We take various kinds of training and learning. When taking these various kinds of training and learning, haw can they be done most efficiently and effciently? This problem was taken up in order to disover in the process of seqential learning and training a rule make this process more efficient and effective. Referring to R. R Bush and F. Mosteller's method in which the process of learning and training is considered as stochastic process, we have made a study of sequential learning using eye measurement. A segment 30 cm long was drawn for 85 second grade elementaly school children ; on this they were asked to mark a plasce 10cm from one end. This learning was continued once every other day for 18 days. As the result of this sequential learn...
We consider the problem of sequential prediction and provide tools to study the minimax value of the...
The adaptive process in motor learning was examined in terms of effects of varying amounts of consta...
Sequential Learning is a framework that was created for statistical learning problems where (Yt) , t...
In education there are many occasions when sequential learning is put into use. On such an occasion ...
The paper presents a stochastic method of optimization of a curriculum based on a new model of the e...
To investigate a human sequential learning Nissen & Bullemer (1987) developed a serial reaction time...
This report points out the role of sequences of samples for training an incremental learn-ing method...
Learning sequential actions is an essential ability, for most daily activities are sequential. We mo...
We apply PAC-Bayesian theory to prove a generalization bound for the case of sequential task solving...
A helpful teacher can significantly improve the learning rate of a learning agent. Teaching algorith...
The purpose of this paper is to derive optimal rules for sequential decision-making in intelligent t...
Sequential learning is a fundamental function of an intelligent agent. This technical report introdu...
Sequential prediction problems arise commonly in many areas of robotics and information processing: ...
Contains fulltext : 191807.pdf (publisher's version ) (Open Access)Sequential acti...
This paper is concerned with training an agent to perform sequential behavior. In previous work we h...
We consider the problem of sequential prediction and provide tools to study the minimax value of the...
The adaptive process in motor learning was examined in terms of effects of varying amounts of consta...
Sequential Learning is a framework that was created for statistical learning problems where (Yt) , t...
In education there are many occasions when sequential learning is put into use. On such an occasion ...
The paper presents a stochastic method of optimization of a curriculum based on a new model of the e...
To investigate a human sequential learning Nissen & Bullemer (1987) developed a serial reaction time...
This report points out the role of sequences of samples for training an incremental learn-ing method...
Learning sequential actions is an essential ability, for most daily activities are sequential. We mo...
We apply PAC-Bayesian theory to prove a generalization bound for the case of sequential task solving...
A helpful teacher can significantly improve the learning rate of a learning agent. Teaching algorith...
The purpose of this paper is to derive optimal rules for sequential decision-making in intelligent t...
Sequential learning is a fundamental function of an intelligent agent. This technical report introdu...
Sequential prediction problems arise commonly in many areas of robotics and information processing: ...
Contains fulltext : 191807.pdf (publisher's version ) (Open Access)Sequential acti...
This paper is concerned with training an agent to perform sequential behavior. In previous work we h...
We consider the problem of sequential prediction and provide tools to study the minimax value of the...
The adaptive process in motor learning was examined in terms of effects of varying amounts of consta...
Sequential Learning is a framework that was created for statistical learning problems where (Yt) , t...