אריה קנטורוביץ

אקדמי בכיר

Near-optimal sample compression for nearest neighbors

Lee Ad Gottlieb, Aryeh Kontorovich, Pinhas Nisnevitch

We present the first sample compression algorithm for nearest neighbors with non-trivial performance guarantees. We complement these guarantees by demonstrating almost matching hardness lower bounds, which show that our bound is nearly optimal. Our result yields new insight into margin-based nearest neighbor classification in metric spaces and allows us to significantly sharpen and simplify existing bounds. Some encouraging empirical results are also presented.

שפת פרסום אנגלית
דפים 370-378
כתב עת Advances in Neural Information Processing Systems
כרך 1
נושא מספר January
סטטוס פרסום פורסם - 01.01.2014

ASJC Scopus subject areas

Computer Networks and Communications
Information Systems
Signal Processing
קבצים וקישורים אחרים
Link to publication in Scopus