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01/21/2021
Better Short than Greedy: Interpretable Models through Optimal Rule Boosting
Rule ensembles are designed to provide a useful trade-off between predic...
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09/06/2020
Discovering Reliable Causal Rules
We study the problem of deriving policies, or rules, that when enacted o...
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11/28/2019
Communication-Efficient Distributed Online Learning with Kernels
We propose an efficient distributed online learning protocol for low-lat...
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11/28/2019
Adaptive Communication Bounds for Distributed Online Learning
We consider distributed online learning protocols that control the excha...
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08/30/2019
Discovering Reliable Correlations in Categorical Data
In many scientific tasks we are interested in discovering whether there ...
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10/08/2018
Effective Parallelisation for Machine Learning
We present a novel parallelisation scheme that simplifies the adaptation...
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09/14/2018
Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms
The reliable fraction of information is an attractive score for quantify...
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09/22/2017
Efficiently Discovering Locally Exceptional yet Globally Representative Subgroups
Subgroup discovery is a local pattern mining technique to find interpret...
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05/25/2017
Discovering Reliable Approximate Functional Dependencies
Given a database and a target attribute of interest, how can we tell whe...
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01/26/2017