Google Inc.

Thomas Fischbacher

Jyrki Antero Alakuijala

Matthias Heiler

Luciano Sbaiz

Lode Vandevenne

Michael Schaer

Robin Nittka

Nikola Todorovic

Laura Dragoi

A first context update indicative of a present state associated with an application is received. A first contextual situation, among a plurality of contextual situations associated with a plurality of conditions, that corresponds to the first context update is identified. Identifying the first contextual situation includes implementing a decision tree to minimize a number of the plurality of conditions to be evaluated, identifying the first contextual situation using the decision tree, and determining one or more actions to be performed corresponding with the first contextual situation.

Contextual situation analysis

A system and method includes receiving a first context update for an application. The method determines whether one or more of multiple rules has been satisfied in view of the first context update. The multiple rules include a multiple conditions and are associated with multiple contextual situations. The determining includes minimizing a number of the multiple conditions to be evaluated to determine whether a particular rule of the multiple rules has been satisfied. The method responsive to determining a first rule of the multiple rules has been satisfied, identifies a first contextual situation of the multiple contextual situations that is associated with the first rule. The method also determines at least one action that is associated with the first contextual situation.

An image block is coded using entropy-inspired directional filtering. During encoding, intensity differences are determined for at least some pixels of an image block based on neighboring pixels of respective ones of the at least some pixels. Angles are estimated for each of those pixels based on the intensity differences. A main filtering direction of the image block is then determined based on the estimated angles. The image block is filtered according to the main filtering direction to remove artifacts along oblique edges associated with the image block. The filtered image block is then encoded to an encoded image. During decoding, an angular map indicating angles estimated for pixels of an encoded image block is received and used to determine the main filtering direction of the image block. The image block can then be filtered according to the main filtering direction and then output for display or storage.

Entropy-inspired directional filtering for image coding

A method for encoding a block of a frame. The method includes receiving the block that is in the spatial domain; selecting, based on a border that crosses the block, a set of basis functions for transforming the block to a transform domain; transforming the block using the set of basis functions to obtain a transform block; encoding, in a compressed bitstream, an indication of the set of basis functions; and encoding, in the compressed bitstream, the transform block.

Using border-aligned block functions for image compression

A system and method for providing a search experience in which users are protected from exposure to inappropriate offensive or sensitive content is described. A search system may classify a search query and candidate search results obtained in response to the search query. Based on the classification of the search query and search results, the candidate search results may be modified to generate a set of search results presented to a user such that the presented search results do not include inappropriate sensitive or offensive content.

Protecting users from inappropriate sensitive or offensive search results

Described is a machine learning system for binary classifications. The system improves interpolation schemes used in isotonic regressions by providing a continuous function that also is monotonic. The system outputs a probability estimating function on a signal space that is both monotonic and varies continuously with the input signals. More specifically, described is an interpolation function that is continuous and piecewise linear on Delaunay simplices. Accordingly, the resulting probability estimation function may more accurately match actual probabilities especially when training data is sparse.

Interpolating isotonic regression for binary classification of spam, explicit material or malware using interpolation based on a Delaunay triangulation

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Gattikon, Switzerland

Thomas Fischbacher