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ACL
2004
13 years 9 months ago
Relieving the data Acquisition Bottleneck in Word Sense Disambiguation
Supervised learning methods for WSD yield better performance than unsupervised methods. Yet the availability of clean training data for the former is still a severe challenge. In ...
Mona T. Diab
ATAL
2008
Springer
13 years 9 months ago
Efficient multi-agent reinforcement learning through automated supervision
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in large-scale systems. In this work, we develop a supervision fr...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
CVPR
2010
IEEE
1135views Computer Vision» more  CVPR 2010»
14 years 3 months ago
Towards Weakly Supervised Semantic Segmentation by Means of Multiple Instance and Multitask Learning.
We address the task of learning a semantic segmentation from weakly supervised data. Our aim is to devise a system that predicts an object label for each pixel by making use of on...
Alexander Vezhnevets, Joachim Buhmann
CSL
2002
Springer
13 years 7 months ago
Lightly supervised and unsupervised acoustic model training
The last decade has witnessed substantial progress in speech recognition technology, with todays state-of-the-art systems being able to transcribe unrestricted broadcast news audi...
Lori Lamel, Jean-Luc Gauvain, Gilles Adda
COLING
1996
13 years 9 months ago
Unsupervised Discovery of Phonological Categories through Supervised Learning of Morphological Rules
We describe a case study in tit(', application of symbolic machinc learning techniques for the discow;ry of linguistic rules and categories. A supervised rule induction algor...
Walter Daelemans, Peter Berck, Steven Gillis