Marco Degemmis

Artificial Intelligence · 2011–2019

A researcher in the Science corpus: 3 papers; trusts 10 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 19 citations into it; #12,522 of 35,345 by trust here, #14,181 by citations
• Information Systems — 16 citations into it; #2,274 of 8,771 by trust here, #2,406 by citations
• Natural Language Processing — 13 citations into it

Whom Marco Degemmis trusts overall

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

1. Dekang Lin
2. Fabrizio Sebastiani
3. Magnus Sahlgren
4. Raymond J. Mooney
5. Daniel Billsus
6. Marko Balabanovic
7. Jonathan L. Herlocker
8. Michael J. Pazzani
9. Stuart E. Middleton
10. Evgeniy Gabrilovich

Who trusts Marco Degemmis overall

1. Charu C. Aggarwal
2. Sarasi Lalithsena
3. Panniello Umberto
4. M. M. Afsar
5. Li Chen
6. Maurizio Ferrari Dacrema
7. Zhaochun Ren
8. Manasi Vartak
9. Zhongqi Lu

Papers from Marco Degemmis's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
5. GloVe: Global Vectors for Word Representation
6. Long Short-Term Memory
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Language Models are Unsupervised Multitask Learners
9. Gradient-based learning applied to document recognition
10. ImageNet: A large-scale hierarchical image database

Their papers

• AlBERTo: Italian BERT Language Understanding Model for NLP Challenging Tasks Based on Tweets (2019) — 235 citations
• ExpLOD: A Framework for Explaining Recommendations based on the Linked Open Data Cloud (2016) — 77 citations
• Content-based Recommender Systems: State of the Art and Trends (2011) — 2,032 citations