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SIGSOFT
2007
ACM
14 years 8 months ago
Recommending random walks
We improve on previous recommender systems by taking advantage of the layered structure of software. We use a random-walk approach, mimicking the more focused behavior of a develo...
Zachary M. Saul, Vladimir Filkov, Premkumar T. Dev...
KDD
2006
ACM
129views Data Mining» more  KDD 2006»
14 years 7 months ago
Suppressing model overfitting in mining concept-drifting data streams
Mining data streams of changing class distributions is important for real-time business decision support. The stream classifier must evolve to reflect the current class distributi...
Haixun Wang, Jian Yin, Jian Pei, Philip S. Yu, Jef...
WWW
2008
ACM
14 years 8 months ago
Optimal marketing strategies over social networks
We discuss the use of social networks in implementing viral marketing strategies. While influence maximization has been studied in this context (see Chapter 24 of [10]), we study ...
Jason D. Hartline, Vahab S. Mirrokni, Mukund Sunda...
SODA
2008
ACM
100views Algorithms» more  SODA 2008»
13 years 8 months ago
On allocations that maximize fairness
We consider a problem known as the restricted assignment version of the max-min allocation problem with indivisible goods. There are n items of various nonnegative values and m pl...
Uriel Feige
SODA
2001
ACM
79views Algorithms» more  SODA 2001»
13 years 8 months ago
Learning Markov networks: maximum bounded tree-width graphs
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
David R. Karger, Nathan Srebro