Qingcan Li

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 9 citations into it
• Safety, Robustness & Interpretability — 6 citations into it

Whom Qingcan Li trusts overall

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

1. Andrew McCallum
2. Olcay Boz
3. Richard S. Sutton

Papers from Qingcan Li's perspective

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

1. Do Deep Nets Really Need to be Deep?
2. OpenAI Gym
3. Association for Computational Linguistics " Why Should I Trust You? " Explaining the Predictions of Any Classifier
4. Introduction to Reinforcement Learning
5. Support Vector Machine Active Learning with Applications to Text Classification
6. The mythos of model interpretability
7. Interpretable Deep Models for ICU Outcome Prediction
8. Tree Based Discretization for Continuous State Space Reinforcement Learning
9. Extracting Tree-Structured Representations of Trained Networks
10. Learning With Continuous Classes

Their papers

• Toward Interpretable Deep Reinforcement Learning with Linear Model U-Trees (2018) — 157 citations