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» Prediction on Spike Data Using Kernel Algorithms
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FLAIRS
2008
13 years 11 months ago
A Mixture Imputation-Boosted Collaborative Filter
Recommendation systems suggest products to users. Collaborative filtering (CF) systems, which base those recommendations on a database of previous ratings by various users and pro...
Xiaoyuan Su, Taghi M. Khoshgoftaar, Russell Greine...
SIGMOD
2009
ACM
215views Database» more  SIGMOD 2009»
14 years 9 months ago
Efficient type-ahead search on relational data: a TASTIER approach
Existing keyword-search systems in relational databases require users to submit a complete query to compute answers. Often users feel "left in the dark" when they have l...
Guoliang Li, Shengyue Ji, Chen Li, Jianhua Feng
JAIR
2002
163views more  JAIR 2002»
13 years 9 months ago
Efficient Reinforcement Learning Using Recursive Least-Squares Methods
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is main...
Xin Xu, Hangen He, Dewen Hu
KAIS
2010
144views more  KAIS 2010»
13 years 7 months ago
Boosting support vector machines for imbalanced data sets
Real world data mining applications must address the issue of learning from imbalanced data sets. The problem occurs when the number of instances in one class greatly outnumbers t...
Benjamin X. Wang, Nathalie Japkowicz
SIGIR
2009
ACM
14 years 3 months ago
Temporal collaborative filtering with adaptive neighbourhoods
Recommender Systems, based on collaborative filtering (CF), aim to accurately predict user tastes, by minimising the mean error achieved on hidden test sets of user ratings, afte...
Neal Lathia, Stephen Hailes, Licia Capra