Displaying 298 resources



Real-like MAX-SAT Instances and the Landscape Structure Across the Phase Transition
In contrast with random uniform instances, industrial SAT instances of large size are solvable today by state-of-the-art algorithms.



AI Studies Survey
AI is a rapidly emerging field that has opened up new vistas of innovation and creativity. From intelligent systems to self-driving cars, AI has transformed the way we live and work.


The Silent (R)evolution of SAT
The Propositional Satisfiability problem (SAT) was the first to be shown NP-complete by Cook and Levin. SAT remained the embodiment of theoretical worst-case hardness.


Algorithms for manifold learning
The technical report presents popular methods for mapping data into a low-dimensional manifold (nonlinear dimensionality reduction).


Geometric data analysis based on manifold learning with applications for image understanding
The conference paper gives in the first section a brief and easy understandable introduction into the basics of Riemannian geometry.


Terse notes on Riemannian geometry
The technical report gives a compact introduction into the basic definitions and theorems of Riemannian geometry, Lie groups & Lie algebras and symmetric spaces.