340 citations
• Algorithmic Bias: From Discrimination Discovery to Fairness-aware Data Mining (2016) — 394 citations
• Topic-aware social influence propagation models (2012) — 420 citations
• A Data-Based Approach to Social Influence Maximization (2011) — 483 citations
• Social Network Analysis and Mining for Business Applications (2011) — 357 citations
• Fast shortest path distance estimation in large networks (2009) — 338 citations
• The query-flow graph: model and applications (2008) — 358 citations
• Never Walk Alone: Uncertainty for Anonymity in Moving Objects Databases (2008) — 558 citations