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- Natali Ruchansky, Sungyong Seo, Yan Liu
- ArXiv
- 2017

e topic of fake news has drawn aention both from the public and the academic communities. Such misinformation has the potential of aecting public opinion, providing an opportunity for malicious parties to manipulate the outcomes of public events such as elections. Because such high stakes are at play,automatically detecting fake news is an important, yet… (More)

- Natali Ruchansky, Davide Proserpio
- SIGCOMM
- 2013

The introduction of Software Defined Networks (SDNs) is completely changing the way in which networks are built and managed. SDNs decouple data from control plane access, which makes introduction of new network functionalities significantly simpler. The philosophy of OpenFlow is a move towards centralization, where a single controller program manages the… (More)

- Gonca Gürsun, Natali Ruchansky, Evimaria Terzi, Mark Crovella
- TinyToCS
- 2012

Consider this simple question: how can a network operator identify the set of routes that pass through its network? Answering this question is surprisingly hard: BGP only informs an operator about a limited set of routes. By observing traffic, an operator can only conclude that a particular route passes through its network -- but not that a route does not… (More)

- Gonca Gürsun, Natali Ruchansky, Evimaria Terzi, Mark Crovella
- Internet Measurement Conference
- 2012

Characterizing the set of routes used between domains is an important and difficult problem. The size and complexity of the millions of BGP paths in use at any time can hide important phenomena and hinder attempts to understand the path selection behavior of ASes. In this paper we introduce a new approach to analysis of the interdomain routing system… (More)

- Natali Ruchansky, Mark Crovella, Evimaria Terzi
- KDD
- 2015

In many applications, e.g., recommender systems and traffic monitoring, the data comes in the form of a matrix that is only partially observed and low rank. A fundamental data-analysis task for these datasets is <i>matrix completion</i>, where the goal is to accurately infer the entries missing from the matrix. Even when the data satisfies the low-rank… (More)

- Natali Ruchansky, Francesco Bonchi, David García-Soriano, Francesco Gullo, Nicolas Kourtellis
- SIGMOD Conference
- 2015

The Wiener index of a graph is the sum of all pairwise shortest-path distances between its vertices. In this paper we study the novel problem of finding a <i>minimum Wiener connector</i>: given a connected graph <i>G=(V,E)</i> and a set <i>Q</i> ⊆ <i>V</i> of query vertices, find a subgraph of <i>G</i> that connects all query vertices and has minimum… (More)

- Natali Ruchansky, Claire Lochner, +5 authors William J. Kaiser
- 2011 IEEE International Conference on Acoustics…
- 2011

In this paper, we describe a physical activity classification system using a body sensor network (BSN) consisting of cost-sensitive tri-axial accelerometers. We focus on workspace activities (different motions and sitting postures). We use a Naive Bayes classifier and show that we can train the system simply and systematically. For each task, we find a set… (More)

- Natali Ruchansky, Mark Crovella, Evimaria Terzi
- SDM
- 2017

Matrix completion is a problem that arises in many dataanalysis settings where the input consists of a partiallyobserved matrix (e.g., recommender systems, traffic matrix analysis etc.). Classical approaches to matrix completion assume that the input partially-observed matrix is low rank. The success of these methods depends on the number of observed… (More)

1 Preliminaries 2 1.1 Vector spaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Complexity of optimization problems . . . . . . . . . . . . . . . . 2 1.2.1 Single-objective optimization problems . . . . . . . . . . . 2 1.2.2 Multi-objective optimization problems . . . . . . . . . . . 2 1.3 Parameterized complexity . . . . . . . . . . . .… (More)