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AAAI
2011
12 years 7 months ago
Coarse-to-Fine Inference and Learning for First-Order Probabilistic Models
Coarse-to-fine approaches use sequences of increasingly fine approximations to control the complexity of inference and learning. These techniques are often used in NLP and visio...
Chloe Kiddon, Pedro Domingos
AAAI
2011
12 years 7 months ago
Heterogeneous Transfer Learning with RBMs
A common approach in machine learning is to use a large amount of labeled data to train a model. Usually this model can then only be used to classify data in the same feature spac...
Bin Wei, Christopher Pal
ATAL
2006
Springer
13 years 11 months ago
Solving POMDPs using quadratically constrained linear programs
Developing scalable algorithms for solving partially observable Markov decision processes (POMDPs) is an important challenge. One promising approach is based on representing POMDP...
Christopher Amato, Daniel S. Bernstein, Shlomo Zil...
ECAI
2004
Springer
13 years 11 months ago
Goal Specification in Presence of Non-Deterministic Actions
One important aspect in directing cognitive robots or agents is to formally specify what is expected of them. This is often referred to as goal specification. For agents whose act...
Chitta Baral, Jicheng Zhao
AAAI
2007
13 years 10 months ago
Supporting Feedback and Assessment of Digital Ink Answers to In-Class Exercises
Effective teaching involves treating the presentation of new material and the assessment of students’ mastery of this material as part of a seamless and continuous feedback cycl...
Kimberle Koile, Kevin Chevalier, Michel Rbeiz, Ada...