Property testing is concerned with deciding whether an object (e.g. a graph or a function) has a certain property or is “far” (for some definition of far) from every object w...
In recent years analysis of complexity of learning Gaussian mixture models from sampled data has received significant attention in computational machine learning and theory commun...
Most of the existing active learning algorithms are based on the realizability assumption: The learner’s hypothesis class is assumed to contain a target function that perfectly c...
We present several new examples of speed-ups obtainable by quantum algorithms in the context of property testing. First, motivated by sampling algorithms, we consider probability d...
Sourav Chakraborty, Eldar Fischer, Arie Matsliah, ...
Low-Complexity Regions (LCRs) of biological sequences are the main source of false positives in similarity searches for biological sequence databases. We consider the problem of ...