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» Learning from Multiple Sources of Inaccurate Data
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KDD
2005
ACM
149views Data Mining» more  KDD 2005»
14 years 1 months ago
A distributed learning framework for heterogeneous data sources
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
Srujana Merugu, Joydeep Ghosh
CC
2005
Springer
106views System Software» more  CC 2005»
14 years 1 months ago
Source-Level Debugging for Multiple Languages with Modest Programming Effort
Abstract. We present techniques that enable source-level debugging for multiple languages at the cost of only modest programming effort. The key idea is to avoid letting debugging ...
Sukyoung Ryu, Norman Ramsey
ICASSP
2011
IEEE
12 years 11 months ago
Novel beamformers for Multiple Correlated brain source localization and reconstruction
This paper introduces two novel beamforming algorithms, namely the Region Constrained and Multiple Correlated Source Model beamformers, designed to localize and to reconstruct hig...
Hung V. Dang, Kwong T. Ng, James K. Kroger
CIKM
2010
Springer
13 years 6 months ago
Collaborative Dual-PLSA: mining distinction and commonality across multiple domains for text classification
:  Collaborative Dual-PLSA: Mining Distinction and Commonality across Multiple Domains for Text Classification Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yuhong Xiong, Zhon...
Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yu...
IIWAS
2003
13 years 8 months ago
Zero-Latency Data Warehousing for Heterogeneous Data Sources and Continuous Data Streams
In this paper, a framework for building an overall Zero-Latency Data Warehouse system (ZLDWH) is provided. Such a ZLDWH requires tasks such as data changes detection, continuous l...
Tho Manh Nguyen, A. Min Tjoa