The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
We present sublinear-time (randomized) algorithms for finding simple cycles of length at least k 3 and tree-minors in bounded-degree graphs. The complexity of these algorithms is...
Artur Czumaj, Oded Goldreich, Dana Ron, C. Seshadh...
We present a general approximation technique for a large class of graph problems. Our technique mostly applies to problems of covering, at minimum cost, the vertices of a graph wit...
Abstract A dynamic programming algorithm for constructing optimal dyadic decision trees was recently introduced, analyzed, and shown to be very effective for low dimensional data ...
We consider the problem of storing an ordered dictionary data structure over a distributed set of nodes. In contrast to traditional sequential data structures, distributed data st...