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» Learning to Apply Theory of Mind
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ICML
1994
IEEE
13 years 11 months ago
Learning Without State-Estimation in Partially Observable Markovian Decision Processes
Reinforcement learning (RL) algorithms provide a sound theoretical basis for building learning control architectures for embedded agents. Unfortunately all of the theory and much ...
Satinder P. Singh, Tommi Jaakkola, Michael I. Jord...
CVPR
2000
IEEE
14 years 9 months ago
Multimodal Speaker Detection Using Error Feedback Dynamic Bayesian Networks
Design and development of novel human-computer interfaces poses a challenging problem: actions and intentions of users have to be inferred from sequences of noisy and ambiguous mu...
Vladimir Pavlovic, James M. Rehg, Ashutosh Garg, T...
ISTCS
1997
Springer
13 years 11 months ago
Learning with Queries Corrupted by Classification Noise
Kearns introduced the "statistical query" (SQ) model as a general method for producing learning algorithms which are robust against classification noise. We extend this ...
Jeffrey C. Jackson, Eli Shamir, Clara Shwartzman
SYNTHESE
2010
157views more  SYNTHESE 2010»
13 years 6 months ago
Which empathy? Limitations in the mirrored "understanding" of emotion
The recent discovery of so-called “mirror-neurons” in monkeys and a corresponding mirroring “system” in humans has provoked wide endorsement of the claim that humans under...
Remy Debes
FOCS
1999
IEEE
13 years 12 months ago
Boosting and Hard-Core Sets
This paper connects two fundamental ideas from theoretical computer science: hard-core set construction, a type of hardness amplification from computational complexity, and boosti...
Adam Klivans, Rocco A. Servedio