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Short Notes: Equal Partitions, Products, and Decimal Structure
We study how splitting an integer into equal parts affects the maximum attainable product and how arithmetic properties of the optimum emerge. In particular, we relate a continuous optimization problem to the decimal structure of the resulting rational values.
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Short Notes: On a Curious Prefix-Sum Problem
A deceptively simple recurrence leads to an unexpected challenge when computing its prefix sums. Solving it efficiently requires looking at the problem from a different angle.
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Short Notes: Summing Non-Isolated Divisors Across All Subsets
A step-by-step combinatorial derivation of an efficient algorithm to compute S(n): the total sum of subset elements that divide another element in the same subset. The post shows how a brute-force exponential problem can be transformed into a fast method using number-theoretic structure and closed-form counting.
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Backpropagation from Scratch: Feed-Forward Neural Networks in Matrix Notation
A notation-first walkthrough of feed-forward neural networks and vectorized backpropagation, focusing on how the math translates directly into clean, correct implementations. Covers forward pass, backprop, batching, and practical training considerations.
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Online and Batch-Incremental Estimation of Covariance Matrices and Means in Python
Learn how to estimate the mean, covariance, and inverse covariance matrices in an online or batch-incremental fashion. This post explains the theory behind forgetting factors and effective memory, provides Python implementations for both online and batch estimators, and investigates their accuracy and efficiency through experiments and visualizations.