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AAAI
2008
15 years 8 months ago
Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
Hirotaka Hachiya, Takayuki Akiyama, Masashi Sugiya...
NIPS
2007
15 years 7 months ago
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation
A situation where training and test samples follow different input distributions is called covariate shift. Under covariate shift, standard learning methods such as maximum likeli...
Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashi...
CERA
2004
93views more  CERA 2004»
15 years 6 months ago
Virtual-Build-to-Order as a Mass Customization Order Fulfilment Model
: Virtual-build-to-order (VBTO) is a form of order fulfilment system in which the producer has the ability to search across the entire pipeline of finished stock, products in produ...
Philip G. Brabazon, Bart L. MacCarthy
QSHINE
2005
IEEE
15 years 11 months ago
A Per-Class QoS Service Model in IEEE 802.11e WLANs
Abstract -- In this paper, we study the provision of perclass QoS for IEEE 802.11e Enhanced Distributed Channel Access (EDCA) WLANs. We propose two mechanisms, called BIWF-SP and I...
Jeng Farn Lee, Wanjiun Liao, Meng Chang Chen
ACMICEC
2008
ACM
272views ECommerce» more  ACMICEC 2008»
15 years 8 months ago
Adapting the interaction state model in conversational recommender systems
Conventional conversational recommender systems support interaction strategies that are hard-coded into the system in advance. In this context, Reinforcement Learning techniques h...
Tariq Mahmood, Francesco Ricci