Definition: In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.
Input: The sample complexity of active learning under the realizability assumption has been well-studied. The realizability assumption, however, rarely holds in practice. In this paper, we theoretically characterize the sample complexity of active learning in the non-realizable case under multiview setting. We prove that, with unbounded Tsybakov noise, the sample complexity of multiview active learning can be Õ(log 1ǫ ), contrasting to single-view setting where the polynomial improvement is the best possible achievement. We also prove that in general multi-view setting the sample complexity of active learning with unbounded Tsybakov noise is Õ(1ǫ ), where the order of 1/ǫ is independent of the parameter in Tsybakov noise, contrasting to previous polynomial bounds where the order of 1/ǫ is related to the parameter in Tsybakov noise.

Multi-View Active Learning in the Non-Realizable Case