ملخص
We present an improved algorithm for properly learning convex polytopes in the realizable PAC setting from data with a margin. Our learning algorithm constructs a consistent polytope as an intersection of about t log t halfspaces with margins in time polynomial in t (where t is the number of halfspaces forming an optimal polytope). We also identify distinct generalizations of the notion of margin from hyperplanes to polytopes and investigate how they relate geometrically; this result may be of interest beyond the learning setting.
اللغة الأصلية | الإنجليزيّة |
---|---|
الصفحات (من إلى) | 5706-5716 |
عدد الصفحات | 11 |
دورية | Advances in Neural Information Processing Systems |
مستوى الصوت | 2018-December |
حالة النشر | نُشِر - 2018 |
الحدث | 32nd Conference on Neural Information Processing Systems, NeurIPS 2018 - Montreal, كندا المدة: ٢ ديسمبر ٢٠١٨ → ٨ ديسمبر ٢٠١٨ |