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PERSUASIVE
2009
Springer
16 years 1 months ago
A behavior model for persuasive design
This paper presents a new model for understanding human behavior. In this model (FBM), behavior is a product of three factors: motivation, ability, and triggers, each of which has...
B. J. Fogg
IJCAI
2007
15 years 8 months ago
A Theoretical Framework for Learning Bayesian Networks with Parameter Inequality Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
NIPS
1992
15 years 7 months ago
Explanation-Based Neural Network Learning for Robot Control
How can artificial neural nets generalize better from fewer examples? In order to generalize successfully, neural network learning methods typically require large training data se...
Tom M. Mitchell, Sebastian Thrun
CIDR
2009
152views Algorithms» more  CIDR 2009»
15 years 7 months ago
Visualizing the robustness of query execution
In database query processing, actual run-time conditions (e.g., actual selectivities and actual available memory) very often differ from compile-time expectations of run-time cond...
Goetz Graefe, Harumi A. Kuno, Janet L. Wiener
IJCAI
1989
15 years 7 months ago
A Critique of the Valiant Model
This paper considers the Valiant framework as it is applied to the task of learning logical concepts from random examples. It is argued that the current interpretation of this Val...
Wray L. Buntine