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ECIR
2011
Springer
14 years 8 months ago
Balancing Exploration and Exploitation in Learning to Rank Online
Abstract. As retrieval systems become more complex, learning to rank approaches are being developed to automatically tune their parameters. Using online learning to rank approaches...
Katja Hofmann, Shimon Whiteson, Maarten de Rijke
JMLR
2012
13 years 7 months ago
Globally Optimizing Graph Partitioning Problems Using Message Passing
Graph partitioning algorithms play a central role in data analysis and machine learning. Most useful graph partitioning criteria correspond to optimizing a ratio between the cut a...
Elad Mezuman, Yair Weiss
CVPR
2009
IEEE
1081views Computer Vision» more  CVPR 2009»
17 years 6 days ago
Learning Real-Time MRF Inference for Image Denoising
Many computer vision problems can be formulated in a Bayesian framework with Markov Random Field (MRF) or Conditional Random Field (CRF) priors. Usually, the model assumes that ...
Adrian Barbu (Florida State University)
ICML
2008
IEEE
16 years 5 months ago
Training SVM with indefinite kernels
Similarity matrices generated from many applications may not be positive semidefinite, and hence can't fit into the kernel machine framework. In this paper, we study the prob...
Jianhui Chen, Jieping Ye
WWW
2004
ACM
16 years 5 months ago
PipeCF: a scalable DHT-based collaborative filtering recommendation system
Collaborative Filtering (CF) technique has proved to be one of the most successful techniques in recommendation systems in recent years. However, traditional centralized CF system...
Bo Xie, Peng Han, Ruimin Shen