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» On learning with dissimilarity functions
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NIPS
2004
15 years 8 months ago
Log-concavity Results on Gaussian Process Methods for Supervised and Unsupervised Learning
Log-concavity is an important property in the context of optimization, Laplace approximation, and sampling; Bayesian methods based on Gaussian process priors have become quite pop...
Liam Paninski
IJCAI
1997
15 years 8 months ago
Learning Short-Term Weights for GSAT
We investigate an improvement to GSAT which associates a weight with each clause. We change the objective function so that GSAT moves to assignments maximizing the weight of satis...
Jeremy Frank
IEEECIT
2010
IEEE
15 years 5 months ago
A Learning Spectrum Hole Prediction Model for Cognitive Radio Systems
—In this paper, we present a new spectrum-hole prediction model for cognitive radio (CR) systems based on the IEEE 802.11 wireless local areas networks. We have also analyzed the...
Zhigang Wen, Chunxiao Fan, Xiaoying Zhang, Yuexin ...
RECSYS
2010
ACM
15 years 4 months ago
List-wise learning to rank with matrix factorization for collaborative filtering
A ranking approach, ListRank-MF, is proposed for collaborative filtering that combines a list-wise learning-to-rank algorithm with matrix factorization (MF). A ranked list of item...
Yue Shi, Martha Larson, Alan Hanjalic
191
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ICML
2008
IEEE
16 years 7 months ago
Predicting diverse subsets using structural SVMs
In many retrieval tasks, one important goal involves retrieving a diverse set of results (e.g., documents covering a wide range of topics for a search query). First of all, this r...
Yisong Yue, Thorsten Joachims