We present a distributed machine learning framework based on support vector machines that allows classification problems to be solved iteratively through parallel update algorithm...
— This paper describes a robotic system that learns visual models of symmetric objects autonomously. Our robot learns by physically interacting with an object using its end effec...
The error-correcting output coding (ECOC) method reduces the multiclass learning problem into a series of binary classifiers. In this paper, we consider the dense ECOC methods, co...
Aijun Zhang, Zhi-Li Wu, Chun Hung Li, Kai-Tai Fang
The vision-based scene understanding technique that infers scene-interpreting contexts from real-world vision data has to not only deal with various uncertain environments but also...
We investigate the use of self-predicting neural networks for autonomous robot learning within noisy or partially predictable environments. A benchmark experiment is performed in ...
James B. Marshall, Neil K. Makhija, Zachary D. Rot...