Add to ORKGThis paper presents initial results of modeling human behavior with a novel algorithm that creates human behavior models automatically by observing human performance. However, these results together with conclusions from the No Free Lunch Theorems signify the scalability of the modeling algorithm. The implication from the No Free Lunch Theorems also indicates how applicable or scalable a machine learning algorithm might be, applied to a new real world problem. Furthermore, the results are universal and might be applicable to many related areas of automatic modeling
In recent years there has been an increased interest in the modelling and recognition of human activ...
Thesis (Ph. D.)--University of Rochester. Dept. of Computer Science, 2012.Until recently, complex ph...
This paper focuses on the creation and presentation of a user-friendly experience for developing com...
This paper presents initial results of modeling human behavior with a novel algorithm that creates h...
In this era of big data, massive data are generated from heterogeneous resources every day, which pr...
Abstract: Machine Learning generates programs that make predictions and informed decisions about com...
The tools we use have a great impact on our productivity. It is imperative that tools are designed w...
Learning Analytics (LA) has a major interest in exploring and understanding the learning process of ...
This paper presents a sandbox example of how the integration of models borrowed from Behavioral Econ...
A sizable amount of research has been done to improve the mechanisms for knowledge extraction such a...
Model-free (MF) reinforcement learning (RL) algorithms account for a wealth of neuroscientific and b...
Machine learning (ML), a computational self-learning platform, is expected to be applied in a variet...
The No Free Lunch (NFL) Theorem imposes a theoretical restriction on optimization algorithms and the...
We are approaching a future where robots and humans will co-exist and co-adapt. To understand how ca...
The concept of human behavior recognition is an interesting yet daunting task to delve into. This pa...
In recent years there has been an increased interest in the modelling and recognition of human activ...
Thesis (Ph. D.)--University of Rochester. Dept. of Computer Science, 2012.Until recently, complex ph...
This paper focuses on the creation and presentation of a user-friendly experience for developing com...
This paper presents initial results of modeling human behavior with a novel algorithm that creates h...
In this era of big data, massive data are generated from heterogeneous resources every day, which pr...
Abstract: Machine Learning generates programs that make predictions and informed decisions about com...
The tools we use have a great impact on our productivity. It is imperative that tools are designed w...
Learning Analytics (LA) has a major interest in exploring and understanding the learning process of ...
This paper presents a sandbox example of how the integration of models borrowed from Behavioral Econ...
A sizable amount of research has been done to improve the mechanisms for knowledge extraction such a...
Model-free (MF) reinforcement learning (RL) algorithms account for a wealth of neuroscientific and b...
Machine learning (ML), a computational self-learning platform, is expected to be applied in a variet...
The No Free Lunch (NFL) Theorem imposes a theoretical restriction on optimization algorithms and the...
We are approaching a future where robots and humans will co-exist and co-adapt. To understand how ca...
The concept of human behavior recognition is an interesting yet daunting task to delve into. This pa...
In recent years there has been an increased interest in the modelling and recognition of human activ...
Thesis (Ph. D.)--University of Rochester. Dept. of Computer Science, 2012.Until recently, complex ph...
This paper focuses on the creation and presentation of a user-friendly experience for developing com...