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ATAL
2011
Springer
12 years 10 months ago
Learning action models for multi-agent planning
In multi-agent planning environments, action models for each agent must be given as input. However, creating such action models by hand is difficult and time-consuming, because i...
Hankz Hankui Zhuo, Hector Muñoz-Avila, Qian...
IUI
2000
ACM
14 years 3 months ago
Learning to recommend from positive evidence
In recent years, many systems and approaches for recommending information, products or other objects have been developed. In these systems, often machine learning methods that nee...
Ingo Schwab, Wolfgang Pohl, Ivan Koychev
ACMICEC
2007
ACM
154views ECommerce» more  ACMICEC 2007»
14 years 2 months ago
Learning and adaptivity in interactive recommender systems
Recommender systems are intelligent E-commerce applications that assist users in a decision-making process by offering personalized product recommendations during an interaction s...
Tariq Mahmood, Francesco Ricci
NIPS
2001
14 years 3 days ago
Efficiency versus Convergence of Boolean Kernels for On-Line Learning Algorithms
The paper studies machine learning problems where each example is described using a set of Boolean features and where hypotheses are represented by linear threshold elements. One ...
Roni Khardon, Dan Roth, Rocco A. Servedio
NIPS
1994
14 years 1 days ago
Catastrophic Interference in Human Motor Learning
Biological sensorimotor systems are not static maps that transform input sensory information into output motor behavior. Evidence from many lines of research suggests that their r...
Tom Brashers-Krug, Reza Shadmehr, Emanuel Todorov