4 code implementations • 26 Jan 2019 • Yonatan Geifman, Ran El-Yaniv
We consider the problem of selective prediction (also known as reject option) in deep neural networks, and introduce SelectiveNet, a deep neural architecture with an integrated reject option.
1 code implementation • NeurIPS 2019 • Yonatan Geifman, Ran El-Yaniv
We consider active learning of deep neural networks.
no code implementations • ICLR 2019 • Yonatan Geifman, Guy Uziel, Ran El-Yaniv
We consider the problem of uncertainty estimation in the context of (non-Bayesian) deep neural classification.
no code implementations • 2 Nov 2017 • Yonatan Geifman, Ran El-Yaniv
This paper is concerned with pool-based active learning for deep neural networks.
no code implementations • NeurIPS 2017 • Yonatan Geifman, Ran El-Yaniv
Our method allows a user to set a desired risk level.
no code implementations • 23 May 2017 • Ran El-Yaniv, Yonatan Geifman, Yair Wiener
We introduce the Prediction Advantage (PA), a novel performance measure for prediction functions under any loss function (e. g., classification or regression).