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SIAMCOMP
2011
14 years 9 months ago
Self-Improving Algorithms
We investigate ways in which an algorithm can improve its expected performance by fine-tuning itself automatically with respect to an arbitrary, unknown input distribution. We gi...
Nir Ailon, Bernard Chazelle, Kenneth L. Clarkson, ...
APSEC
2000
IEEE
15 years 7 months ago
Transatlantic project courses in a university environment
Communication and collaboration is difficult in geographically distributed settings. As a result of globalization, merges and acquisition, and scarce skills, software development...
Bernd Brügge, Allen H. Dutoit, Rafael Kobylin...
179
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WWW
2010
ACM
15 years 9 months ago
Factorizing personalized Markov chains for next-basket recommendation
Recommender systems are an important component of many websites. Two of the most popular approaches are based on matrix factorization (MF) and Markov chains (MC). MF methods learn...
Steffen Rendle, Christoph Freudenthaler, Lars Schm...
152
Voted
LEGE
2003
107views Education» more  LEGE 2003»
15 years 4 months ago
Design Considerations for an ELeGI Portal
ELeGI, the European Learning Grid Infrastructure, has the ambitious goal of fostering effective learning and knowledge construction through the dynamic provision of service-based ...
Colin Allison, Rosa Michaelson
118
Voted
ICML
2004
IEEE
16 years 3 months ago
Approximate inference by Markov chains on union spaces
A standard method for approximating averages in probabilistic models is to construct a Markov chain in the product space of the random variables with the desired equilibrium distr...
Max Welling, Michal Rosen-Zvi, Yee Whye Teh