Most models for online advertising assume that an advertiser's value from winning an ad auction, which depends on the clickthrough rate or conversion rate of the advertisemen...
In this abstract, we present a rule-based modelling language for constraint programming, called Rules2CP [1], and a library PKML for modelling packing problems. Unlike other modell...
With the arrival of high throughput genotyping techniques, the detection of likely genotyping errors is becoming an increasingly important problem. In this paper we are interested...
We describe a new class of utility-maximization scheduling problem with precedence constraints, the disconnected staged scheduling problem (DSSP). DSSP is a nonpreemptive multipro...
Eric Anderson, Dirk Beyer 0002, Kamalika Chaudhuri...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...