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» Learning Finite Automata Using Label Queries
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AAAI
2011
12 years 7 months ago
Markov Logic Sets: Towards Lifted Information Retrieval Using PageRank and Label Propagation
Inspired by “GoogleTM Sets” and Bayesian sets, we consider the problem of retrieving complex objects and relations among them, i.e., ground atoms from a logical concept, given...
Marion Neumann, Babak Ahmadi, Kristian Kersting
COLT
1994
Springer
13 years 11 months ago
An Optimal Parallel Algorithm for Learning DFA
: Sequential algorithms given by Angluin 1987 and Schapire 1992 learn deterministic nite automata DFA exactly from Membership and Equivalence queries. These algorithms are feasible...
José L. Balcázar, Josep Díaz,...
SDM
2010
SIAM
144views Data Mining» more  SDM 2010»
13 years 8 months ago
A Probabilistic Framework to Learn from Multiple Annotators with Time-Varying Accuracy
This paper addresses the challenging problem of learning from multiple annotators whose labeling accuracy (reliability) differs and varies over time. We propose a framework based ...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider
PKDD
2010
Springer
164views Data Mining» more  PKDD 2010»
13 years 5 months ago
Complexity Bounds for Batch Active Learning in Classification
Active learning [1] is a branch of Machine Learning in which the learning algorithm, instead of being directly provided with pairs of problem instances and their solutions (their l...
Philippe Rolet, Olivier Teytaud
KDD
2008
ACM
207views Data Mining» more  KDD 2008»
14 years 7 months ago
Active learning with direct query construction
Active learning may hold the key for solving the data scarcity problem in supervised learning, i.e., the lack of labeled data. Indeed, labeling data is a costly process, yet an ac...
Charles X. Ling, Jun Du