This paper attempts to bridge the gap between FrameNet frames and inference. We describe a computational formalism that captures structural relationships among participants in a d...
Nancy Chang, Srini Narayanan, Miriam R. L. Petruck
A central problem in multistrategy learning systems is the selection and sequencing of machine learning algorithms for particular situations. This is typically done by the system ...
In this paper, we present a space efficient algorithm for speeding up isosurface extraction. Even though there exist algorithms that can achieve optimal search performance to iden...
In cross-modal inference, we estimate complete fields from noisy and missing observations of one sensory modality using structure found in another sensory modality. This inference...
S. Ravela, Antonio B. Torralba, William T. Freeman
In this paper we propose a new framework for modeling 2D shapes. A shape is first described by a sequence of local features (e.g., curvature) of the shape boundary. The resulting ...