This paper studies the evaluation of policies that recommend an ordered set of items (eg, a
ranking) based on some context---a common scenario in web search, ads, and …

We introduce a new notion of graph sparsification based on spectral similarity of graph
Laplacians: spectral sparsification requires that the Laplacian quadratic form of the sparsifier …

Spectral graph theory is the study and exploration of graphs through the eigenvalues and
eigenvectors of matrices naturally associated with those graphs. It is intuitively related to …

We present a randomized algorithm that on input a symmetric, weakly diagonally dominant n-
by-n matrix A with m nonzero entries and an n-vector b produces an ̃x such that ‖̃x …

In this paper, we present a simple combinatorial algorithm that solves symmetric diagonally
dominant (SDD) linear systems in nearly-linear time. It uses little of the machinery that …

We present an algorithm that on input of an n-vertex m-edge weighted graph G and a value
k produces an incremental sparsifier ̂G with n-1+m/k edges, such that the relative condition …

Surface representation and processing is one of the key topics in computer graphics and
geometric modeling, since it greatly affects the range of possible applications. In this paper …

We present an improved algorithm for solving symmetrically diagonally dominant linear
systems. On input of an n× n symmetric diagonally dominant matrix A with m non-zero …

The ability to solve a system of linear equations lies at the heart of areas such as
optimization, scientific computing, and computer science, and has traditionally been a …

The sheer size of today's power grid and the increasingly stressed conditions under which
power systems operate demand the use of computers for analysis and simulations. Yet …