activity
20092017
most citedStochastic Optimization with Bandit Sampling

11 citations · 16 across the 4 of their papers we have counts for

collaborators

7 papers

cs.LG201711 cited

Stochastic Optimization with Bandit Sampling

Farnood Salehi, L. Elisa Celis, Patrick Thiran

Many stochastic optimization algorithms work by estimating the gradient of the cost function on the fly by sampling datapoints uniformly at random from a training set. However, the…

cs.CY20175 cited

Fair Personalization

L. Elisa Celis, Nisheeth K. Vishnoi

Personalization is pervasive in the online space as, when combined with learning, it leads to higher efficiency and revenue by allowing the most relevant content to be served to ea…

cs.LG2017

A Distributed Learning Dynamics in Social Groups

L. Elisa Celis, Peter M. Krafft, Nisheeth K. Vishnoi

We study a distributed learning process observed in human groups and other social animals. This learning process appears in settings in which each individual in a group is trying t…

cs.GT2017

A Model for Information Networks: Efficiency, Stability and Dynamics

L. Elisa Celis, Aida S. Mousavifar

We introduce a simple network model that is inspired by social information networks such as twitter. Agents are nodes, connecting to another agent by building a directed edge has a…

cs.SI2017

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

Brunella Spinelli, L. Elisa Celis, Patrick Thiran

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 u…

cs.SI2016

Sequential Voting Promotes Collective Discovery in Social Recommendation Systems

L. Elisa Celis, Peter M. Krafft, Nathan Kobe

One goal of online social recommendation systems is to harness the wisdom of crowds in order to identify high quality content. Yet the sequential voting mechanisms that are commonl…