We define a natural notion of efficiency for approximate nearest-neighbor (ANN) search in general n-point metric spaces, namely the existence of a randomized algorithm which answ...
We initiate a study of tradeoffs between communication and computation in well-known communication models and in other related models. The fundamental question we investigate is t...
Prahladh Harsha, Yuval Ishai, Joe Kilian, Kobbi Ni...
Abstract. We study strategies that minimize the instability of a faulttolerant consensus system. More precisely, we find the strategy than minimizes the number of output changes ov...
We provide a deterministic algorithm that constructs small point sets exhibiting a low star discrepancy. The algorithm is based on recent results on randomized roundings respectin...
While most supervised machine learning models assume that training examples are sampled at random or adversarially, this article is concerned with models of learning from a cooper...
Sandra Zilles, Steffen Lange, Robert Holte, Martin...