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cs.LG2018★ 17 cited
Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution
Judea Pearl
Current machine learning systems operate, almost exclusively, in a statistical, or model-free mode, which entails severe theoretical limits on their power and performance. Such sys…
cs.LG2014★ 21 cited
Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data
Guy Van den Broeck, Karthika Mohan, Arthur Choi +1
We propose an efficient family of algorithms to learn the parameters of a Bayesian network from incomplete data. In contrast to textbook approaches such as EM and the gradient meth…