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The increasing power consumption of processors has made power reduction a first-order priority in their design. Voltage scaling is one of the most successful power-reduction techniques introduced to date, but it is limited to some minimum voltage, VDDMIN, below which all components cannot operate reliably. In particular, ever-increasing process variability(More)
—The increasing power consumption of processors has made power reduction a first-order priority in processor design. Voltage scaling is one of the most powerful power-reduction techniques introduced to date, but is limited to some minimum voltage. Below on-chip SRAM cells cannot all operate reliably due to increased process variability with technology(More)
The dueling bandit problem is a variation of the classical multi-armed bandit in which the allowable actions are noisy comparisons between pairs of arms. This paper focuses on a new approach for finding the " best " arm according to the Borda criterion using noisy comparisons. We prove that in the absence of structural assumptions, the sample complexity of(More)
A search engine recommends to the user a list of web pages. The user examines this list, from the first page to the last, and clicks on all attractive pages until the user is satisfied. This behavior of the user can be described by the dependent click model (DCM). We propose DCM bandits, an on-line learning variant of the DCM where the goal is to maximize(More)
Biopotential signal recording is often affected by noise during recording. There is a large body of literature on noise removal techniques for every class of biopotential signals. However, obtaining clean recording is preferable to cleaning a noisy recording. An instantaneous quality measure of the signal to noise ratio during recording would be invaluable(More)
This work studies multiple hypothesis testing in the setting when we obtain data sequentially and may choose when to stop sampling. We summarize the notion of a sequential pvalue (one that can be continually updated and still maintain a type I error guarantee) and provide several examples from the literature. This tool allows us to convert fixedhorizon(More)
We propose stochastic rank-1 bandits, a class of online learning problems where at each step a learning agent chooses a pair of row and column arms, and receives the product of their values as a reward. The main challenge of the problem is that the individual values of the row and column are unobserved. We assume that these values are stochastic and drawn(More)
The probability that a user will click a search result depends both on its relevance and its position on the results page. The position based model explains this behavior by ascribing to every item an attraction probability, and to every position an examination probability. To be clicked, a result must be both attractive and examined. The probabilities of(More)
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