Several published reports show that instancebased learning algorithms yield high classification accuracies and have low storage requirements during supervised learning application...
A fundamental problem in computer vision (CV) is the estimation of geometric parameters from multiple observations obtained from images; examples of such problems range from ellip...
Binary search trees are a fundamental data structure and their height plays a key role in the analysis of divide-and-conquer algorithms like quicksort. Their worst-case height is l...
Effective reduction of noise is generally difficult because of the possible tight coupling of noise with high-frequency image structure. The problem is worse under low-light cond...
We address well-studied problems concerning the learnability of parities and halfspaces in the presence of classification noise. Learning of parities under the uniform distributi...