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Found 6 papers, 1 papers with code
On the Role of Memory in Robust Opinion Dynamics
We investigate opinion dynamics in a fully-connected system, consisting of $n$ identical and anonymous agents, where one of the opinions (which is called correct) represents a piece of information to disseminate.
On the Multidimensional Random Subset Sum Problem
random variables $X_1, ..., X_n$, we wish to approximate any point $z \in [-1, 1]$ as the sum of a suitable subset $X_{i_1(z)}, ..., X_{i_s(z)}$ of them, up to error $\varepsilon$.
A Ihara-Bass Formula for Non-Boolean Matrices and Strong Refutations of Random CSPs
Strong refutation results based on current approaches construct a certificate that a certain matrix associated to the k-CSP instance is quasirandom.
Spectral Robustness for Correlation Clustering Reconstruction in Semi-Adversarial Models
We study the reconstruction version of this problem in which one is seeking to reconstruct a latent clustering that has been corrupted by random noise and adversarial modifications.
Finding a Bounded-Degree Expander Inside a Dense One
It follows from the Marcus-Spielman-Srivastava proof of the Kadison-Singer conjecture that if $G=(V, E)$ is a $\Delta$-regular dense expander then there is an edge-induced subgraph $H=(V, E_H)$ of $G$ of constant maximum degree which is also an expander.
Distributed, Parallel, and Cluster Computing
Partitioning into Expanders
Unlike the recent results on higher order Cheeger's inequality [LOT12, LRTV12], our algorithmic results do not use higher order eigenfunctions of G. If there is a sufficiently large gap between lambda_k and lambda_{k+1}, more precisely, if \lambda_{k+1} >= \poly(k) lambda_{k}^{1/4} then our algorithm finds a k partitioning of V into sets P_1,..., P_k such that the induced subgraph G[P_i] has a significantly larger conductance than the conductance of P_i in G. Such a partitioning may represent the best k clustering of G. Our algorithm is a simple local search that only uses the Spectral Partitioning algorithm as a subroutine.
