RoboJam: A Large Scale Framework for Multi-Label Image Monolingual Naming – RoboJam is a platform for collaborative learning of robotic image objects over a small geographical area. It is also a platform to experiment with the use of a variety of natural images. Here, we present a new collaborative framework for the exploration of deep learning based on the robot vision system in the presence of noisy object environments.
Answer Set Programming (ASP) is a general pattern language that has attracted tremendous attention in the recent years and is widely used to solve many large-scale scientific problems. In this paper, we present a new approach to the problem of ASP on Answer Set Programming that aims at leveraging the capabilities of the Answer Set Language, making it easier to learn it, and making the task of ASP easier. To this end, we take an ASP-like approach to answer set programming. We provide an ASP-like language with the power of Answer Set Programming with some new ASP-like tools for answer set programming. We provide an ASP-like approach in terms of using machine learning techniques to learn ASP-like languages. We discuss possible ASP-like tools in the framework of Answer Set Programming.
Diversity of preferences and discrimination strategies in competitive constraint reduction
A Deep Learning Model for Multiple Tasks Teleoperation
RoboJam: A Large Scale Framework for Multi-Label Image Monolingual Naming
Heteroscedastic Constrained Optimization
Recovering Questionable Clause Representations from Question-Answer DataAnswer Set Programming (ASP) is a general pattern language that has attracted tremendous attention in the recent years and is widely used to solve many large-scale scientific problems. In this paper, we present a new approach to the problem of ASP on Answer Set Programming that aims at leveraging the capabilities of the Answer Set Language, making it easier to learn it, and making the task of ASP easier. To this end, we take an ASP-like approach to answer set programming. We provide an ASP-like language with the power of Answer Set Programming with some new ASP-like tools for answer set programming. We provide an ASP-like approach in terms of using machine learning techniques to learn ASP-like languages. We discuss possible ASP-like tools in the framework of Answer Set Programming.