—Multi-robot reinforcement learning is a very challenging area due to several issues, such as large state spaces, difficulty in reward assignment, nondeterministic action selecti...
Most up-to-date well-behaved topic-based summarization systems are built upon the extractive framework. They score the sentences based on the associated features by manually assig...
We introduce a modified Kalman filter that performs robust, real-time outlier detection, without the need for manual parameter tuning by the user. Systems that rely on high quali...
Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...
This paper proposes a novel method for learning probability models of subcategorization preference of verbs. We consider the issues of case dependencies and noun class generalizat...