• Publications
  • Influence
Maximizing the Spread of Influence through a Social Network
TLDR
We consider this problem in several of the most widely studied models in social network analysis. Expand
  • 4,357
  • 1001
  • PDF
Gossip-based computation of aggregate information
TLDR
We analyze the diffusion speed of uniform gossip in the presence of node and link failures, as well as for flooding-based mechanisms. Expand
  • 1,452
  • 145
  • PDF
Maximizing the spread of influence through a social network
TLDR
We provide the first provable approximation guarantees for efficient algorithms for the optimization problem of selecting the most influential nodes in several of the most widely studied social network models. Expand
  • 1,764
  • 111
  • PDF
Submodular meets Spectral: Greedy Algorithms for Subset Selection, Sparse Approximation and Dictionary Selection
TLDR
We study the problem of selecting a subset of k random variables from a large set, in order to obtain the best linear prediction of another variable of interest. Expand
  • 328
  • 60
  • PDF
On profit-maximizing envy-free pricing
TLDR
We study the problem of pricing items for sale to consumers so as to maximize the seller's revenue by finding envy-free prices that maximize seller profit and at the same time are envy free. Expand
  • 326
  • 55
  • PDF
Influential Nodes in a Diffusion Model for Social Networks
TLDR
We study the problem of maximizing the expected spread of an innovation or behavior within a social network, in the presence of “word-of-mouth” referral. Expand
  • 925
  • 51
  • PDF
Auction-Based Multi-Robot Routing
TLDR
We propose a generic framework for auction-based multi-robot routing and analyze a variety of bidding rules for different team objectives. Expand
  • 285
  • 38
  • PDF
Competitive Influence Maximization in Social Networks
TLDR
We propose a natural and mathematically tractable model for the diffusion of multiple innovations in a network. Expand
  • 452
  • 32
  • PDF
Algorithms for subset selection in linear regression
TLDR
We study the problem of selecting a subset of k random variables to observe that will yield the best linear prediction of another variable of interest, given the pairwise correlations between the observation variables and the predictor variable. Expand
  • 172
  • 26
  • PDF
A Knapsack Secretary Problem with Applications
TLDR
We consider situations in which a decision-maker with a fixed budget faces a sequence of options, each with a cost and a value, and must select a subset of them online so as to maximize the total value. Expand
  • 177
  • 23
  • PDF
...
1
2
3
4
5
...