The defining feature of many modern large-scale computer systems is the sheer amount of
data that they generate and process. Google's MapReduce clusters process over twenty …

Parallel algorithms and dynamic algorithms possess an interesting duality property:
compared to sequential algorithms, parallel algorithms improve run-time while preserving …

Self-adjusting computation is an approach for automatically producing dynamic algorithms
from static ones. It works by tracking control and data dependencies, and propagating …

Dynamic algorithms are used to compute a property of some data while the data undergoes
changes over time. Many dynamic algorithms have been proposed but nearly all are …

Let P be a collection of n points moving along pseudo-algebraic trajectories in the plane.
One of the hardest open problems in combinatorial and computational geometry is to obtain …

In many applications there has been an increasing interest in computing certain properties
of a changing set of input objects where the changes may be of dynamic nature in terms of …

Resumen Kinetic Data Structures are a special way to model continuous collision detection
due to the model and combination of the state of geometrical and motion configuration …

Many algorithms and applications involve repeatedly solving a variation of the same
statistical inference problem. Adaptive inference is a technique where the previous …

Dynamic algorithms are used to maintain a property of some data while the data undergoes
changes over time. For example, a dynamic algorithm on forests may maintain connectivity …

We present a kinetic data structure named Kinetic Interval Graph (KI-Graph) for performing
efficient range search on moving one dimensional axis-parallel segments. This finds …