21 citations · 23 across the 10 of their papers we have counts for
5 papers · 1 filter
High-Order Markov Blanket Discovery via a k-Order Relaxation of the Faithfulness Assumption
Loong Kuan Lee, Ragavi Krishnamoorthy, Nico Piatkowski
The problem of learning the graphical Markov blanket (MB) of a variable from data has applications in many areas such as structure learning for Bayesian networks and Markov random…
Standardization of Multi-Objective QUBOs
Loong Kuan Lee, Thore Gerlach, Nico Piatkowski
Multi-objective optimization involving Quadratic Unconstrained Binary Optimization (QUBO) problems arises in various domains. A fundamental challenge in this context is the effecti…
Computing Marginal and Conditional Divergences between Decomposable Models with Applications
Loong Kuan Lee, Geoffrey I. Webb, Daniel F. Schmidt +1
The ability to compute the exact divergence between two high-dimensional distributions is useful in many applications but doing so naively is intractable. Computing the alpha-beta…
Computing Divergences between Discrete Decomposable Models
Loong Kuan Lee, Nico Piatkowski, François Petitjean +1
There are many applications that benefit from computing the exact divergence between 2 discrete probability measures, including machine learning. Unfortunately, in the absence of a…
Understanding Concept Drift
Geoffrey I. Webb, Loong Kuan Lee, François Petitjean +1
Concept drift is a major issue that greatly affects the accuracy and reliability of many real-world applications of machine learning. We argue that to tackle concept drift it is im…