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KDD
2004
ACM
210views Data Mining» more  KDD 2004»
16 years 4 months ago
Probabilistic author-topic models for information discovery
We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
CORR
2010
Springer
147views Education» more  CORR 2010»
15 years 3 months ago
Learning Probabilistic Hierarchical Task Networks to Capture User Preferences
While much work on learning in planning focused on learning domain physics (i.e., action models), and search control knowledge, little attention has been paid towards learning use...
Nan Li, William Cushing, Subbarao Kambhampati, Sun...
TCBB
2010
176views more  TCBB 2010»
15 years 2 months ago
Feature Selection for Gene Expression Using Model-Based Entropy
—Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best...
Shenghuo Zhu, Dingding Wang, Kai Yu, Tao Li, Yihon...
140
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ICML
2004
IEEE
16 years 4 months ago
The multiple multiplicative factor model for collaborative filtering
We describe a class of causal, discrete latent variable models called Multiple Multiplicative Factor models (MMFs). A data vector is represented in the latent space as a vector of...
Benjamin M. Marlin, Richard S. Zemel
ITS
1992
Springer
152views Multimedia» more  ITS 1992»
15 years 8 months ago
People Power: A Human-Computer Collaborative Learning System
Abstract. This paper reports our research work in the new field of humancomputer collaborative learning (HCCL). The general architecture of an HCCL is defined. An HCCL system, call...
Pierre Dillenbourg, John A. Self