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» Embedding Heterogeneous Data Using Statistical Models
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115
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ICML
2010
IEEE
15 years 3 months ago
Local Minima Embedding
Dimensionality reduction is a commonly used step in many algorithms for visualization, classification, clustering and modeling. Most dimensionality reduction algorithms find a low...
Minyoung Kim, Fernando De la Torre
140
Voted
PERCOM
2010
ACM
15 years 22 days ago
Sensor.Network: An open data exchange for the web of things
Abstract—Tiny, wireless, sensors embedded in a large number of Internet-capable devices–smart phones, cameras, cars, toys, medical instruments, home appliances and energy meter...
Vipul Gupta, Arshan Poursohi, Poornaprajna Udupi
BMCBI
2008
128views more  BMCBI 2008»
15 years 2 months ago
HAPSIMU: a genetic simulation platform for population-based association studies
Background: Population structure is an important cause leading to inconsistent results in population-based association studies (PBAS) of human diseases. Various statistical method...
Feng Zhang, Jianfeng Liu, Jie Chen, Hong-Wen Deng
96
Voted
ICML
2010
IEEE
15 years 3 months ago
Deep Supervised t-Distributed Embedding
Deep learning has been successfully applied to perform non-linear embedding. In this paper, we present supervised embedding techniques that use a deep network to collapse classes....
Martin Renqiang Min, Laurens van der Maaten, Zinen...
CORR
2007
Springer
140views Education» more  CORR 2007»
15 years 2 months ago
From the entropy to the statistical structure of spike trains
— We use statistical estimates of the entropy rate of spike train data in order to make inferences about the underlying structure of the spike train itself. We first examine a n...
Yun Gao, Ioannis Kontoyiannis, Elie Bienenstock