Intuit, Inc.

Omer Zalmanson

Aviv Ben Arie

Yair Horesh

Ido Meir Mintz

A method implements efficient real time serving of ensemble models. The method includes receiving an input and processing the input with an abridged model to generate a set of component scores and an abridged score. The method further includes processing the set of component scores with a deviation threshold to select one of the abridged score and an ensemble score as an output and presenting the output.

Efficient real time serving of ensemble models

A method including monitoring, using a machine learning model, network events of a network. The machine learning model generates fraud scores representing a corresponding probability that a corresponding network event is fraudulent. The method also includes detecting a failure of the machine learning model to generate, within a threshold time, a given fraud score for a given network event. The method also includes determining, by the machine learning model and after the threshold time, the given fraud score. The method also includes logging, responsive to detecting the failure, the given network event in a first table, including logging the given fraud score. The method also includes determining a metric based on comparing the first table to a second table which logs at least the given fraud score and the fraud scores. The method also includes generating an adjusted machine learning model based on the metric.

Evaluating machine learning model performance by leveraging system failures

A processor may receive a plurality of text samples generated by a user and identify at least one variable text element in at least one of the plurality of text samples. The processor may tokenize the at least one variable text element, thereby producing a plurality of tokenized text samples including at least one token. The processor may build a longest common substring from the plurality of tokenized text samples and add the longest common substring and the at least one token to a set of selectable user interface options specific to the user. The processor may generate a user interface comprising the set of selectable user interface options. This can include detecting a user interface context and automatically replacing the at least one token with information specific to the user interface context within the set of selectable user interface options.

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Petah Tikva, Israel

Omer Zalmanson