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The Power of Adaptivity in Identifying Statistical Alternatives
This paper studies the trade-off between two different kinds of pure exploration: breadth versus depth.
On the Detection of Mixture Distributions with applications to the Most Biased Coin Problem
As a result, these bounds have surprising implications both for solutions to the most biased coin problem and for anomaly detection when only partial information about the parameters is known.
Detecting People in Cubist Art
Although the human visual system is surprisingly robust to extreme distortion when recognizing objects, most evaluations of computer object detection methods focus only on robustness to natural form deformations such as people's pose changes.
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