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KDD
2010
ACM
218views Data Mining» more  KDD 2010»
15 years 10 months ago
Online multiscale dynamic topic models
We propose an online topic model for sequentially analyzing the time evolution of topics in document collections. Topics naturally evolve with multiple timescales. For example, so...
Tomoharu Iwata, Takeshi Yamada, Yasushi Sakurai, N...
PR
2007
146views more  PR 2007»
15 years 5 months ago
ML-KNN: A lazy learning approach to multi-label learning
Abstract: Multi-label learning originated from the investigation of text categorization problem, where each document may belong to several predefined topics simultaneously. In mul...
Min-Ling Zhang, Zhi-Hua Zhou
BMCBI
2007
137views more  BMCBI 2007»
15 years 6 months ago
Bayesian refinement of protein functional site matching
Background: Matching functional sites is a key problem for the understanding of protein function and evolution. The commonly used graph theoretic approach, and other related appro...
Kanti V. Mardia, Vysaul B. Nyirongo, Peter J. Gree...
TSMC
2008
132views more  TSMC 2008»
15 years 6 months ago
Ensemble Algorithms in Reinforcement Learning
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and fin...
Marco A. Wiering, Hado van Hasselt
ICCV
2011
IEEE
14 years 6 months ago
From Learning Models of Natural Image Patches to Whole Image Restoration
Learning good image priors is of utmost importance for the study of vision, computer vision and image processing applications. Learning priors and optimizing over whole images can...
Daniel Zoran, Yair Weiss