Abstract: One or more computing devices, systems, and/or methods for selecting content items for transmission to client devices are provided. A first content item may be transmitted to a first set of client devices. A first request for content associated with a first client device of a second set of client devices may be received. A first bid value associated with a second content item may be selected. The first bid value may be modified based upon a second bid value associated with the first content item to generate a third bid value associated with the second content item. The second content item may be selected from a first plurality of content items for presentation via the first client device based upon a plurality of bid values having the third bid value. The second content item may be transmitted to the first client device.

Abstract: One or more computing devices, systems, and/or methods for selecting content items for transmission to client devices are provided. A first content item may be transmitted to a first set of client devices. A first request for content associated with a first client device of a second set of client devices may be received. A first bid value associated with a second content item may be selected. The first bid value may be modified based upon a second bid value associated with the first content item to generate a third bid value associated with the second content item. The second content item may be selected from a first plurality of content items for presentation via the first client device based upon a plurality of bid values having the third bid value. The second content item may be transmitted to the first client device.

Abstract: One or more computing devices, systems, and/or methods for selecting content items for transmission to client devices are provided. A request for content may be received. A second plurality of content items associated with a plurality of rankings may be selected from a plurality of content items based upon a plurality of bid values. A quantity of content items of the second plurality of content items may be greater than a quantity of content items associated with the request for content. One or more ghost content items associated with one or more rankings of the plurality of rankings may be identified. A ghost impression indicator associated with a ghost content item of the one or more ghost content items may be stored based upon a determination that a ranking, of the one or more rankings, associated with the ghost content item matches a second ranking of a presented content item.

Abstract: One or more computing devices, systems, and/or methods for selecting content items for transmission to client devices are provided. A first content item may be transmitted to a first set of client devices. A first request for content associated with a first client device of a second set of client devices may be received. A first bid value associated with a second content item may be selected. The first bid value may be modified based upon a second bid value associated with the first content item to generate a third bid value associated with the second content item. The second content item may be selected from a first plurality of content items for presentation via the first client device based upon a plurality of bid values having the third bid value. The second content item may be transmitted to the first client device.

Abstract: The technology described in this document is, among other things, capable of efficiently monitoring storage device signal data for anomalies. In an example method, signal data for a plurality of non-transitory storage devices is collected. The method determines a hyper feature representation from the collected signal data and computes, using the hyper feature representation, scores for statistics associated with the non-transitory storage devices. The method further determines a reduced hyper feature representation aggregating the scores for each of the statistics associated with each of the non-transitory storage devices; generates, using the reduced hyper feature representation, storage device scores for the non-transitory storage devices of the plurality, respectively; and identifies one or more non-transitory storage devices from among the plurality of non-transitory storage devices exhibiting anomalous storage device behavior using the storage device scores.

Abstract: The technology described in this document is, among other things, capable of efficiently monitoring storage device signal data for anomalies. In an example method, signal data for a plurality of non-transitory storage devices is collected. The method determines a hyper feature representation from the collected signal data and computes, using the hyper feature representation, scores for statistics associated with the non-transitory storage devices. The method further determines a reduced hyper feature representation aggregating the scores for each of the statistics associated with each of the non-transitory storage devices; generates, using the reduced hyper feature representation, storage device scores for the non-transitory storage devices of the plurality, respectively; and identifies one or more non-transitory storage devices from among the plurality of non-transitory storage devices exhibiting anomalous storage device behavior using the storage device scores.