We propose a general method to watermark and probabilistically identify the structured outputs of machine learning algorithms. Our method is robust to local editing operations and...
Ashish Venugopal, Jakob Uszkoreit, David Talbot, F...
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
Prateek Jain, Brian Kulis, Jason V. Davis, Inderji...
—Traditional clustering techniques are inapplicable to problems where the relationships between data points evolve over time. Not only is it important for the clustering algorith...
Lijun Wang, Manjeet Rege, Ming Dong, Yongsheng Din...
—Natural languages like English are rich, complex, and powerful. The highly creative and graceful use of languages like English and Tamil, by masters like Shakespeare and Avvaiya...
Abram Hindle, Earl T. Barr, Zhendong Su, Mark Gabe...
A problem facing many textbook authors (including one of the authors of this paper) is the inevitable delay between new advances in the subject area and their incorporation in a n...
Timothy Miles-Board, Christopher Bailey, Wendy Hal...