2,437 research outputs found
Identifiability and Unmixing of Latent Parse Trees
This paper explores unsupervised learning of parsing models along two
directions. First, which models are identifiable from infinite data? We use a
general technique for numerically checking identifiability based on the rank of
a Jacobian matrix, and apply it to several standard constituency and dependency
parsing models. Second, for identifiable models, how do we estimate the
parameters efficiently? EM suffers from local optima, while recent work using
spectral methods cannot be directly applied since the topology of the parse
tree varies across sentences. We develop a strategy, unmixing, which deals with
this additional complexity for restricted classes of parsing models
Modelling of building interiors with mobile phone sensor data
Creating as-built plans of building interiors is a challenging task. In this paper we present a semi-automatic modelling system for creating residential building interior plans and their integration with existing map data to produce building models. Taking a set of imprecise measurements made with an interactive mobile phone room mapping application, the system performs spatial adjustments in accordance with soft and hard constraints imposed on the building plan geometry. The approach uses an optimisation model that exploits a high accuracy building outline, such as can be found in topographic map data, and the building topology to improve the quality of interior measurements and generate a standardised output. We test our system on building plans of five residential homes. Our evaluation shows that the approach enables construction of accurate interior plans from imprecise measurements. The experiments report an average accuracy of 0.24 m, close to the 0.20 m recommended by the CityGML LoD4 specificatio
Approximation, generalisation and deconstruction of planar curves
CISRG discussion paper ; 1
Evolving missions to create game spaces
This paper describes a search-based generative
method which creates game levels by evolving the intended
sequence of player actions rather than their spatial layout. The
proposed approach evolves graphs where nodes representing
player actions are linked to form one or more ways in which
a mission can be completed. Initially simple graphs containing
the mission’s starting and ending nodes are evolved via mutation
operators which expand and prune the graph topology. Evolution
is guided by several objective functions which capture game
design patterns such as exploration or balance; experiments
in this paper explore how these objective functions and their
combinations affect the quality and diversity of the evolved
mission graphs.peer-reviewe
- …