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NIPS
1998
15 years 8 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
INTERACT
2003
15 years 8 months ago
The Misapplication of Engineering Models to Business Decisions
: The HCI community has long been accused of delivering ‘common sense’, ‘useless’ information, and to be ignorant of business needs. HCI experts are also criticized for fai...
Gitte Lindgaard
DEBU
2006
163views more  DEBU 2006»
15 years 6 months ago
Towards Activity Databases: Using Sensors and Statistical Models to Summarize People's Lives
Automated reasoning about human behavior is a central goal of artificial intelligence. In order to engage and intervene in a meaningful way, an intelligent system must be able to ...
Tanzeem Choudhury, Matthai Philipose, Danny Wyatt,...
ALT
1998
Springer
15 years 11 months ago
Predictive Learning Models for Concept Drift
Concept drift means that the concept about which data is obtained may shift from time to time, each time after some minimum permanence. Except for this minimum permanence, the con...
John Case, Sanjay Jain, Susanne Kaufmann, Arun Sha...
EMNLP
2008
15 years 8 months ago
A Phrase-Based Alignment Model for Natural Language Inference
The alignment problem--establishing links between corresponding phrases in two related sentences--is as important in natural language inference (NLI) as it is in machine translati...
Bill MacCartney, Michel Galley, Christopher D. Man...