14 citations · 19 across the 5 of their papers we have counts for
6 papers
Explosive Percolation on Directed Networks Due to Monotonic Flow of Activity
Alex Waagen, Raissa M. D'Souza, Tsai-Ching Lu
An important class of real-world networks have directed edges, and in addition, some rank ordering on the nodes, for instance the "popularity" of users in online social networks. Y…
Algorithm Instance Games
Samuel D. Johnson, Tsai-Ching Lu
This paper introduces algorithm instance games (AIGs) as a conceptual classification applying to games in which outcomes are resolved from joint strategies algorithmically. For suc…
Most Relevant Explanation in Bayesian Networks
Changhe Yuan, Heejin Lim, Tsai-Ching Lu
A major inference task in Bayesian networks is explaining why some variables are observed in their particular states using a set of target variables. Existing methods for solving t…
Causal Mechanism-based Model Construction
Tsai-Ching Lu, Marek J. Druzdzel, Tze-Yun Leong
We propose a framework for building graphical causal model that is based on the concept of causal mechanisms. Causal models are intuitive for human users and, more importantly, sup…
Annealed MAP
Changhe Yuan, Tsai-Ching Lu, Marek J. Druzdzel
Maximum a Posteriori assignment (MAP) is the problem of finding the most probable instantiation of a set of variables given the partial evidence on the other variables in a Bayesia…
Most Relevant Explanation: Properties, Algorithms, and Evaluations
Changhe Yuan, Xiaolu Liu, Tsai-Ching Lu +1
Most Relevant Explanation (MRE) is a method for finding multivariate explanations for given evidence in Bayesian networks [12]. This paper studies the theoretical properties of MRE…