A method of generating a classifier model includes distributing a common feature model to two or more users. Multiple classifiers are trained on top of the common feature model. The method further includes distributing a first classifier of the multiple classifiers to a first user and a second classifier of the multiple classifiers to a second user.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method of generating a classifier model comprising: distributing a common feature model to a plurality of users; training a plurality of classifiers on top of the common feature model; and distributing a first classifier of the plurality of classifiers to a first user of the plurality of users and a second classifier of the plurality of classifiers to a second user of the plurality of users. 2. The method of claim 1, in which at least one of the plurality of classifiers are trained on a set of labeled data obtained from at least one entity. 3. The method of claim 2, in which the at least one entity comprises a designated user of the plurality of users. 4. The method of claim 2, further comprising providing a metric for each of the classifiers trained on the set of labeled data obtained from the at least one entity. 5. The method of claim 4, in which the metric comprises information regarding classification accuracy or a number of labeled images. 6. The method of claim 1, further comprising: receiving at least one feature computed from data on a remote device; determining at least one classifier for classifying the data on the remote device based at least in part on the at least one feature; and distributing an indication of at least one classifier to the remote device. 7. The method of claim 1, further comprising: receiving a feature computed from data on a remote device; computing a classification based at least in part on the received feature; and transmitting the classification to the remote device. 8. The method of claim 1, further comprising: combining the first classifier and the second classifier to generate a combined classifier configured to make classifications for classes associated with one or more sets of labeled data; and distributing the combined classifier to at least one of the plurality of users. 9. The method of claim 1, in which at least one of the plurality of classifiers are trained based at least in part on feedback from at least one entity. 10. An apparatus for generating a classifier model comprising: a memory; and at least one processor coupled to the memory, the at least one processor being configured: to distribute a common feature model to a plurality of users; to train a plurality of classifiers on top of the common feature model; and to distribute a first classifier of the plurality of classifiers to a first user of the plurality of users and a second classifier of the plurality of classifiers to a second user of the plurality of users. 11. The apparatus of claim 10, in which the at least one processor is further configured to train at least one of the plurality of classifiers on a set of labeled data obtained from at least one entity. 12. The apparatus of claim 11, in which the at least one entity comprises a designated user of the plurality of users. 13. The apparatus of claim 11, in which the at least one processor is further configured to provide a metric for each of the classifiers trained on the set of labeled data obtained from the at least one entity. 14. The apparatus of claim 13, in which the metric comprises information regarding classification accuracy or a number of labeled images. 15. The apparatus of claim 10, in which the at least one processor is further configured: to receive at least one feature computed from data on a remote device; to determine at least one classifier for classifying the data on the remote device based at least in part on the at least one feature; and to distribute an indication of at least one classifier to the remote device. 16. The apparatus of claim 10, in which the at least one processor is further configured: to receive a feature computed from data on a remote device; to compute a classification based at least in part on the received feature; and to transmit the classification to the remote device. 17. The apparatus of claim 10, in which the at least one processor is further configured: to combine the first classifier and the second classifier to generate a combined classifier configured to make classifications for classes associated with one or more sets of labeled data; and to distribute the combined classifier to at least one of the plurality of users. 18. The apparatus of claim 10, in which the at least one processor is further configured to train at least one of the plurality of classifiers based at least in part on feedback from at least one entity. 19. An apparatus for generating a classifier model comprising: means for distributing a common feature model to a plurality of users; means for training a plurality of classifiers on top of the common feature model; and means for distributing a first classifier of the plurality of classifiers to a first user of the plurality of users and a second classifier of the plurality of classifiers to a second user of the plurality of users. 20. A computer program product for generating a classifier model, comprising: a non-transitory computer readable medium having encoded thereon program code, the program code comprising: program code to distribute a common feature model to a plurality of users; program code to train a plurality of classifiers on top of the common feature model; and program code to distribute a first classifier of the plurality of classifiers to a first user of the plurality of users and a second classifier of the plurality of classifiers to a second user of the plurality of users.