We use a greedy algo- rithm to solve this problem. We first sort the subsets in P by their sizes in descending order, then we assign each subset to the ma- chine with the largest remaining capacity. It is known [21] that this greedy algorithm produces an approximation of 4/3 − 1...
HOW TO THINK ABOUT ALGORITHMS There are many algorithm texts that provide lots of well-polished code and proofs of correctness. Instead, this one presents insights, notations, and analogies to help the novice describe and think about algorithms like an expert. It is a bit like a carpenter ...
Fortunately, in machine learning people are already dealing with estimating the correctness of a model in real life when it is correct on all training data, which is exactly the same as we are trying to estimate the correctness of a guess in system tests when it is correct on all examples ...
This therefore is nothing to the purpose: It only shews you have the Power of imagining or forming Ideas in your Mind; but it doth not shew that you can conceive it possible, the Objects of your Thought may exist without the Mind: To make out this, it is necessary that you conceive ...
Start at C = I (all of the items). 2. Remove from C the element in C \ X which is furthest away from the current average of C, and return true if this new set has variance ≤ k 3. Repeat step 2. Second Algorithm 1. Start at C = X. 2. Add to C the element closest to...
As there may be an exponential number of graph cycles [3,113], this theorem lends itself to nice connections from CS Unplugged to combinatorics, but enumerating and checking all cycles is infeasible in practice. However, a simple greedy algorithm based on depth-first search [2] is sufficient ...