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» Combined regression and ranking
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SIGIR
2009
ACM
14 years 4 months ago
Reciprocal rank fusion outperforms condorcet and individual rank learning methods
Reciprocal Rank Fusion (RRF), a simple method for combining the document rankings from multiple IR systems, consistently yields better results than any individual system, and bett...
Gordon V. Cormack, Charles L. A. Clarke, Stefan B&...
ICMLA
2009
13 years 7 months ago
Discovering Characterization Rules from Rankings
For many ranking applications we would like to understand not only which items are top-ranked, but also why they are top-ranked. However, many of the best ranking algorithms (e.g....
Ansaf Salleb-Aouissi, Bert C. Huang, David L. Walt...
TIT
2008
109views more  TIT 2008»
13 years 9 months ago
Statistical Analysis of Bayes Optimal Subset Ranking
Abstract--The ranking problem has become increasingly important in modern applications of statistical methods in automated decision making systems. In particular, we consider a for...
David Cossock, Tong Zhang
STOC
2009
ACM
133views Algorithms» more  STOC 2009»
14 years 10 months ago
Numerical linear algebra in the streaming model
We give near-optimal space bounds in the streaming model for linear algebra problems that include estimation of matrix products, linear regression, low-rank approximation, and app...
Kenneth L. Clarkson, David P. Woodruff
RECOMB
2006
Springer
14 years 10 months ago
Probabilistic Paths for Protein Complex Inference
Understanding how individual proteins are organized into complexes and pathways is a significant current challenge. We introduce new algorithms to infer protein complexes by combin...
Hailiang Huang, Lan V. Zhang, Frederick P. Roth, J...