Performance Analysis
Faster Online Learning of Optimal Threshold for Consistent F-measure Optimization
Xiaoxuan Zhang, Mingrui Liu, Xun Zhou, Tianbao Yang
In this paper, we consider online F-measure optimization (OFO). Unlike traditional performance metrics (e.g., classification error rate), F-measure is non-decomposable over training examples and is a non-convex function of model parameters, making it much more difficult to be optimized in an online fashion. Most existing results of OFO usually suffer from high memory/computational costs and/or lack statistical consistency guarantee for optimizing F-measure at the population level.
Early Stopping for Nonparametric Testing
In this paper, we show that early stopping can also be applied to obtain the minimax optimal testing in a general non-parametric setup.
Multi-value Rule Sets for Interpretable Classification with Feature-Efficient Representations
Neural Information Processing Systems http://nips.cc/
On preserving non-discrimination when combining expert advice
Avrim Blum, Suriya Gunasekar, Thodoris Lykouris, Nati Srebro
Discrimination is commonly an issue in applications where decisions need to be made sequentially. The most prominent such application is online advertising where platforms need to sequentially select which ad to display in response to particular query searches.
Out-of-Distribution Detection using Multiple Semantic Label Representations
Gabi Shalev, Yossi Adi, Joseph Keshet
Neural Information Processing Systems http://nips.cc/
Why Is My Classifier Discriminatory?
Irene Chen, Fredrik D. Johansson, David Sontag
Recent attempts to achieve fairness in predictive models focus on the balance between fairness and accuracy.
Random Feature Stein Discrepancies
Jonathan Huggins, Lester Mackey
D 2 N, define [ D ]: = { 1,...,D } . The symbol & indicates greater than up to a universal constant.
A Model for Learned Bloom Filters and Optimizing by Sandwiching
Bloom filter is meant to represent.
Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer
David Madras, Toni Pitassi, Richard Zemel
Can humans and machines make decisions jointly?
Distributed Weight Consolidation: A Brain Segmentation Case Study
Patrick McClure, Charles Y. Zheng, Jakub Kaczmarzyk, John Rogers-Lee, Satra Ghosh, Dylan Nielson, Peter A. Bandettini, Francisco Pereira
Neural Information Processing Systems http://nips.cc/