In this paper, we develop the first one-pass streaming algorithm for submodular
maximization that does not evaluate the entire stream even once. By carefully subsampling …

As being clear that the joint optimization of caching, computing, and communication (3C)
can significantly improve vehicular network performance, this paper investigates the quality …

We study the problem of extracting a small subset of representative items from a large data
stream. In many data mining and machine learning applications such as social network …

Submodular function maximization is a fundamental combinatorial optimization problem with
plenty of applications--including data summarization, influence maximization, and …

Coresets are important tools to generate concise summaries of massive datasets for
approximate analysis. A coreset is a small subset of points extracted from the original point …

Maximizing constrained submodular functions lies at the core of substantial machine
learning and data mining. Specially, the case that the data come in a streaming fashion …

A valuable small subset strategically selected from massive online reviews is beneficial to
improve consumers' decision-making efficiency in e-commerce. Existing review selection …

BABOONS (BlAck BOx Optimization of Natural language data Summaries) optimizes text
data summaries for an arbitrary, user-defined utility function. Primarily, it targets scenarios in …

Selecting a small set of representatives from a large database is important in many
applications such as multi-criteria decision making, web search, and recommendation. The k …

To satisfy the increasing demands of wireless traffic in vehicular networks, how to
significantly improve vehicular networks becomes a critical issue. Motivated by the potential …