We give efficient algorithms to sample uniformly, and count approximately, the solutions to a zero-one knapsack problem. The algorithm is based on using dynamic programming to pro...
We consider the problem of maintaining aggregates over recent elements of a massive data stream. Motivated by applications involving network data, we consider asynchronous data str...
We show that randomization can lead to significant improvements for a few fundamental problems in distributed tracking. Our basis is the count-tracking problem, where there are k...
RANSAC (Random Sample Consensus) is a popular and effective technique for estimating model parameters in the presence of outliers. Efficient algorithms are necessary for both fram...
Paul McIlroy, Edward Rosten, Simon Taylor, Tom Dru...
We present and evaluate GPU Bucket Sort, a parallel deterministic sample sort algorithm for many-core GPUs. Our method is considerably faster than Thrust Merge (Satish et.al., Pro...