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ICML
2005
IEEE
16 years 7 months ago
Hierarchic Bayesian models for kernel learning
The integration of diverse forms of informative data by learning an optimal combination of base kernels in classification or regression problems can provide enhanced performance w...
Mark Girolami, Simon Rogers
NIPS
2003
15 years 7 months ago
Learning with Local and Global Consistency
We consider the general problem of learning from labeled and unlabeled data, which is often called semi-supervised learning or transductive inference. A principled approach to sem...
Dengyong Zhou, Olivier Bousquet, Thomas Navin Lal,...
ACL
1998
15 years 7 months ago
Trainable, Scalable Summarization Using Robust NLP and Machine Learning
We describe a trainable and scalable summarization system which utilizes features derived from information retrieval, information extraction, and NLP techniques and on-line resour...
Chinatsu Aone, Mary Ellen Okurowski, James Gorlins...
CRV
2009
IEEE
115views Robotics» more  CRV 2009»
16 years 1 months ago
Learning Model Complexity in an Online Environment
In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification pro...
Dan Levi, Shimon Ullman
SAB
2010
Springer
156views Optimization» more  SAB 2010»
15 years 4 months ago
Attentional Mechanisms for Lateral Line Sensing through Spectral Analysis
Abstract. For autonomy in underwater robotics it is essential to develop context-driven controllers, capable of leading from perception to action without human intervention. One of...
Otar Akanyeti, Maria-Camilla Fiazza, Paolo Fiorini