37 citations · 65 across the 8 of their papers we have counts for
5 papers · 1 filter
Learning with Changing Features
Amit Dhurandhar, Steve Hanneke, Liu Yang
In this paper we study the setting where features are added or change interpretation over time, which has applications in multiple domains such as retail, manufacturing, finance. I…
Statistical Learning under Nonstationary Mixing Processes
Steve Hanneke, Liu Yang
We study a special case of the problem of statistical learning without the i.i.d. assumption. Specifically, we suppose a learning method is presented with a sequence of data points…
Bounds on the Minimax Rate for Estimating a Prior over a VC Class from Independent Learning Tasks
Liu Yang, Steve Hanneke, Jaime Carbonell
We study the optimal rates of convergence for estimating a prior distribution over a VC class from a sequence of independent data sets respectively labeled by independent target fu…
Learning with a Drifting Target Concept
Steve Hanneke, Varun Kanade, Liu Yang
We study the problem of learning in the presence of a drifting target concept. Specifically, we provide bounds on the error rate at a given time, given a learner with access to a h…
Minimax Analysis of Active Learning
Steve Hanneke, Liu Yang
This work establishes distribution-free upper and lower bounds on the minimax label complexity of active learning with general hypothesis classes, under various noise models. The r…