Bandit-Based Monte Carlo Optimization for Nearest Neighbors — mentioned by kristjansson

Thu, 15 Jun 2023 20:51:32 GMT

The actual arXiv link for the curious: https://arxiv.org/abs/1805.08321

Paper and discussion history. A mention is not an endorsement.

Bandit-Based Monte Carlo Optimization for Nearest Neighbors — mentioned by bagavi

Thu, 06 Apr 2023 13:46:47 GMT

Simple explaination of the general idea using nearest neighbor search as example: 1. You want to calculate the l2-nearest neighbor to y from a set of x1, x2, ... xn. Where each point is a d-dimensional vector. 2. Naive approach will take O(nd) computations. For very large d, say 1e4, this is very expensive Multi-arm bandits idea: 3. Estimate the distance of y to each point (xi) by sampling only along log(d) dimensions. 4. Keep the nearest n/2 points (throw away the rest) 5. Repeat step 3 and 4 until you have one point left 6. The total run time = nlog(d) + nlog(d)/2 + nlog(d)/4.... = O…

Paper and discussion history. A mention is not an endorsement.

Bandit-Based Monte Carlo Optimization for Nearest Neighbors · HackerPapers discussions

Bandit-Based Monte Carlo Optimization for Nearest Neighbors — mentioned by kristjansson

Bandit-Based Monte Carlo Optimization for Nearest Neighbors — mentioned by bagavi