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» Approximate algorithms for neural-Bayesian approaches
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PROMISE
2010
14 years 4 months ago
Exploiting count spectra for Bayesian fault localization
Background: Automated diagnosis of software defects can drastically increase debugging efficiency, improving reliability and time-to-market. Current, low-cost, automatic fault dia...
Rui Abreu, Alberto González-Sanchez, Arjan ...
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
15 years 10 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal
SIGMOD
2001
ACM
200views Database» more  SIGMOD 2001»
15 years 10 months ago
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
HPDC
2007
IEEE
15 years 4 months ago
A fast topology inference: a building block for network-aware parallel processing
Adapting to the network is the key to achieving high performance for communication-intensive applications, including scientific computing, data intensive computing, and multicast...
Tatsuya Shirai, Hideo Saito, Kenjiro Taura
CVPR
2010
IEEE
15 years 29 days ago
Ray Markov Random Fields for Image-Based 3D Modeling: Model and Efficient Inference
In this paper, we present an approach to multi-view image-based 3D reconstruction by statistically inversing the ray-tracing based image generation process. The proposed algorithm...
Shubao Liu, David Cooper