We review and formulate results concerning log-concavity and strong-log-concavity in both
discrete and continuous settings. We show how preservation of log-concavity and strongly …

Difference of Convex functions (DC) Programming and DC Algorithm (DCA) constitute the
backbone of Nonconvex Programming and Global Optimization. The paper is devoted to the …

One popular method for dealing with large-scale data sets is sampling. Using the empirical
statistical leverage scores as an importance sampling distribution, the method of algorithmic …

It is usually expected that learning performance can be improved by exploiting unlabeled
data, particularly when the number of labeled data is limited. However, it has been reported …

Learning to localize objects with minimal supervision is an important problem in computer
vision, since large fully annotated datasets are extremely costly to obtain. In this paper, we …

Spectral computed tomography (CT) is a promising technique with the potential for
improving lesion detection, tissue characterization, and material decomposition. In this …

Second-price auctions with reserve play a critical role for modern search engine and
popular online sites since the revenue of these companies often directly depends on the …

This paper focuses on the problem of object detection when the annotation at training time is
restricted to presence or absence of object instances at image level. We present a method …

This paper addresses the problem of recognizing and localizing coherent activities of a
group of people, called collective activities, in video. Related work has argued the benefits of …

We present two graph-based algorithms for multiclass segmentation of high-dimensional
data on graphs. The algorithms use a diffuse interface model based on the Ginzburg …