Abstract: Graphs are ubiquitous data structures, present in many machine-learning tasks, such as link prediction, node classification, ontology alignment, etc. As gradient descent drives the training of most modern...
Abstract: Graphs are ubiquitous data structures, present in many machine-learning tasks, such as link prediction, node classification, ontology alignment, etc. As gradient descent drives the training of most modern...
Title: Distance-Estimation in Modern Graphs: Algorithms and Impossibility
Abstract: The size and complexity of today's graphs present challenges that necessitate the discovery of new algorithms. One central...