Google Inc.

Vanu, Inc.

Columbia University

Jon Feldman

Shanmugavelayutham Muthukrishnan

Ibrahim Abou-Faycal

Seyed Vahab Mirrokni Banadaki

Matteo Frigo

Vishal Misra

Abhishek Bapna

Aranyak Mehta

David R Karger

Piotr Indyk

Daniel Rubenstein

Gagan Aggarwal

Evdokia V Nikolova

Albert M Chan

Anand Bhalgat

Raghavendra Madyastha

Rohit Rao

Adam Wildavsky

Santiago R Balseiro

Abhinav Kamra

Martin Pal

This specification describes technologies relating to displaying online content. In general, one aspect of the subject matter described in this specification can be embodied in methods that include determining a timing penalty for a content item, the timing penalty based in part on weights of previous impressions the content item has been allocated during a plurality of intervals within a delivery period. The methods may further include determining a weight associated with a pairing of the content item and an impression, the weight based in part on characteristics of the impression. The methods may further include determining a score for the content item, based in part on the weight and the timing penalty. The methods may further include selecting one of a set of matching content items, based in part on the score for the content item, and allocating the selected content item in response to a request.

Online allocation of content items with smooth delivery

A method is described that includes accessing bids for ranked goods and minimum rank indicators that each specifies a lowest rank for a good that is acceptable to a bidder, assigning a ranked good to a first bidder based on a first bid and a first minimum rank indicator each associated with the first bidder, and outputting a signal indicative of a cost of the assigned rank good based on a second bid associated with a next highest bidder having a second minimum rank indicator that specifies a rank that is inclusive of a rank of the ranked good assigned to the first bidder.

Position-based auction

Methods, systems, and apparatus for content distribution. In one aspect, a method includes obtaining reservation data for a resource, the reservation data specifying a reservation period and a number of impression reservations for the reservation period; receiving, during the reservation period, content item request data specifying that the resource was requested; identifying candidate content item providers; determining an expected revenue that will be obtained by selecting one of the candidate content item providers to provide a content item providing, to a content item exchange, auction data including a reserve price; receiving positive response data specifying that the content item exchange will provide an exchange content item for a price that meets the reserve price; and in response to receiving the positive response data, selecting the exchange content item as the content item to be provided in response to receiving the content item request data.

Content item allocation

Methods, systems, and media for forming linear combinations of data are provided. In some embodiments, methods for forming a linear combination of data include: receiving at a device a first codeword, wherein the first codeword comprises a linear combination of at least a first data unit including data, and a second data unit including data; encoding at the device the first codeword and a third data unit including data to form a second codeword, wherein the second codeword includes a linear combination of at least the first data unit, the second data unit, and the third data unit; and transmitting from the device the second codeword.

Methods, systems, and media for forming linear combinations of data

Systems and methods for allocating and providing advertisements in response to impression events (e.g., a request for a placement of an advertisement) corresponding to forecasted impressions (e.g., a forecast of a request for a placement of an advertisement). The advertisements are allocated according to solution data that includes two disjoint solution sets, with each solution set identifying an advertisement that can be allocated to a forecasted impression.

Advertisement allocation

Content item presentation slots (e.g., advertisement slots) can be grouped into a slot group so that more than one presenter (e.g., advertiser) can share a corresponding number of slots on the publisher's property over a defined time period. The presenters can be scheduled to the slots within the slot group to maximize a performance measurement (e.g., number of clicks) that each presenter realizes according to budget constraints that are defined by the presenters.

Content item slot scheduling

Items can be reserved in advance of a future spot market sale. A reservation price can be determined for the item based on an expected spot market price required to obtain the item in the future sport market sale, a time until the spot market sale, and/or market signals. The reservation price can converge to the expected spot market price as the time of the future spot market approaches.

Item reservation

Methods, systems, devices, and computer program products for decoding of Walsh codewords are disclosed.

Decoding of Walsh codes

In one aspect the invention is a method for sequence estimating. The method includes receiving convolutional codes. The method further includes using a lazy Viterbi decoder to decode the convolutional codes. The convolutional codes may be stream convolutional codes. The convolutional codes may also be block convolutional codes. The lazy Viterbi decoder may be used in a software radio environment.

Convolutional decoding

In one aspect the invention is a method for decoding. The method includes receiving encoded data and decoding the encoded data using a noise-adaptive decoder. The data may include first-order Reed-Mueller (FORM) based codes. The data may be based on Complementary Code Keying. Using a noise-adaptive decoder may include determining values of a hard decision based on a first decoding process and discarding the values of the hard decision if a noise sensitivity parameter is above a threshold value. The method may further include using a second decoder process if the noise sensitivity parameter is above the threshold value.

Noise-adaptive decoding

In one aspect the invention is a method for sequence estimating. The method includes generating a dynamic programming table, which represents a trellis. The trellis includes a set of time steps, which have a set of states. The trellis also includes a number of branches that connect the states. The method also includes expanding a search along the branches having a least accumulated error, inserting a pointer into a priority queue, where the pointer indicates an end of a partially completed path within the trellis, searching other branches when the accumulated error is no longer the least accumulated error, and continuing the search until the time step equals a current time.

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New York, NY, United States of America

Jon Feldman