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» Embedding Heterogeneous Data Using Statistical Models
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NIPS
2003
15 years 3 months ago
Fast Algorithms for Large-State-Space HMMs with Applications to Web Usage Analysis
In applying Hidden Markov Models to the analysis of massive data streams, it is often necessary to use an artificially reduced set of states; this is due in large part to the fac...
Pedro F. Felzenszwalb, Daniel P. Huttenlocher, Jon...
134
Voted
EMNLP
2007
15 years 4 months ago
Bootstrapping Feature-Rich Dependency Parsers with Entropic Priors
One may need to build a statistical parser for a new language, using only a very small labeled treebank together with raw text. We argue that bootstrapping a parser is most promis...
David A. Smith, Jason Eisner
ICML
2006
IEEE
16 years 3 months ago
Nonstationary kernel combination
The power and popularity of kernel methods stem in part from their ability to handle diverse forms of structured inputs, including vectors, graphs and strings. Recently, several m...
Darrin P. Lewis, Tony Jebara, William Stafford Nob...
141
Voted
ALT
2006
Springer
15 years 11 months ago
Learning Linearly Separable Languages
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri
146
Voted
KDD
2012
ACM
212views Data Mining» more  KDD 2012»
13 years 5 months ago
Factoring past exposure in display advertising targeting
Online advertising is increasingly becoming more performance oriented, where the decision to show an advertisement to a user is made based on the user’s propensity to respond to...
Neha Gupta, Abhimanyu Das, Sandeep Pandey, Vijay K...