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ICML
2009
IEEE
16 years 5 months ago
BoltzRank: learning to maximize expected ranking gain
Ranking a set of retrieved documents according to their relevance to a query is a popular problem in information retrieval. Methods that learn ranking functions are difficult to o...
Maksims Volkovs, Richard S. Zemel
CAV
2009
Springer
135views Hardware» more  CAV 2009»
16 years 5 months ago
Sliding Window Abstraction for Infinite Markov Chains
Window Abstraction for Infinite Markov Chains Thomas A. Henzinger1 , Maria Mateescu1 , and Verena Wolf1,2 1 EPFL, Switzerland 2 Saarland University, Germany Abstract. We present an...
Thomas A. Henzinger, Maria Mateescu, Verena Wolf
ECIR
2009
Springer
16 years 1 months ago
Risk-Aware Information Retrieval
Probabilistic retrieval models usually rank documents based on a scalar quantity. However, such models lack any estimate for the uncertainty associated with a document’s rank. Fu...
Jianhan Zhu, Jun Wang, Michael J. Taylor, Ingemar ...
ICCAD
2004
IEEE
110views Hardware» more  ICCAD 2004»
16 years 1 months ago
Wire-length prediction using statistical techniques
We address the classic wire-length estimation problem and propose a new statistical wire-length estimation approach that captures the probability distribution function of net leng...
Jennifer L. Wong, Azadeh Davoodi, Vishal Khandelwa...
TMA
2010
Springer
212views Management» more  TMA 2010»
15 years 11 months ago
EmPath: Tool to Emulate Packet Transfer Characteristics in IP Network
The paper describes the EmPath tool that was designed to emulate packet transfer characteristics as delays and losses in IP network. The main innovation of this tool is its ability...
Jaroslaw Sliwinski, Andrzej Beben, Piotr Krawiec