Workday, Inc.

Sergei Winitzki

Yury Markovsky

Parag Avinash Namjoshi

Harikrishna Narayanan

Lakshminarayanan Renganarayana

Sameer Kapoor

Yunxing Zhang

Xuan Tan

Milan Desai

Vivien Leong

Vivek Srivastava

The present application discloses a method, system, and computer system for dynamically managing or distributing models across a plurality of shards. The method includes determining that a first model is to be added to a first shard of a plurality of shards, the first shard being determined based at least in part on a predetermined cost function, adding the first model to the first shard, and restarting the first shard. The first model is associated with a first tenant. The first shard comprises at least one second model that is associated with a second tenant.

Scaling machine learning using dynamic sharding

A secure tenant activity data system for a deployment service includes processor that is configured to decrypt a set of encrypted stream processed monitoring data to recover a set of stream processed monitoring data; determine a transaction identifier associated with the set of stream processed monitoring data; determine whether the transaction identifier has been seen associated with a set of previous data; in response to determining that the transaction identifier has been seen associated with the set of previous data, retrieve the set of previous data; decrypt the set of previous data to recover a set of decrypted previous data; aggregate the set of stream processed monitoring data with the set of decrypted previous data to generate a set of aggregated data; encrypt the set of aggregated data to create a set of encrypted aggregated data; and provide the set of encrypted aggregated data to a safe storage area.

User action collection for sensitive customer data

A system for document parsing includes an interface and a processor. The interface is configured to receive an image. The processor is configured to determine text boxes. Determining text boxes uses multiple zoom levels of the image. The processor is further configured to determine labels from the strings and provide the labels.

Document parsing using multistage machine learning

A secure tenant activity data system for a deployment service includes an interface and a processor. The interface is configured to receive a set of encrypted monitoring data collected and encrypted from a monitoring instrument from a tenant system. The processor is configured to decrypt the data for stream processing; encrypt and store the stream processed data; and provide the encrypted data with a tenant identifier to a deployment service. Steam processing is one or more of data cleaning, data rounding, data filtering, data smoothing, algorithmic processing, improving ranking of results, improved navigation, generating recommendations, generating metrics, or computation of features for a machine learning system.

Growing community of inventors

San Francisco, CA, United States of America

Sergei Winitzki