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JGO
2010
117views more  JGO 2010»
15 years 2 months ago
Machine learning problems from optimization perspective
Both optimization and learning play important roles in a system for intelligent tasks. On one hand, we introduce three types of optimization tasks studied in the machine learning l...
Lei Xu
ICALP
2001
Springer
15 years 8 months ago
On the Approximability of Average Completion Time Scheduling under Precedence Constraints
Abstract. We consider the scheduling problem of minimizing the average weighted job completion time on a single machine under precedence constraints. We show that this problem with...
Gerhard J. Woeginger
JMLR
2010
141views more  JMLR 2010»
14 years 11 months ago
FastInf: An Efficient Approximate Inference Library
The FastInf C++ library is designed to perform memory and time efficient approximate inference in large-scale discrete undirected graphical models. The focus of the library is pro...
Ariel Jaimovich, Ofer Meshi, Ian McGraw, Gal Elida...
132
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VTC
2008
IEEE
161views Communications» more  VTC 2008»
15 years 10 months ago
Evaluation of Outage Restricted Distributed MIMO Multi-Hop Networks by the Improved Approximative Power Allocation
—The concept of Virtual Antenna Array (VAA) is a promising approach to apply MIMO concepts in relaying systems. In order to fulfill a given Quality-of-Service (QoS) requirement ...
Dirk Wubben
DAGM
2008
Springer
15 years 5 months ago
Approximate Parameter Learning in Conditional Random Fields: An Empirical Investigation
We investigate maximum likelihood parameter learning in Conditional Random Fields (CRF) and present an empirical study of pseudo-likelihood (PL) based approximations of the paramet...
Filip Korc, Wolfgang Förstner