We define the problem of decomposing human-written summary sentences and propose a novel Hidden Markov Model solution to the problem. Human summarizers often rely on cutting and ...
We are interested in building decision-support software for social welfare case managers. Our model in the form of a factored Markov decision process is so complex that a standard...
This paper describes our work on building Part-of-Speech (POS) tagger for Bengali. We have use Hidden Markov Model (HMM) and Maximum Entropy (ME) based stochastic taggers. Bengali...
We propose a new decision-theoretic approach for solving execution-time deliberation scheduling problems using recent advances in Generalized Semi-Markov Decision Processes (GSMDP...
Partially Observable Markov Decision Process models (POMDPs) have been applied to low-level robot control. We show how to use POMDPs differently, namely for sensorplanning in the ...