Traditional Data Mining and Knowledge Discovery algorithms assume free access to data, either at a centralized location or in federated form. Increasingly, privacy and security co...
Content-based publish/subscribe (pub/sub) is a promising paradigm for building asynchronous distributed applications. In many application scenarios, these systems are required to ...
We boost the efficiency and robustness of distributionbased matching by random subsampling which results in the minimum number of samples required to achieve a specified probabili...
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. denite clause programs containing probabilistic facts with a ...
We initiate the study of sublinear-time algorithms in the external memory model [Vit01]. In this model, the data is stored in blocks of a certain size B, and the algorithm is char...
Alexandr Andoni, Piotr Indyk, Krzysztof Onak, Roni...