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📐Linear Algebra15📈Calculus & Differentiation10🎯Optimization14🎲Probability Theory12📊Statistics for ML9📡Information Theory10🔺Convex Optimization7🔢Numerical Methods6🕸Graph Theory for Deep Learning6🔵Topology for ML5🌐Differential Geometry6∞Measure Theory & Functional Analysis6🎰Random Matrix Theory5🌊Fourier Analysis & Signal Processing9🎰Sampling & Monte Carlo Methods10🧠Deep Learning Theory12🛡️Regularization Theory11👁️Attention & Transformer Theory10🎨Generative Model Theory11🔮Representation Learning10🎮Reinforcement Learning Mathematics9🔄Variational Methods8📉Loss Functions & Objectives10⏱️Sequence & Temporal Models8💎Geometric Deep Learning8

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⚙️AlgorithmAdvanced

CDQ Divide and Conquer

CDQ divide and conquer is an offline technique that splits the timeline (or one coordinate) and lets updates from the left half contribute to queries in the right half.

#cdq divide and conquer#offline algorithm#fenwick tree+11
⚙️AlgorithmIntermediate

2D Prefix Sum

A 2D prefix sum (also called an integral image) lets you compute the sum of any axis-aligned sub-rectangle in constant time after O(nm) preprocessing.

#2d prefix sum
Advanced
Filtering by:
#range sum query
#summed-area table
#integral image
+12
⚙️AlgorithmIntermediate

Prefix Sum and Difference Array

Prefix sums precompute running totals so any range sum [l, r] can be answered in O(1) time as prefix[r] - prefix[l-1].

#prefix sum#difference array#imos method+12