Streaming Euclidean \textsc{Max-Cut}: dimension vs data reduction

Could not fetch data.

Cites Work

An almost space-optimal streaming algorithm for coresets in fixed dimensions
On randomized one-round communication complexity
A randomized approximation scheme for metric MAX-CUT
Random sampling and approximation of MAX-CSPs
Streaming algorithms for extent problems in high dimensions
Approximating extent measures of points
Property testing and its connection to learning and approximation
Polynomial time approximation schemes for Euclidean traveling salesman and other geometric problems
Streaming Embeddings with Slack
Clustering for edge-cost minimization (extended abstract)
Turning Big Data Into Tiny Data: Constant-Size Coresets for $k$-Means, PCA, and Projective Clustering
Extensions of Lipschitz mappings into a Hilbert space
SAMPLING IN DYNAMIC DATA STREAMS AND APPLICATIONS
Facility Location in Dynamic Geometric Data Streams
Sampling from large matrices
On coresets for k-means and k-median clustering
Algorithms for dynamic geometric problems over data streams
Coresets in dynamic geometric data streams
Graph Sparsification in the Semi-streaming Model
Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
Communication Complexity
Non-adaptive adaptive sampling on turnstile streams
Efficient Sketches for Earth-Mover Distance, with Applications
An optimal space lower bound for approximating MAX-CUT
Performance of Johnson-Lindenstrauss transform for k -means and k -medians clustering
A unified framework for approximating and clustering data
Optimal Inapproximability Results for MAX‐CUT and Other 2‐Variable CSPs?
(1 + ε)-Approximation for Facility Location in Data Streams
Perfect $L_p$ Sampling in a Data Stream
Unnamed Item
Unnamed Item
Unnamed Item

This page was built for publication: Streaming Euclidean \textsc{Max-Cut}: dimension vs data reduction