We propose an architecture for fine-grained visual categorization that approaches expert
human performance in the classification of bird species. Our architecture first computes an …

Clustering is a classic topic in optimization with k-means being one of the most fundamental
such problems. In the absence of any restrictions on the input, the best-known algorithm for k …

Matching is a classic problem with a rich history and a significant impact, both on the theory
of algorithms and in practice. Recently there has been a surge of interest in the online …

Let us start with two examples. A company has a machine which drills holes into printed
circuit boards. Since it produces many of these boards it wants the machine to complete one …

In this paper, we analyze local search heuristics for the k-median and facility location
problems. We define the\em locality gap\/of a local search procedure as the maximum ratio …

How does a search engine company decide what ads to display with each query so as to
maximize its revenue? This turns out to be a generalization of the online bipartite matching …

Dependent rounding is a useful technique for optimization problems with hard budget
constraints. This framework naturally leads to negative correlation properties. However, what …

The application of wireless charging technology in traditional battery-powered wireless
sensor networks (WSNs) grows rapidly recently. Although previous studies indicate that the …

Delineating the tremendous growth in this area, the Handbook of Approximation Algorithms
and Metaheuristics covers fundamental, theoretical topics as well as advanced, practical …

We investigate variants of Lloyd's heuristic for clustering high-dimensional data in an attempt
to explain its popularity (a half century after its introduction) among practitioners, and in …