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AAAI
2007
15 years 9 months ago
Active Imitation Learning
Imitation learning, also called learning by watching or programming by demonstration, has emerged as a means of accelerating many reinforcement learning tasks. Previous work has s...
Aaron P. Shon, Deepak Verma, Rajesh P. N. Rao
TLT
2010
90views more  TLT 2010»
15 years 5 months ago
To Flow and Not to Freeze: Applying Flow Experience to Mobile Learning
— A key design goal of mobile learning is that its built-in experiences are enjoyable and proactive, empowering the learner with the knowledge and ability to self-manage. This im...
Jungho Park, David Parsons, Hokyoung Ryu
MP
2002
48views more  MP 2002»
15 years 6 months ago
Maximum stable set formulations and heuristics based on continuous optimization
The stability number (G) for a given graph G is the size of a maximum stable set in G. The Lov
Samuel Burer, Renato D. C. Monteiro, Yin Zhang
GECCO
2009
Springer
151views Optimization» more  GECCO 2009»
16 years 1 months ago
Swarming to rank for information retrieval
This paper presents an approach to automatically optimize the retrieval quality of ranking functions. Taking a Swarm Intelligence perspective, we present a novel method, SwarmRank...
Ernesto Diaz-Aviles, Wolfgang Nejdl, Lars Schmidt-...
CEC
2008
IEEE
16 years 1 months ago
Improved Particle Swarm Optimization with low-discrepancy sequences
— Quasirandom or low discrepancy sequences, such as the Van der Corput, Sobol, Faure, Halton (named after their inventors) etc. are less random than a pseudorandom number sequenc...
Millie Pant, Radha Thangaraj, Crina Grosan, Ajith ...