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WWW
2011
ACM
13 years 3 months ago
Learning to rank with multiple objective functions
We investigate the problem of learning to rank for document retrieval from the perspective of learning with multiple objective functions. We present solutions to two open problems...
Krysta Marie Svore, Maksims Volkovs, Christopher J...
CLEF
2005
Springer
14 years 2 months ago
CLEF 2005: Multilingual Retrieval by Combining Multiple Multilingual Ranked Lists
: We participated in two tasks: Multi-8 two-years-on retrieval and Multi-8 results merging. For our multi-8 two-years-on retrieval work, simple multilingual ranked lists are first ...
Luo Si, Jamie Callan
NIPS
2003
13 years 10 months ago
Log-Linear Models for Label Ranking
Label ranking is the task of inferring a total order over a predefined set of labels for each given instance. We present a general framework for batch learning of label ranking f...
Ofer Dekel, Christopher D. Manning, Yoram Singer
CDC
2008
IEEE
145views Control Systems» more  CDC 2008»
13 years 8 months ago
Necessary and sufficient conditions for success of the nuclear norm heuristic for rank minimization
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in control theory, machine learning, and discrete geometry. This c...
Benjamin Recht, Weiyu Xu, Babak Hassibi
EOR
2008
99views more  EOR 2008»
13 years 8 months ago
Ordinal regression revisited: Multiple criteria ranking using a set of additive value functions
We present a new method, called UTAGMS , for multiple criteria ranking of alternatives from set A using a set of additive value functions which result from an ordinal regression. ...
Salvatore Greco, Vincent Mousseau, Roman Slowinski