Spectral Techniques in Graph Algorithms
LATIN '98 Proceedings of the Third Latin American Symposium on Theoretical Informatics
Techniques from combinatorial approximation algorithms yield efficient algorithms for random 2k-SAT
Theoretical Computer Science
The Lovász Number of Random Graphs
Combinatorics, Probability and Computing
The First Eigenvalue of Random Graphs
Combinatorics, Probability and Computing
A study of Nash equilibrium in contribution games for peer-to-peer networks
ACM SIGOPS Operating Systems Review
Strong Refutation Heuristics for Random k-SAT
Combinatorics, Probability and Computing
Graph partitioning via adaptive spectral techniques
Combinatorics, Probability and Computing
Finding Planted Partitions in Random Graphs with General Degree Distributions
SIAM Journal on Discrete Mathematics
Loose laplacian spectra of random hypergraphs
Random Structures & Algorithms
High-dimensional Gaussian graphical model selection: walk summability and local separation criterion
The Journal of Machine Learning Research
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We prove that, for all values of the edge probability $p(n)$, the largest eigenvalue of the random graph $G(n, p)$ satisfies almost surely $\lambda_1(G)=(1+o(1))\max\{\sqrt{\Delta}, np\}$, where Δ is the maximum degree of $G$, and the o(1) term tends to zero as $\max\{\sqrt{\Delta}, np\}$ tends to infinity.