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BRAIN
2009
Springer
13 years 12 months ago
Reading What Machines "Think"
Abstract. In this paper, we want to farther advance the parallelism between models of the brain and computing machines. We want to apply the same idea underlying neuroimaging techn...
Fabio Massimo Zanzotto, Danilo Croce
LREC
2010
192views Education» more  LREC 2010»
13 years 6 months ago
The DARPA Machine Reading Program - Encouraging Linguistic and Reasoning Research with a Series of Reading Tasks
The goal of DARPA's Machine Reading (MR) program is nothing less than making the world's natural language corpora available for formal processing. Most text processing r...
Stephanie Strassel, Dan Adams, Henry Goldberg, Jon...
AAAI
2007
13 years 7 months ago
Learning by Reading: A Prototype System, Performance Baseline and Lessons Learned
A traditional goal of Artificial Intelligence research has been a system that can read unrestricted natural language texts on a given topic, build a model of that topic and reason...
Ken Barker, Bhalchandra Agashe, Shaw Yi Chaw, Jame...
JETAI
2010
56views more  JETAI 2010»
13 years 3 months ago
Warning: statistical benchmarking is addictive. Kicking the habit in machine learning
Algorithm performance evaluation is so entrenched in the Machine Learning community that one could call it an addiction. Like most addictions, it is harmful and very difficult to ...
Chris Drummond, Nathalie Japkowicz
CAV
2010
Springer
153views Hardware» more  CAV 2010»
13 years 9 months ago
There's Plenty of Room at the Bottom: Analyzing and Verifying Machine Code
This paper discusses the obstacles that stand in the way of doing a good job of machine-code analysis. Compared with analysis of source code, the challenge is to drop all assumptio...
Thomas W. Reps, Junghee Lim, Aditya V. Thakur, Gog...