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How I Study AI - Learn AI Papers & Lectures the Easy Way

Concepts11

Groups

๐Ÿ“Linear Algebra15๐Ÿ“ˆCalculus & Differentiation10๐ŸŽฏOptimization14๐ŸŽฒProbability Theory12๐Ÿ“ŠStatistics for ML9๐Ÿ“กInformation Theory10๐Ÿ”บConvex Optimization7๐Ÿ”ขNumerical Methods6๐Ÿ•ธGraph Theory for Deep Learning6๐Ÿ”ตTopology for ML5๐ŸŒDifferential Geometry6โˆžMeasure Theory & Functional Analysis6๐ŸŽฐRandom Matrix Theory5๐ŸŒŠFourier Analysis & Signal Processing9๐ŸŽฐSampling & Monte Carlo Methods10๐Ÿง Deep Learning Theory12๐Ÿ›ก๏ธRegularization Theory11๐Ÿ‘๏ธAttention & Transformer Theory10๐ŸŽจGenerative Model Theory11๐Ÿ”ฎRepresentation Learning10๐ŸŽฎReinforcement Learning Mathematics9๐Ÿ”„Variational Methods8๐Ÿ“‰Loss Functions & Objectives10โฑ๏ธSequence & Temporal Models8๐Ÿ’ŽGeometric Deep Learning8

Category

๐Ÿ”ทAllโˆ‘Mathโš™๏ธAlgo๐Ÿ—‚๏ธDS๐Ÿ“šTheory

Level

AllBeginnerIntermediate
โš™๏ธAlgorithmIntermediate

Problem Classification Patterns

Many competitive programming problems map to a small set of classic patterns; recognizing keywords and constraints lets you pick the right tool fast.

#problem classification#binary search on answer#two pointers+12
๐Ÿ—‚๏ธData StructureAdvanced

Dominator Tree

A dominator tree summarizes โ€œmust-passโ€ relationships in a directed graph from a chosen root r: u dominates v if every path from r to v goes through u.

#dominator tree
Advanced
Filtering by:
#lca
#lengauer tarjan
#semidominator
+10
โš™๏ธAlgorithmAdvanced

Block-Cut Tree

A Block-Cut Tree decomposes an undirected graph into biconnected components (blocks) and articulation points, forming a bipartite tree.

#block-cut tree#biconnected components#articulation points+11
โš™๏ธAlgorithmAdvanced

Virtual Tree (Auxiliary Tree)

A Virtual Tree (Auxiliary Tree) compresses a large tree into a much smaller tree that contains only the k important nodes and the LCAs needed to keep them connected.

#virtual tree#auxiliary tree#lca+12
โš™๏ธAlgorithmIntermediate

LCA - Binary Lifting

Binary lifting precomputes 2^k ancestors for every node so we can jump upward in powers of two.

#lca#binary lifting#tree+12
โš™๏ธAlgorithmIntermediate

Bridge Tree

A bridge tree is built by contracting every 2-edge-connected component of an undirected graph into a single node, leaving only bridges as edges between nodes.

#bridge tree#2-edge-connected components#bridges+12
โš™๏ธAlgorithmIntermediate

Tree Distances and Diameter

Tree diameter is the longest simple path in a tree and can be found with two BFS/DFS runs.

#tree diameter#tree center#eccentricity+12
๐Ÿ—‚๏ธData StructureAdvanced

Link-Cut Tree

A Link-Cut Tree (LCT) maintains a dynamic forest and supports link, cut, and path queries in O(log n) amortized time.

#link-cut tree#dynamic tree#splay tree+12
๐Ÿ—‚๏ธData StructureAdvanced

Centroid Decomposition

Centroid decomposition splits a tree around a special node (centroid) so that every remaining component has at most half the nodes.

#centroid decomposition#centroid tree#tree algorithms+11
๐Ÿ—‚๏ธData StructureAdvanced

HLD - Path Queries and Updates

Heavy-Light Decomposition (HLD) breaks a tree into a small number of vertical chains so any path (u,v) becomes O(log n) contiguous segments in an array.

#heavy light decomposition#hld#path query+12
๐Ÿ—‚๏ธData StructureIntermediate

Sparse Table

A Sparse Table is a static range-query data structure that preprocesses an array in O(n \log n) time and answers many queries in O(1) time.

#sparse table#range minimum query#rmq+12