Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
The structure-mapping engine: algorithm and examples
Artificial Intelligence
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Automated Refinement of First-Order Horn-Clause Domain Theories
Machine Learning
Machine Learning - Special issue on inductive transfer
Learning to extract symbolic knowledge from the World Wide Web
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Theory Refinement of Bayesian Networks with Hidden Variables
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Learning the structure of Markov logic networks
ICML '05 Proceedings of the 22nd international conference on Machine learning
Machine Learning
Constructing informative priors using transfer learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
Transfer via inter-task mappings in policy search reinforcement learning
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Sound and efficient inference with probabilistic and deterministic dependencies
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Learning and transferring action schemas
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Using advice to transfer knowledge acquired in one reinforcement learning task to another
ECML'05 Proceedings of the 16th European conference on Machine Learning
Probabilistic first-order theory revision from examples
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Learning to assign degrees of belief in relational domains
Machine Learning
Structured machine learning: the next ten years
Machine Learning
Transfer Learning by Mapping and Revising Relational Knowledge
SBIA '08 Proceedings of the 19th Brazilian Symposium on Artificial Intelligence: Advances in Artificial Intelligence
Transferring Knowledge from Another Domain for Learning Action Models
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
On universal transfer learning
Theoretical Computer Science
Transfer Learning Action Models by Measuring the Similarity of Different Domains
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Deep transfer via second-order Markov logic
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Learning directed probabilistic logical models: ordering-search versus structure-search
Annals of Mathematics and Artificial Intelligence
Cross-domain activity recognition
Proceedings of the 11th international conference on Ubiquitous computing
A risk minimization framework for domain adaptation
Proceedings of the 18th ACM conference on Information and knowledge management
Transfer learning from minimal target data by mapping across relational domains
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Expert Systems with Applications: An International Journal
Video summarization via transferrable structured learning
Proceedings of the 20th international conference on World wide web
Cross-domain activity recognition via transfer learning
Pervasive and Mobile Computing
Localized factor models for multi-context recommendation
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Multi-view transfer learning with a large margin approach
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Online structure learning for Markov logic networks
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
Sentiment detection with auxiliary data
Information Retrieval
Lifted online training of relational models with stochastic gradient methods
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
Budgeted knowledge transfer for state-wise heterogeneous RL agents
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part I
Exploiting persistent mappings in cross-domain analogical learning of physical domains
Artificial Intelligence
Double-bootstrapping source data selection for instance-based transfer learning
Pattern Recognition Letters
| Hi-index | 0.00 |
Transfer learning addresses the problem of how to leverage knowledge acquired in a source domain to improve the accuracy and speed of learning in a related target domain. This paper considers transfer learning with Markov logic networks (MLNs), a powerful formalism for learning in relational domains. We present a complete MLN transfer system that first autonomously maps the predicates in the source MLN to the target domain and then revises the mapped structure to further improve its accuracy. Our results in several real-world domains demonstrate that our approach successfully reduces the amount of time and training data needed to learn an accurate model of a target domain over learning from scratch.