Word evolution refers to the changing meanings and associations of words throughout time,
as a byproduct of human language evolution. By studying word evolution, we can infer …

Is it possible to maximize a monotone submodular function faster than the widely used lazy
greedy algorithm (also known as accelerated greedy), both in theory and practice? In this …

Machine learning methods have achieved good performance and been widely applied in
various real-world applications. They can learn the model adaptively and be better fit for …

How can one summarize a massive data set" on the fly", ie, without even having seen it in its
entirety? In this paper, we address the problem of extracting representative elements from a …

Can we summarize multi-category data based on user preferences in a scalable manner?
Many utility functions used for data summarization satisfy submodularity, a natural …

Submodular maximization has become established as the method of choice for the task of
selecting representative and diverse summaries of data. However, if datapoints have …

In this paper, we consider an online optimization process, where the objective functions are
not convex (nor concave) but instead belong to a broad class of continuous submodular …

We consider the problem of maximizing a nonnegative submodular set function f: 2^ N →
R^+ f: 2 N→ R+ subject to ap-matchoid constraint in the single-pass streaming setting …

Submodular optimization generalizes many classic problems in combinatorial optimization
and has recently found a wide range of applications in machine learning (eg, feature …

It is known that greedy methods perform well for maximizing\textitmonotone submodular
functions. At the same time, such methods perform poorly in the face of non-monotonicity. In …