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CHI
2010
ACM
15 years 8 months ago
Examining multiple potential models in end-user interactive concept learning
End-user interactive concept learning is a technique for interacting with large unstructured datasets, requiring insights from both human-computer interaction and machine learning...
Saleema Amershi, James Fogarty, Ashish Kapoor, Des...
JCP
2007
92views more  JCP 2007»
15 years 1 months ago
Lifelong Learning, Empirical Modelling and the Promises of Constructivism
—Educational technology is seen as key for lifelong learning, but it has yet to live up to expectation. We argue that current learning environments are typically oriented too muc...
Meurig Beynon, Antony Harfield
ICMLA
2009
14 years 11 months ago
Automatic Feature Selection for Model-Based Reinforcement Learning in Factored MDPs
Abstract--Feature selection is an important challenge in machine learning. Unfortunately, most methods for automating feature selection are designed for supervised learning tasks a...
Mark Kroon, Shimon Whiteson
ICML
2005
IEEE
16 years 2 months ago
Learning structured prediction models: a large margin approach
Benjamin Taskar, Vassil Chatalbashev, Daphne Kolle...
AIIDE
2008
15 years 3 months ago
Combining Model-Based Meta-Reasoning and Reinforcement Learning for Adapting Game-Playing Agents
Human experience with interactive games will be enhanced if the software agents that play the game learn from their failures. Techniques such as reinforcement learning provide one...
Patrick Ulam, Joshua Jones, Ashok K. Goel