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» Bootstrap learning of foundational representations
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ATAL
2009
Springer
14 years 2 months ago
MABLE: a framework for learning from natural instruction
The Modular Architecture for Bootstrapped Learning Experiments (MABLE) is a system that is being developed to allow humans to teach computers in the most natural manner possible: ...
Roger Mailler, Daniel Bryce, Jiaying Shen, Ciaran ...
AAAI
2000
13 years 8 months ago
Self-Supervised Learning for Visual Tracking and Recognition of Human Hand
Due to the large variation and richness of visual inputs, statistical learning gets more and more concerned in the practice of visual processing such as visual tracking and recogn...
Ying Wu, Thomas S. Huang
ICML
2000
IEEE
14 years 8 months ago
Classification of Individuals with Complex Structure
This paper introduces a foundation for inductive learning based on the use of higher-order logic for knowledge representation. In particular, the paper (i) provides a systematic i...
Antony F. Bowers, Christophe G. Giraud-Carrier, Jo...
ICRA
2007
IEEE
189views Robotics» more  ICRA 2007»
14 years 1 months ago
Context Estimation and Learning Control through Latent Variable Extraction: From discrete to continuous contexts
— Recent advances in machine learning and adaptive motor control have enabled efficient techniques for online learning of stationary plant dynamics and it’s use for robust pre...
Georgios Petkos, Sethu Vijayakumar
ACL
2007
13 years 9 months ago
A Seed-driven Bottom-up Machine Learning Framework for Extracting Relations of Various Complexity
A minimally supervised machine learning framework is described for extracting relations of various complexity. Bootstrapping starts from a small set of n-ary relation instances as...
Feiyu Xu, Hans Uszkoreit, Hong Li