We present the first PAC bounds for learning parameters of Conditional Random Fields [12] with general structures over discrete and real-valued variables. Our bounds apply to com...
Abstract— A common framework for formalization of statetransition computation models is presented based on a general theory for studying the interrelationships between specifica...
Abstract. We consider the problem of training discriminative structured output predictors, such as conditional random fields (CRFs) and structured support vector machines (SSVMs)....
Patrick Pletscher, Cheng Soon Ong, Joachim M. Buhm...
- Events are at the core of reactive applications, which have become popular in many domains. Contemporary modeling tools lack the capability express the event semantics and relati...
This paper proposes a general probabilistic framework for shape-based modeling and classification of waveform data. A segmental hidden Markov model (HMM) is used to characterize w...