Field observations form the basis of many scientific studies, especially in ecological and social sciences. Despite efforts to conduct such surveys a standardized way, can be prone systematic measurement errors. The removal variability introduced by observation process, if possible, greatly increase value this data. Existing non-parametric techniques for correcting errors assume linear additive...

Operator-counting is a recently developed framework for analysing and integrating many state-ofthe-art heuristics for planning using Linear Programming. In cost-optimal planning only the objective value of these heuristics is traditionally used to guide the search. However the primal solution, i.e. the operator counts, contains useful information. We exploit this information using a SATbased ap...

Bayesian statistical inference for Generalized Linear Models (GLMs) with parameters lying on a constrained space is of general interest (e.g., in monotonic or convex regression), but often constructing valid prior distributions supported subspace spanned by set linear inequality constraints can be challenging, especially when some the might binding leading to lower dimensional subspace. For cas...