262 citations · 1.8k across the 75 of their papers we have counts for
8 papers · 1 filter
Real-valued All-Dimensions search: Low-overhead rapid searching over subsets of attributes
Andrew Moore, Jeff Schneider
This paper is about searching the combinatorial space of contingency tables during the inner loop of a nonlinear statistical optimization. Examples of this operation in various dat…
Submodularity in Batch Active Learning and Survey Problems on Gaussian Random Fields
Yifei Ma, Roman Garnett, Jeff Schneider
Many real-world datasets can be represented in the form of a graph whose edge weights designate similarities between instances. A discrete Gaussian random field (GRF) model is a fi…
Maximum Margin Output Coding
Yi Zhang, Jeff Schneider
In this paper we study output coding for multi-label prediction. For a multi-label output coding to be discriminative, it is important that codewords for different label vectors ar…
Bayesian Optimal Active Search and Surveying
Roman Garnett, Yamuna Krishnamurthy, Xuehan Xiong +2
We consider two active binary-classification problems with atypical objectives. In the first, active search, our goal is to actively uncover as many members of a given class as pos…
Copula-based Kernel Dependency Measures
Barnabas Poczos, Zoubin Ghahramani, Jeff Schneider
The paper presents a new copula based method for measuring dependence between random variables. Our approach extends the Maximum Mean Discrepancy to the copula of the joint distrib…
Determining Frequentist Confidence Limits Using a Directed Parameter Space Search
Scott F. Daniel, Andrew J. Connolly, Jeff Schneider
We consider the problem of inferring constraints on a high-dimensional parameter space with a computationally expensive likelihood function. We propose a machine learning algorithm…