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cs.DS2026
Locally Sparsified, Globally Near-Optimal: Matching under Independent Vertex Arrivals
Sara Ahmadian, Edith Cohen, Mohammad Roghani
Resource allocation systems often restrict each request to a short list of options before coordinating assignments globally. We study this separation in stochastic bipartite matchi…
cs.DS2026
Stochastic Matching via Local Sparsification
Sara Ahmadian, Edith Cohen, Mohammad Roghani
The classic online stochastic matching problem typically requires immediate and irrevocable matching decisions. However, in many modern decentralized systems such as real-time ride…
cs.DS2024★ 1 cited
Unmasking Vulnerabilities: Cardinality Sketches under Adaptive Inputs
Sara Ahmadian, Edith Cohen
Cardinality sketches are popular data structures that enhance the efficiency of working with large data sets. The sketches are randomized representations of sets that are only of l…