In this work we present the Subsequence Similarity Language Model (S2-LM) which is a new approach to language modeling based on string similarity. As a language model, S2-LM gener...
This paper proposes a Bayesian algorithm to estimate the parameters of a smooth transition regression model. With in this model, time series are divided into segments and a linear...
The goal of this work was to explore modeling techniques to improve bird species classification from audio samples. We first developed an unsupervised approach to obtain approxima...
Martin Graciarena, Michelle Delplanche, Elizabeth ...
We present several modifications of the original recurrent neural network language model (RNN LM). While this model has been shown to significantly outperform many competitive l...
Tomas Mikolov, Stefan Kombrink, Lukas Burget, Jan ...
We present an analytical model relating FPGA architectural parameters to the routability of the FPGA. The inputs to the model include the channel width and connection and switch b...