Abstract. In this study we propose a novel model for the representation of biological networks and provide algorithms for learning model parameters from experimental data. Our appr...
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
Michael Collins, Amir Globerson, Terry Koo, Xavier...
: Classical inventory models offer a variety of insights into the optimal way to manage inventories of individual products. However, top managers and industry analysts are often co...
Temporal causal modeling has been a highly active research area in the last few decades. Temporal or time series data arises in a wide array of application domains ranging from med...
Inductive Logic Programming (ILP) involves the construction of first-order definite clause theories from examples and background knowledge. Unlike both traditional Machine Learnin...