Michele Santacatterina

Artificial Intelligence · 2019

A researcher in the Science corpus: 2 papers; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 13 citations into it
• Management Science and Operations Research — 8 citations into it
• Reinforcement Learning — 8 citations into it
• Statistics and Probability — 7 citations into it

Whom Michele Santacatterina trusts overall

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

1. Thorsten Joachims
2. Adith Swaminathan
3. J. Langford
4. James M. Robins
5. Subir Ghosh
6. Miroslav Dud'ik
7. Alina Beygelzimer
8. Alekh Agarwal
9. Philip S. Thomas
10. H. Bang

Papers from Michele Santacatterina's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Doubly Robust Policy Evaluation and Learning
3. Reinforcement Learning: An Introduction
4. Gradient-based learning applied to document recognition
5. A Generalization of Sampling Without Replacement from a Finite Universe
6. Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
9. Semiparametric Efficiency in Multivariate Regression Models with Missing Data
10. Doubly Robust Estimation in Missing Data and Causal Inference Models

Their papers

• CAB: Continuous Adaptive Blending for Policy Evaluation and Learning (2019) — 91 citations
• Do the right thing ” : machine learning and causal inference for improved decision making