We consider the problem of PAC-learning distributions over strings, represented by probabilistic deterministic finite automata (PDFAs). PDFAs are a probabilistic model for the gen...
Clustering short length texts is a difficult task itself, but adding the narrow domain characteristic poses an additional challenge for current clustering methods. We addressed thi...
Abstract. We present a performance analysis of three linear dimensionality reduction techniques: Fisher's discriminant analysis (FDA), and two methods introduced recently base...
This paper presents a method for vote-based 3D shape recognition and registration, in particular using mean shift on 3D pose votes in the space of direct similarity transforms for...
Minh-Tri Pham, Oliver J. Woodford, Frank Perbet, A...
— Discrete input distributions are capacity-achieving for a variety of noise distributions whenever the input is subject to peak power or other bounding constraints. In this pape...