This paper presents an LDA-style topic model that captures not only the low-dimensional structure of data, but also how the structure changes over time. Unlike other recent work t...
We present a method coupling multiple switching linear models. The coupled switching linear model is an interactive process of two switching linear models. Coupling is given throu...
Mun Ho Jeong, Yoshinori Kuno, Nobutaka Shimada, Yo...
This work proposes a novel practical and general-purpose lossless compression algorithm named Neural Markovian Predictive Compression (NMPC), based on a novel combination of Bayesi...
We combine two complementary ideas for learning supertaggers from highly ambiguous lexicons: grammar-informed tag transitions and models minimized via integer programming. Each st...
The fusion of information from heterogenous sensors is crucial to the effectiveness of a multimodal system. Noise affect the sensors of different modalities independently. A good ...
Shankar T. Shivappa, Bhaskar D. Rao, Mohan M. Triv...