COLT
2010
Springer
13 years 2 months ago
2010
Springer
Bandit convex optimization is a special case of online convex optimization with partial information. In this setting, a player attempts to minimize a sequence of adversarially gen...
AI
2006
Springer
13 years 4 months ago
2006
Springer
In many situations, a set of hard constraints encodes the feasible configurations of some system or product over which multiple users have distinct preferences. However, making su...
IJCAI
2003
13 years 6 months ago
2003
Utility elicitation is a critical function of any automated decision aid, allowing decisions to be tailored to the preferences of a specific user. However, the size and complexit...
AAAI
2010
13 years 6 months ago
2010
The precise specification of reward functions for Markov decision processes (MDPs) is often extremely difficult, motivating research into both reward elicitation and the robust so...
CDC
2009
IEEE
13 years 9 months ago
2009
IEEE
— We consider decision making in a Markovian setup where the reward parameters are not known in advance. Our performance criterion is the gap between the performance of the best ...
SIGECOM
2010
ACM
13 years 9 months ago
2010
ACM
Product recommendation and decision support systems must generally develop a model of user preferences by querying or otherwise interacting with a user. Recent approaches to elici...
RECSYS
2009
ACM
13 years 11 months ago
2009
ACM
Utility or preference elicitation is a critical component in many recommender and decision support systems. However, most frameworks for elicitation assume a predefined set of fe...