Emir Demirovi'c

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 5 papers; trusts 45 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 68 citations into it; #15,075 of 35,345 by trust here, #27,551 by citations
• Computational Theory and Mathematics — 32 citations into it
• Algorithms & Complexity — 25 citations into it
• Information Systems — 23 citations into it; #5,732 of 8,771 by trust here, #8,258 by citations
• Statistical Learning Theory — 18 citations into it
• Computer Networks and Communications — 12 citations into it; #6,482 of 9,886 by trust here, #9,768 by citations
• Optimization & Training — 11 citations into it
• Mathematical Optimization — 7 citations into it

Whom Emir Demirovi'c trusts overall

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

1. Siegfried Nijssen
2. Sicco Verwer
3. Florent Avellaneda
4. Dimitris J. Bertsimas
5. Gaël Aglin
6. Leo Breiman
7. J. Ross Quinlan
8. Nina Narodytska
9. Yingqian Zhang
10. Xiyang Hu

Who trusts Emir Demirovi'c overall

1. Vinícius G. Costa
2. Hao Hu
3. Carlos Eduardo Pedreira
4. Emilio Carrizosa
5. Mohamed Siala
6. Emmanuel Hebrard
7. Cynthia Rudin
8. Cristina Molero-Río
9. Peter James Stuckey
10. Marie-José Huguet

Papers from Emir Demirovi'c's perspective

Ordered by how strongly the researchers Emir Demirovi'c 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. Classification and regression trees
4. Induction of decision trees
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. ImageNet: A large-scale hierarchical image database
9. Constructing Optimal Binary Decision Trees is NP-Complete
10. C4.5: Programs for Machine Learning

Their papers

• Core-Boosted Linear Search for Incomplete MaxSAT (2019) — 61 citations
• Optimal Decision Trees for Nonlinear Metrics (2020) — 31 citations
• MurTree: Optimal Decision Trees via Dynamic Programming and Search (2020) — 89 citations
• MurTree: Optimal Classification Trees via Dynamic Programming and Search (2020) — 19 citations
• Techniques Inspired by Local Search for Incomplete MaxSAT and the Linear Algorithm: Varying Resolution and Solution-Guided Search (2019) — 17 citations