Theoretical foundations can be found in the following papers. Learning of constraints: @inproceedings{ciravegna2020constraint, title={A Constraint-Based Approach to Learning and Explanation.}, author= ...

Digital learning, a form of education that uses electronic resources to facilitate learning, often requires a delicate balance between creativity and the constraints inherent in the medium.

Based on these measurements, the set of feasible constraint parameters is refined using set-membership learning techniques. The reference command value is selected so that it minimizes the worst-case ...

Abstract: Learning symbolic-level numerical constraints is key to use abstractions in effective reasoning and transfer of knowledge for robot systems. We investigate this problem in an ...

This repository contains two notebooks which will guide you step-by-step towards the implementation of learning of and with constraints in Pytorch. Learning with constraints: learn how to train a NN ...

Phonological processes are context-dependent sound changes in natural languages. We present an unsupervised approach to learning human-readable descriptions of phonological processes from collections ...

Constraints on the Cloud: why we need machine learning at the Edge. ... with machine learning (ML) at the forefront. Even today, ML is an important aspect of any device experience, powering all kinds ...