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cs.DS2023
Relaxed Models for Adversarial Streaming: The Advice Model and the Bounded Interruptions Model
Menachem Sadigurschi, Moshe Shechner, Uri Stemmer
Streaming algorithms are typically analyzed in the oblivious setting, where we assume that the input stream is fixed in advance. Recently, there is a growing interest in designing…
cs.DS2022★ 2 cited
On the Robustness of CountSketch to Adaptive Inputs
Edith Cohen, Xin Lyu, Jelani Nelson +3
CountSketch is a popular dimensionality reduction technique that maps vectors to a lower dimension using randomized linear measurements. The sketch supports recovering -hea…
cs.DS2021
A Framework for Adversarial Streaming via Differential Privacy and Difference Estimators
Idan Attias, Edith Cohen, Moshe Shechner +1
Classical streaming algorithms operate under the (not always reasonable) assumption that the input stream is fixed in advance. Recently, there is a growing interest in designing ro…