Publications by Laura Elisa Celis

Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees

Nisheeth Vishnoi, Laura Elisa Celis, Vijay Keswani, Lingxiao Huang

Developing classification algorithms that are fair with respect to sensitive attributes of the data is an important problem due to the increased deployment of classification algorithms in societal contexts. Several recent works have focused on studying cla ...

ASSOC COMPUTING MACHINERY2019

Controlling Polarization in Personalization: An Algorithmic Framework

Nisheeth Vishnoi, Farnood Salehi, Laura Elisa Celis, Sayash Kapoor

Personalization is pervasive in the online space as it leads to higher efficiency for the user and higher revenue for the platform by individualizing the most relevant content for each user. However, recent studies suggest that such personalization can lea ...

ASSOC COMPUTING MACHINERY2019

A dashboard for controlling polarization in personalization

Nisheeth Vishnoi, Farnood Salehi, Laura Elisa Celis, Vijay Keswani, Sayash Kapoor

Personalization is pervasive in the online space as it leads to higher efficiency for the user and higher revenue for the platform by individualizing the most relevant content for each user. However, recent studies suggest that such personalization can lea ...

IOS PRESS2019

Coordinate Descent with Bandit Sampling

Patrick Thiran, Farnood Salehi, Laura Elisa Celis

Coordinate descent methods usually minimize a cost function by updating a random decision variable (corresponding to one coordinate) at a time. Ideally, we would update the decision variable that yields the largest decrease in the cost function. However, f ...

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)2018

A General Framework for Sensor Placement in Source Localization

Patrick Thiran, Brunella Marta Spinelli, Laura Elisa Celis

When an epidemic spreads in a given network of individuals or communities, can we detect its source using only the information provided by a small set of nodes? We propose a general framework that incorporates two dimensions. First, we can either rely excl ...

2019

The effect of transmission variance on observer placement for source-localization

Patrick Thiran, Brunella Marta Spinelli, Laura Elisa Celis

2017

Back to the Source: an Online Approach for Sensor Placement and Source Localization

Patrick Thiran, Laura Elisa Celis, Brunella Marta Spinelli

Source localization, the act of finding the originator of a disease or rumor in a network, has become an important problem in sociology and epidemiology. The localization is done using the infection state and time of infection of a few designated sensor no ...

2017

Assignment Techniques for Crowdsourcing Sensitive Tasks

Laura Elisa Celis

Protecting the privacy of crowd workers has been an important topic in crowdsourcing, however, task privacy has largely been ignored despite the fact that many tasks, e.g., form digitization, live audio transcription or image tagging often contain sensitiv ...

Assoc Computing Machinery2016

Observer Placement for Source Localization: the Effect of Budgets and Transmission Variance

Patrick Thiran, Laura Elisa Celis, Brunella Marta Spinelli

When an epidemic spreads in a network, a key question is where was its source, i.e., the node that started the epidemic. If we know the time at which various nodes were infected, we can attempt to use this information in order to identify the source. Howev ...

2016

Budgeted sensor placement for source localization on trees

Patrick Thiran, Laura Elisa Celis, Brunella Marta Spinelli

We address the problem of choosing a fixed number of sensor vertices in a graph in order to detect the source of a partially-observed diffusion process on the graph itself. Building on the definition of double resolvability we introduce a notion of vertex ...

2015