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» Approximate algorithms for neural-Bayesian approaches
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KDD
2003
ACM
269views Data Mining» more  KDD 2003»
15 years 10 months ago
Maximizing the spread of influence through a social network
Models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains, including the diffusion of medical and technolog...
David Kempe, Jon M. Kleinberg, Éva Tardos
80
Voted
ICCV
2005
IEEE
15 years 3 months ago
KALMANSAC: Robust Filtering by Consensus
We propose an algorithm to perform causal inference of the state of a dynamical model when the measurements are corrupted by outliers. While the optimal (maximumlikelihood) soluti...
Andrea Vedaldi, Hailin Jin, Paolo Favaro, Stefano ...
DATAMINE
2006
142views more  DATAMINE 2006»
14 years 10 months ago
Sequential Pattern Mining in Multi-Databases via Multiple Alignment
To efficiently find global patterns from a multi-database, information in each local database must first be mined and summarized at the local level. Then only the summarized infor...
Hye-Chung Kum, Joong Hyuk Chang, Wei Wang 0010
75
Voted
PRL
2008
118views more  PRL 2008»
14 years 9 months ago
Bayes Machines for binary classification
In this work we propose an approach to binary classification based on an extension of Bayes Point Machines. Particularly, we take into account the whole set of hypotheses that are...
Daniel Hernández-Lobato, José Miguel...
VLDB
2007
ACM
145views Database» more  VLDB 2007»
15 years 10 months ago
LCS-TRIM: Dynamic Programming Meets XML Indexing and Querying
In this article, we propose a new approach for querying and indexing a database of trees with specific applications to XML datasets. Our approach relies on representing both the q...
Shirish Tatikonda, Srinivasan Parthasarathy, Matth...