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COLT
2006
Springer
15 years 8 months ago
Online Learning with Constraints
In this paper, we study a sequential decision making problem. The objective is to maximize the total reward while satisfying constraints, which are defined at every time step. The...
Shie Mannor, John N. Tsitsiklis
AAAI
2008
15 years 7 months ago
Learning to Connect Language and Perception
To truly understand language, an intelligent system must be able to connect words, phrases, and sentences to its perception of objects and events in the world. Current natural lan...
Raymond J. Mooney
APPROX
2008
Springer
101views Algorithms» more  APPROX 2008»
15 years 7 months ago
Learning Random Monotone DNF
We give an algorithm that with high probability properly learns random monotone DNF with t(n) terms of length log t(n) under the uniform distribution on the Boolean cube {0, 1}n ....
Jeffrey C. Jackson, Homin K. Lee, Rocco A. Servedi...
ESANN
2007
15 years 6 months ago
Kernel-based online machine learning and support vector reduction
We apply kernel-based machine learning methods to online learning situations, and look at the related requirement of reducing the complexity of the learnt classifier. Online meth...
Sumeet Agarwal, V. Vijaya Saradhi, Harish Karnick
137
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NAACL
2007
15 years 6 months ago
Using "Annotator Rationales" to Improve Machine Learning for Text Categorization
We propose a new framework for supervised machine learning. Our goal is to learn from smaller amounts of supervised training data, by collecting a richer kind of training data: an...
Omar Zaidan, Jason Eisner, Christine D. Piatko