A classical learning problem in Inductive Inference consists of identifying each function of a given class of recursive functions from a finite number of its output values. Unifor...
This paper presents a method for learning a semantic parser from ambiguous supervision. Training data consists of natural language sentences annotated with multiple potential mean...
The advantage of a kernel method often depends critically on a proper choice of the kernel function. A promising approach is to learn the kernel from data automatically. In this p...
We present a probabilistic generative model for learning semantic parsers from ambiguous supervision. Our approach learns from natural language sentences paired with world states ...
The standardization of the design of learning games is a contradictory topic: The existence of a rich variety of domains and applications is in conflict with the desire for unifica...
Sebastian Kelle, Roland Klemke, Marion R. Gruber, ...