The discovery of causal relationships between a set of observed variables is a fundamental problem in science. For continuous-valued data linear acyclic causal models with additiv...
Patrik O. Hoyer, Dominik Janzing, Joris M. Mooij, ...
Hierarchical probabilistic modeling of discrete data has emerged as a powerful tool for text analysis. Posterior inference in such models is intractable, and practitioners rely on...
An important task in data analysis is the discovery of causal relationships between observed variables. For continuous-valued data, linear acyclic causal models are commonly used ...
Much previous work has examined the wireless power control problem using tools from game theory, an economic concept which describes the behavior of interdependent but non-coopera...
( )1 The most common metric for evaluating the performance of an optical communications system is the symbol error probability (SEP) versus the received optical power. In circuit-l...
Stefano Galli, Ronald Menendez, Russel Fischer, Ro...