Sciweavers

363 search results - page 22 / 73
» GraphLab: A New Framework for Parallel Machine Learning
Sort
View
JMLR
2006
186views more  JMLR 2006»
15 years 2 months ago
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Mikhail Belkin, Partha Niyogi, Vikas Sindhwani
112
Voted
AAAI
2008
15 years 4 months ago
Zero-data Learning of New Tasks
We introduce the problem of zero-data learning, where a model must generalize to classes or tasks for which no training data are available and only a description of the classes or...
Hugo Larochelle, Dumitru Erhan, Yoshua Bengio
116
Voted
ICPR
2004
IEEE
16 years 3 months ago
Relaxation Labeling Processes for Protein Secondary Structure Prediction
The prediction of protein secondary structure is a classical problem in bioinformatics, and in the past few years several machine learning techniques have been proposed to t. From...
Giacomo Colle, Marcello Pelillo
ICML
2005
IEEE
16 years 3 months ago
Reinforcement learning with Gaussian processes
Gaussian Process Temporal Difference (GPTD) learning offers a Bayesian solution to the policy evaluation problem of reinforcement learning. In this paper we extend the GPTD framew...
Yaakov Engel, Shie Mannor, Ron Meir
IEEEICCI
2003
IEEE
15 years 7 months ago
Conceptual Framework for Interactive Ontology Building
Abstract— An ontology is a formal language adequately representing the knowledge used for reasoning in a specific environment. When contradictions arise and make ontologies inad...
Jean Sallantin, Jacques Divol, Patrice Duroux