1183 search results - page 123 / 237 » Learning Process Models with Missing Data |
167
Voted
ICASSP
2010
IEEE
15 years 5 months ago
2010
IEEE
Data sparseness is an ever dominating problem in automatic emotion recognition. Using artificially generated speech for training or adapting models could potentially ease this: t...
156
click to vote
KDD
2005
ACM
16 years 5 months ago
2005
ACM
Discriminative sequential learning models like Conditional Random Fields (CRFs) have achieved significant success in several areas such as natural language processing, information...
137
click to vote
ECML
2007
Springer
15 years 11 months ago
2007
Springer
Many applications in information retrieval, natural language processing, data mining, and related fields require a ranking of instances with respect to a specified criteria as op...
161
Voted
JMLR
2010
14 years 12 months ago
2010
In this paper we integrate two essential processes, discretization of continuous data and learning of a model that explains them, towards fully computational machine learning from...
135
Voted
AAAI
2010
15 years 6 months ago
2010
Constructing models of mobile agents can be difficult without domain-specific knowledge. Parametric models flexible enough to capture all mobility patterns that an expert believes...