Abstract
We investigate active learning with access to two distinct oracles: LABEL (which is standard) and SEARCH (which is not). The SEARCH oracle models the situation where a human searches a database to seed or counterexample an existing solution. SEARCH is stronger than LABEL while being natural to implement in many situations. We show that an algorithm using both oracles can provide exponentially large problem-dependent improvements over LABEL alone.
Original language | English (US) |
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Pages (from-to) | 3350-3358 |
Number of pages | 9 |
Journal | Advances in Neural Information Processing Systems |
State | Published - 2016 |
Externally published | Yes |
Event | 30th Annual Conference on Neural Information Processing Systems, NIPS 2016 - Barcelona, Spain Duration: Dec 5 2016 → Dec 10 2016 |
ASJC Scopus subject areas
- Computer Networks and Communications
- Information Systems
- Signal Processing