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...
In this paper we present algorithmic and architectural methodology for building Particle Filters in hardware. Particle filtering is a new paradigm for filtering in presence of n...
Aswin C. Sankaranarayanan, Rama Chellappa, Ankur S...
Modeling and simulating pipelined processors in procedural languages such as C/C++ requires lots of cost in handling concurrent events, which hinders fast simulation. A number of ...
In the last years dependency parsing has been accomplished by machine learning–based systems showing great accuracy but usually under 90% for Labelled Attachment Score (LAS). Mal...
In this paper we describe an automated system, and its attendant set of techniques and tools, that is able to generate novel multimedia experiences. Using existing online sources,...