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KDD
2004
ACM
117views Data Mining» more  KDD 2004»
16 years 7 months ago
Regularized multi--task learning
Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks...
Theodoros Evgeniou, Massimiliano Pontil
AAAI
2008
15 years 9 months ago
A Case Study on the Critical Role of Geometric Regularity in Machine Learning
An important feature of many problem domains in machine learning is their geometry. For example, adjacency relationships, symmetries, and Cartesian coordinates are essential to an...
Jason Gauci, Kenneth O. Stanley
IJCAI
1989
15 years 7 months ago
Coping With Uncertainty in Map Learning
In many applications in mobile robotics, it is important for a robot to explore its environment in order to construct a representation of space useful for guiding movement. We refe...
Kenneth Basye, Thomas Dean, Jeffrey Scott Vitter
ROBOCUP
2005
Springer
96views Robotics» more  ROBOCUP 2005»
16 years 4 days ago
Self Task Decomposition for Modular Learning System Through Interpretation of Instruction by Coach
One of the most formidable issues of RL application to real robot tasks is how to find a suitable state space, and this has been much more serious since recent robots tends to hav...
Yasutake Takahashi, Tomoki Nishi, Minoru Asada
ICPR
2010
IEEE
15 years 4 months ago
An Efficient and Stable Algorithm for Learning Rotations
This paper analyses the computational complexity and stability of an online algorithm recently proposed for learning rotations. The proposed algorithm involves multiplicative upda...
Raman Arora, William A. Sethares