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ICML
2004
IEEE
16 years 7 months ago
Learning associative Markov networks
Markov networks are extensively used to model complex sequential, spatial, and relational interactions in fields as diverse as image processing, natural language analysis, and bio...
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
ECML
1991
Springer
15 years 10 months ago
Learning by Analogical Replay in PRODIGY: First Results
Robust reasoning requires learning from problem solving episodes. Past experience must be compiled to provide adaptation to new contingencies and intelligent modification of solut...
Manuela M. Veloso, Jaime G. Carbonell
ICML
2010
IEEE
15 years 7 months ago
Gaussian Processes Multiple Instance Learning
This paper proposes a multiple instance learning (MIL) algorithm for Gaussian processes (GP). The GP-MIL model inherits two crucial benefits from GP: (i) a principle manner of lea...
Minyoung Kim, Fernando De la Torre
ICML
2005
IEEE
16 years 7 months ago
A model for handling approximate, noisy or incomplete labeling in text classification
We introduce a Bayesian model, BayesANIL, that is capable of estimating uncertainties associated with the labeling process. Given a labeled or partially labeled training corpus of...
Ganesh Ramakrishnan, Krishna Prasad Chitrapura, Ra...
ICST
2009
IEEE
16 years 1 months ago
A Model Building Process for Identifying Actionable Static Analysis Alerts
Automated static analysis can identify potential source code anomalies early in the software process that could lead to field failures. However, only a small portion of static ana...
Sarah Smith Heckman, Laurie A. Williams