121 citations · 295 across the 15 of their papers we have counts for
5 papers · 1 filter
Training Set Camouflage
Ayon Sen, Scott Alfeld, Xuezhou Zhang +3
We introduce a form of steganography in the domain of machine learning which we call training set camouflage. Imagine Alice has a training set on an illicit machine learning classi…
An Optimal Control Approach to Sequential Machine Teaching
Laurent Lessard, Xuezhou Zhang, Xiaojin Zhu
Given a sequential learning algorithm and a target model, sequential machine teaching aims to find the shortest training sequence to drive the learning algorithm to the target mode…
Axiomatic Interpretability for Multiclass Additive Models
Xuezhou Zhang, Sarah Tan, Paul Koch +3
Generalized additive models (GAMs) are favored in many regression and binary classification problems because they are able to fit complex, nonlinear functions while still remaining…
Teacher Improves Learning by Selecting a Training Subset
Yuzhe Ma, Robert Nowak, Philippe Rigollet +2
We call a learner super-teachable if a teacher can trim down an iid training set while making the learner learn even better. We provide sharp super-teaching guarantees on two learn…
Training Set Debugging Using Trusted Items
Xuezhou Zhang, Xiaojin Zhu, Stephen J. Wright
Training set bugs are flaws in the data that adversely affect machine learning. The training set is usually too large for man- ual inspection, but one may have the resources to ver…