Commit ecded799 authored by Jaspreet's avatar Jaspreet

added papers related to black box interpretability and a related thesis.

parent 5f34e78e
......@@ -9,6 +9,21 @@ We release [InterpretMe]
1. **Jaspreet's Master Piece**
*Jaspreet Singh* 2019. [paper](https://arxiv.org/pdf/xxx.pdf)
1. **Interpretability of Machine Learning Models and Representations: an Introduction**
*Adrien Bibal and Benoît Frénay* 2018. [paper](https://pdfs.semanticscholar.org/4646/56fc6431f1db8b2e0b0b3093a5df1cb7958e.pdf)
1. **A Survey Of Methods For Explaining Black Box Models**
*Riccardo Guidotti, Anna Monreale, Franco Turini, Dino Pedreschi, Fosca Giannotti
* 2018. [paper](https://arxiv.org/pdf/1802.01933.pdf)
### Theses:
1. **Learning Interpretable Models**
*Stefan R¨uping* 2006. [paper](https://eldorado.tu-dortmund.de/bitstream/2003/23008/1/dissertation_rueping.pdf)
### Journal and Conference papers:
......@@ -68,3 +83,15 @@ We release [InterpretMe]
1. **What your images reveal: Exploiting visual contents for point-of-interest recommendation.**
*Suhang Wang, Yilin Wang, Jiliang Tang, Kai Shu,Suhas Ranganath,and Huan Liu*. WWW 2017.[paper](http://www.public.asu.edu/~swang187/publications/VPOI.pdf)
1. **A causal framework for explaining the predictions of black-box sequence-to-sequence models**
*David Alvarez-Melis, Tommi S. Jaakkola*. ACL 2017.[paper](http://www.aclweb.org/anthology/D17-1042)
1. **Why should i trust you?: Explaining the predictions of any classifier.**
*Ribeiro, Marco Tulio, Sameer Singh, and Carlos Guestrin*. SIGKDD 2016.[paper](https://chara.cs.illinois.edu/sites/fa16-cs591txt/pdf/Ribeiro-2016-KDD.pdf)
1. **Understanding Black-box Predictions via Influence Functions**
*Pang Wei Koh and Percy Liang*. ICML 2017.[paper](https://arxiv.org/pdf/1703.04730.pdf)
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