Diffusion Kernels on Graphs and Other Discrete Input Spaces
The application of kernel-based learning algorithms has, so far, largely been confined to realvalued data and a few special data types, such as strings. In this paper we propose...
Publications
6 shownInducing features of random fields
We present a technique for constructing random fields from a set of training samples. The learning paradigm builds increasingly complex fields by allowing potential functions, o...
Using Maximum Entropy for Text Classification
This paper proposes the use of maximum entropy techniques for text classification. Maximum entropy is a probability distribution estimation technique widely used for a variety o...
Document Language Models, Query Models, and Risk Minimization for Information Retrieval
We present a framework for information retrieval that combines document models and query models using a probabilistic ranking function based on Bayesian decision theory. The fra...
A correlated topic model of Science
Topic models, such as latent Dirichlet allocation (LDA), can be useful tools for the statistical analysis of document collections and other discrete data. The LDA model assumes ...
Expectation-propagation for the generative aspect model
The generative aspect model is an extension of the multinomial model for text that allows word probabilities to vary stochastically across docu-ments. Previous results with aspe...
Frequent Co-Authors
Researcher Info
- h-index
- 6
- Publications
- 6
- Citations
- 4,877
- Institution
- Carnegie Mellon University
External Links
Identifiers
- ORCID
- 0000-0002-5929-220X
Impact Metrics
h-index
6
h-index: Number of publications with at least h citations each.