Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing)
Decision trees for entity identification: approximation algorithms and hardness results
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Importance weighted active learning
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Teaching dimension and the complexity of active learning
COLT'07 Proceedings of the 20th annual conference on Learning theory
Approximation algorithms for optimal decision trees and adaptive TSP problems
ICALP'10 Proceedings of the 37th international colloquium conference on Automata, languages and programming
Adaptive submodularity: theory and applications in active learning and stochastic optimization
Journal of Artificial Intelligence Research
InSite: QoE-aware video delivery from cloud data centers
Proceedings of the 2012 IEEE 20th International Workshop on Quality of Service
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We analyze the expected cost of a greedy active learning algorithm. Our analysis extends previous work to a more general setting in which different queries have different costs. Moreover, queries may have more than two possible responses and the distribution over hypotheses may be non uniform. Specific applications include active learning with label costs, active learning for multiclass and partial label queries, and batch mode active learning. We also discuss an approximate version of interest when there are very many queries.