The quantum analog of a constraint satisfaction problem is a sum of local Hamiltonians - each (term of the) Hamiltonian specifies a local constraint whose violation contributes to...
Dorit Aharonov, Itai Arad, Zeph Landau, Umesh V. V...
Kernel machines are a popular class of machine learning algorithms that achieve state of the art accuracies on many real-life classification problems. Kernel perceptrons are among...
More and more museums aim at enhancing their visitors' museum experiences in a personalized, intensive and engaging way inside the museum. The CHIP1 (Cultural Heritage Inform...
A recent study by two prominent finance researchers, Fama and French, introduces a new framework for studying risk vs. return: the migration of stocks across size-value portfolio ...
Xiaoxi Du, Ruoming Jin, Liang Ding, Victor E. Lee,...
Spatial classification is the task of learning models to predict class labels based on the features of entities as well as the spatial relationships to other entities and their fe...