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AMEC
2004
Springer
14 years 26 days ago
Multi-attribute Bilateral Bargaining in a One-to-Many Setting
Negotiations are an important way of reaching agreements between selfish autonomous agents. In this paper we focus on one-to-many bargaining within the context of agent-mediated e...
Enrico H. Gerding, D. J. A. Somefun, Han La Poutr&...
AAAI
2010
13 years 9 months ago
Structure Learning for Markov Logic Networks with Many Descriptive Attributes
Many machine learning applications that involve relational databases incorporate first-order logic and probability. Markov Logic Networks (MLNs) are a prominent statistical relati...
Hassan Khosravi, Oliver Schulte, Tong Man, Xiaoyua...
SC
2009
ACM
14 years 2 months ago
Kestrel: an XMPP-based framework for many task computing applications
This paper presents a new distributed computing framework for Many Task Computing (MTC) applications, based on the Extensible Messaging and Presence Protocol (XMPP). A lightweight...
Lance Stout, Michael A. Murphy, Sebastien Goasguen
CIVR
2007
Springer
158views Image Analysis» more  CIVR 2007»
13 years 11 months ago
How many high-level concepts will fill the semantic gap in news video retrieval?
A number of researchers have been building high-level semantic concept detectors such as outdoors, face, building, etc., to help with semantic video retrieval. Using the TRECVID v...
Alexander G. Hauptmann, Rong Yan, Wei-Hao Lin
PPSN
2010
Springer
13 years 5 months ago
Feature Selection for Multi-purpose Predictive Models: A Many-Objective Task
The target of machine learning is a predictive model that performs well on unseen data. Often, such a model has multiple intended uses, related to different points in the tradeoff ...
Alan P. Reynolds, David W. Corne, Michael J. Chant...