Vladimir Vapnik

1 milestone · 1995

Vladimir Vapnik is featured for contributions to AI through Support Vector Machines in 1995 during Quiet Emergence.

Quiet Emergence (1)Research Breakthroughs (1)

Chronology

Research

Support Vector Machines

Vapnik and Cortes published their work on Support Vector Machines (SVMs), a method for finding maximum-margin decision boundaries in high-dimensional spaces with unusually strong theoretical guarantees. SVMs quickly became one of the leading approaches for classification problems across text, vision, and bioinformatics.

Vladimir VapnikCorinna CortesAT&T Bell Labs

Related People

Corinna Cortes (1)

Related Organizations

AT&T Bell Labs (1)

Frequent Topics

Classification (1)Machine Learning (1)Statistical Learning (1)