Consider the problem: A committee interviews a stream of N candidates for selecting one. It has to accept or reject each candidate immediately after his/her interview.
High-throughput short read DNA sequencers are enabling inexpensive sampling of genomes at high coverage. Assembling such short reads to discover hitherto unsequenced organisms is an important challenge in computational biology.
Markov chain Monte Carlo (MCMC) methods (which include random walk Monte Carlo methods), are a class of algorithms for sampling from probability distributions based on constructing a Markov chain that has the desired distribution as its equilibriu
In the last few decades, there has been considerable progress in the understanding of binary classification (learning of binary-valued functions) and regression (learning of real-valued functions), both classical problems in machine learning.
We will try to answer the above question by analyzing the stopping times (which is the time after which the deck of cards is completely random) of the card shuffling process.
