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ECML
2006
Springer
14 years 6 days ago
Unsupervised Multiple-Instance Learning for Functional Profiling of Genomic Data
Multiple-instance learning (MIL) is a popular concept among the AI community to support supervised learning applications in situations where only incomplete knowledge is available....
Corneliu Henegar, Karine Clément, Jean-Dani...
NEUROSCIENCE
2001
Springer
14 years 29 days ago
Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources
We propose a theoretical framework for specification and analysis of a class of learning problems that arise in open-ended environments that contain multiple, distributed, dynamic...
Doina Caragea, Adrian Silvescu, Vasant Honavar
CVPR
2000
IEEE
14 years 28 days ago
Learning Patterns from Images by Combining Soft Decisions and Hard Decisions
We present a novel approach for learning patterns (sub-images) shared by multiple images without prior knowledge about the number and the positions of the patterns in the images. ...
Pengyu Hong, Thomas S. Huang, Roy Wang
DIS
2004
Springer
14 years 7 days ago
Extracting Positive Attributions from Scientific Papers
The aim of our work is to provide support for reading (or skimming) scientific papers. In this paper we report on the task to identify concepts or terms with positive attributions ...
Son Bao Pham, Achim G. Hoffmann
ATAL
2007
Springer
14 years 2 months ago
IFSA: incremental feature-set augmentation for reinforcement learning tasks
Reinforcement learning is a popular and successful framework for many agent-related problems because only limited environmental feedback is necessary for learning. While many algo...
Mazda Ahmadi, Matthew E. Taylor, Peter Stone