ILP turns 20

ILP turns 20 Biography and future challenges

Inductive Logic Programming (ILP) is an area of Machine Learning which has now reached its twentieth year. Using the analogy of a human biography this paper recalls the development of the subject from its infancy through childhood and teenage years. We show how in each phase ILP has been characterised by an attempt to extend theory and implementations in tandem with the development of novel and...

The disease that transformed medicine: AIDS turns 20.

Ilp 07

• Complementary advantages • logic can represent domain knowledge in a natural and expressive way • inductive logic programming (ILP) can generate theories and explanations • probabilities allow us to deal with uncertainty and noise in the data • Fixed unknown density ρ on X × Y • The optimal decision would be ρ(Y = 1|x) > 0.5 • Generative direction: model the class conditional densities p(x|y)...

Two Decades of Saving Lives on the Battlefield: Tactical Combat Casualty Care Turns 20.

BACKGROUND Twenty years ago, the original Tactical Combat Casualty Care (TCCC) article was published in this journal. Since TCCC is essentially a set of best-practice prehospital trauma care guidelines customized for use on the battlefield, the presence of a journal with a specific focus on military medicine was a profound benefit to the initial presentation of TCCC to the U.S. Military. METH...

Generic ILP vs Specialized 0-1 ILP for Haplotype Inference

Haplotype inference is an important and computationally challenging problem in genetics. A well-known approach to haplotype inference is pure parsimony (HIPP). Despite being based on a simple optimization criterion, HIPP is a computationally hard problem. Recent work has shown that approaches based on Boolean satisfiability namely pseudo-Boolean optimization (PBO), are very effective at tacklin...