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This paper proposes a tradeoff between sample complexity and computation time that applies to statistical estimators based on convex optimization. As the amount of data increases, we can smooth optimization problems more and more aggressively to achieve ac ...
Recent advances in data processing and communication systems have led to a continuous increase in the amount of data communicated over today’s networks. These large volumes of data pose new challenges on the current networking infrastructure that only offe ...
We consider Gaussian diamond networks with n half-duplex relays. At any point of time, a relay can either be in a listening (L) or transmitting (T) state. The capacity of such networks can be approximated to within a constant gap (independent of channel SN ...
In distributed processing, agents generally collect data generated by the same underlying unknown model (represented by a vector of parameters) and then solve an estimation or inference task cooperatively. In this paper, we consider the situation in which ...
When can we reason about the neutrality of a network based on external observations? We prove conditions under which it is possible to (a) detect neutrality violations and (b) localize them to specific links, based on external observations. Our insight is ...
When can we reason about the neutrality of a network based on external observations? We prove conditions under which it is possible to (a) detect neutrality violations and (b) localize them to specific links, based on external observations. Our insight is ...
Synthetic social contact networks play a central role in the study of epidemics and methods to control them. In this paper we propose a new methodology that combines subjective surveys and data obtained using digital devices to synthesize detailed social n ...
Infinite nature of sensor data poses a serious challenge for query processing even in a cloud infrastructure. Model-based sensor data approximation reduces the amount of data for query processing, but all modeled segments need to be scanned, in the worst c ...
Infinite nature of sensor data poses a serious challenge for query processing even in a cloud infrastructure. Model-based sensor data approximation reduces the amount of data for query processing, but all modeled segments need to be scanned, in the worst c ...
Query optimizers depend heavily on statistics representing column distributions to create efficient query plans. In many cases, though, statistics are outdated or non-existent, and the process of refreshing statistics is very expensive, especially for ad-h ...
