KISHALAY DAS <kishalay.msit@gmail.com>
Abhilash Nandy <nandyabhilash@gmail.com>
J. Kleinberg, S. Mullainathan, Simplicity Creates Inequity: Implications for
Fairness, Stereotypes, and Interpretability. ACM Conference on Economics and
Computation, 2019
Michael Feldman, Sorelle A. Friedler, John Moeller, Carlos Scheidegger, and
Suresh Venkatasubramanian. Certifying and Removing Disparate Impact, KDD 2015
Fairness Constraints: Mechanisms for Fair Classification
M. B. Zafar, I. Valera, M. Gomez Rodriguez and K. P. Gummadi
AISTATS 2017, Fort Lauderdale, FL, April 2017.
Equality of opportunity in supervised learning,
Moritz Hardt, Eric Price, Nati Srebro,
NIPS 2016
FairRec: Two-Sided Fairness for Personalized Recommendations in Two-Sided Platforms
Gourab K Patro*, Arpita Biswas*, Niloy Ganguly, Krishna P. Gummadi, Abhijnan Chakraborty.
The Twenty-ninth Web Conference (WWW-2020).
Manjish Pal, Subham Pokhriyal, Sandipan Sikdar, Niloy Ganguly
Ensuring Generalized Fairness in Batch Classification
EXPLAINABILITY
Benjamin Letham, Cynthia Rudin, Tyler McCormick, David Madigan;
Interpretable Classifiers Using
Rules and Bayesian Analysis
2015
Himabindu Lakkaraju, Stephen H. Bach, Jure Leskovec
Interpretable Decision Sets: A Joint Framework for
Description and Prediction
Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin
Anchors: High-Precision Model-Agnostic Explanations
AAAI'2018
Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin
"Why Should I Trust You?" Explaining the Predictions of Any Classifier
KDD 2016
Rex Ying, Dylan Bourgeois, Jiaxuan You, Marinka Zitnik, Jure Leskovec
GNNExplainer: Generating Explanations for Graph Neural Networks
Neurips,19
Matthew D Zeiler, Rob Fergus
Visualizing and Understanding Convolutional Networks
ECCV, 2014
Karen Simonyan, Andrea Vedaldi, Andrew Zisserman
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
ICLR Workshop, 2014
B. Zhou, A. Khosla, L. A., A. Oliva, and A. Torralba. Learning Deep Features for Discriminative Localization. In CVPR,
2016.
Ramprasaath R Selvaraju, Abhishek Das, Ramakrishna Vedantam, Michael Cogswell, Devi Parikh, Dhruv Batra
Grad-CAM: Why did you say that?
ROBUSTNESS
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, Rob Fergus
Intriguing properties of neural networks
ICLR (Poster) 2014
Ian Goodfellow Jonathon Shlens Christian Szegedy
Explaining And Harnessing Adversarial Examples
International Conference on Learning Representations (2015)
Nicolas Papernot, Patrick McDaniel, Ian Goodfellow, Somesh Jha, Z. Berkay Celik, Ananthram Swami
Practical Black-Box Attacks against Machine Learning
PRIVACY - FEDERATED LEARNING
Brendan McMahan Eider Moore Daniel Ramage Seth Hampson Blaise Aguera y Arcas
Communication-Efficient Learning of Deep Networks
from Decentralized Data
Jianyu Wang, Gauri Joshi
Adaptive Communication Strategies to Achieve the Best Error-Runtime Trade-off in Local-Update SGD
Jianyu Wang, Qinghua Liu, Hao Liang, Gauri Joshi, H. Vincent Poor
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization
Evaluation