695 citations · 2.7k across the 76 of their papers we have counts for
7 papers · 1 filter
Improved Consistency Regularization for GANs
Zhengli Zhao, Sameer Singh, Honglak Lee +3
Recent work has increased the performance of Generative Adversarial Networks (GANs) by enforcing a consistency cost on the discriminator. We improve on this technique in several wa…
Improving Differentially Private Models with Active Learning
Zhengli Zhao, Nicolas Papernot, Sameer Singh +2
Broad adoption of machine learning techniques has increased privacy concerns for models trained on sensitive data such as medical records. Existing techniques for training differen…
Compact Factorization of Matrices Using Generalized Round-Rank
Pouya Pezeshkpour, Carlos Guestrin, Sameer Singh
Matrix factorization is a well-studied task in machine learning for compactly representing large, noisy data. In our approach, instead of using the traditional concept of matrix ra…
Programs as Black-Box Explanations
Sameer Singh, Marco Tulio Ribeiro, Carlos Guestrin
Recent work in model-agnostic explanations of black-box machine learning has demonstrated that interpretability of complex models does not have to come at the cost of accuracy or m…
Nothing Else Matters: Model-Agnostic Explanations By Identifying Prediction Invariance
Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin
At the core of interpretable machine learning is the question of whether humans are able to make accurate predictions about a model's behavior. Assumed in this question are three p…
Model-Agnostic Interpretability of Machine Learning
Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin
Understanding why machine learning models behave the way they do empowers both system designers and end-users in many ways: in model selection, feature engineering, in order to tru…