Abstract. The ultimate aim of our research is a free, evolutionary, Internetbased, agent-based, long-distance teaching environment for academic English. For this purpose, we are bu...
The scarcity of manually labeled data for supervised machine learning methods presents a significant limitation on their ability to acquire knowledge. The use of kernels in Suppor...
Mahesh Joshi, Ted Pedersen, Richard Maclin, Sergue...
Compounded words are a challenge for NLP applications such as machine translation (MT). We introduce methods to learn splitting rules from monolingual and parallel corpora. We eva...
A finite-state method, based on leftmost longestmatch replacement, is presented for segmenting words into graphemes, and for converting graphemes into phonemes. A small set of han...
A gradient-based method for both symmetric and asymmetric multiagent reinforcement learning is introduced in this paper. Symmetric multiagent reinforcement learning addresses the ...