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Too Much Data: Prices and Inefficiencies in Data Markets
TLDR
It is demonstrated that the data externalities depress the price of data because once a user’s information is leaked by others, she has less reason to protect her data and privacy.
View on SSRN
From the Information Bottleneck to the Privacy Funnel
TLDR
It is shown that the privacy-utility tradeoff under the log-loss can be cast as the non-convex Privacy Funnel optimization, and its connection to the Information Bottleneck is Leveraged, to provide a greedy algorithm that is locally optimal.
View on IEEE
Fast and Slow Learning from Reviews
TLDR
It is shown that providing more information does not always lead to faster learning, but strictly finer rating systems always do, and how different rating systems can lead to very fast or very slow speeds of learning.
View on SSRN
Convergence Rate of Distributed ADMM Over Networks
TLDR
A new distributed algorithm based on alternating direction method of multipliers (ADMM) to minimize sum of locally known convex functions using communication over a network and highlights the effect of network and communication weights on the convergence rate through degrees of the nodes, the smallest nonzero eigenvalue, and operator norm of the communication matrix.
View on IEEE
Graph balancing for distributed subgradient methods over directed graphs
  • A. MakhdoumiA. Ozdaglar
  • Computer Science, Mathematics
    54th IEEE Conference on Decision and Control (CDC…
  • 1 December 2015
TLDR
This work considers a multi agent optimization problem where a set of agents collectively solves a global optimization problem with the objective function given by the sum of locally known convex functions and proposes a distributed subgradient algorithm in which each agent performs local processing based on information obtained from his incoming neighbors.
View on IEEE
Informational Braess' Paradox: The Effect of Information on Traffic Congestion
TLDR
This work introduces a new class of congestion games in which users have differing information sets about the available edges and can only use routes consisting of edges in their information set, and provides a comprehensive answer to whether additional information can be harmful (in the sense of generating greater equilibrium costs/delays).
View PDF on arXiv
Testing, Voluntary Social Distancing and the Spread of an Infection
We study the effects of testing policy on voluntary social distancing and the spread of an infection. Agents decide their social activity level, which determines a social network over which the virus…
View on SSRN
Tunable sparse network coding for multicast networks
TLDR
A mechanism to perform efficient Gaussian elimination over sparse matrices going beyond belief propagation but maintaining low decoding complexity is presented.
View on IEEE
Privacy-utility tradeoff under statistical uncertainty
  • A. MakhdoumiN. Fawaz
  • Computer Science
    51st Annual Allerton Conference on Communication…
  • 1 October 2013
We focus on the privacy-accuracy tradeoff encountered by a user who wishes to release some data to an analyst, that is correlated with his private data, in the hope of receiving some utility. We rely…
View on IEEE
Principal Inertia Components and Applications
TLDR
It is proved that the PICs are related to the fundamental limits of perfect privacy, and they can be used to characterize information-theoretic limits of certain estimation problems.
View on IEEE
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