๐ŸŽ“How I Study AIHISA
๐Ÿ“–Read
๐Ÿ“„Papers๐Ÿ“ฐBlogs๐ŸŽฌCourses
๐Ÿ’กLearn
๐Ÿ›ค๏ธPaths๐Ÿ“šTopics๐Ÿ’กConcepts๐ŸŽดShorts
๐ŸŽฏPractice
๐Ÿ“Daily Log๐ŸŽฏPrompts๐Ÿง Review
SearchSettings
How I Study AI - Learn AI Papers & Lectures the Easy Way

Concepts158

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

Euler Path and Circuit

An Euler path visits every edge exactly once, and an Euler circuit is an Euler path that starts and ends at the same vertex.

#euler path#euler circuit#hierholzer algorithm+12
โš™๏ธAlgorithmIntermediate

Knapsack Problems

Knapsack problems ask how to pick items under a weight (or cost) limit to maximize value or to check if a target sum is reachable.

#0/1 knapsack
678910
Advanced
Filtering by:
#competitive programming
#unbounded knapsack
#bounded knapsack
+12
โš™๏ธAlgorithmIntermediate

Coin Change and Variants

Coin Change uses dynamic programming to find either the minimum number of coins to reach a target or the number of ways to reach it.

#coin change#dynamic programming#unbounded knapsack+12
โˆ‘MathIntermediate

Linear Basis for XOR

A linear basis for XOR is a compact set of at most W numbers (W = number of bits) that can generate every XOR value obtainable from a multiset of numbers.

#xor basis#linear basis#gaussian elimination f2+12
โˆ‘MathIntermediate

Matrix Rank and Linear Independence

Matrix rank is the number of pivots after Gaussian elimination and equals the dimension of both the column space and the row space.

#matrix rank#linear independence#gaussian elimination+12
โˆ‘MathAdvanced

Berlekamp-Massey Algorithm

Berlekampโ€“Massey (BM) finds the shortest linear recurrence that exactly fits a given sequence over a field (e.g., modulo a prime).

#berlekamp-massey#linear recurrence#minimal polynomial+11
โˆ‘MathAdvanced

Gaussian Elimination over GF(2)

Gaussian elimination over GF(2) is ordinary Gaussian elimination where addition and subtraction are XOR and multiplication is AND.

#gaussian elimination#gf(2)#xor basis+12
โš™๏ธAlgorithmIntermediate

Bipartite Matching - Hopcroft-Karp

Hopcroftโ€“Karp computes maximum matching in a bipartite graph in O(E \sqrt{V}) time, which is asymptotically faster than repeated DFS (Kuhn's algorithm).

#hopcroft karp#bipartite matching#augmenting path+11
โš™๏ธAlgorithmAdvanced

General Matching - Blossom Algorithm

Edmonds' Blossom Algorithm finds a maximum matching in any undirected graph, not just bipartite ones.

#blossom algorithm#edmonds matching#general graph matching+12
โš™๏ธAlgorithmIntermediate

Bipartite Matching - Kuhn's Algorithm

Kuhnโ€™s algorithm finds a maximum matching in a bipartite graph by repeatedly searching for augmenting paths using DFS.

#bipartite matching#kuhn algorithm#augmenting path+12
โš™๏ธAlgorithmIntermediate

Kรถnig's Theorem

Kรถnig's Theorem states that in any bipartite graph, the size of a maximum matching equals the size of a minimum vertex cover.

#konig's theorem#bipartite matching#minimum vertex cover+12
โš™๏ธAlgorithmIntermediate

Maximum Flow - Dinic's Algorithm

Dinic's algorithm computes maximum flow by repeatedly building a level graph with BFS and sending a blocking flow using DFS.

#dinic#maximum flow#blocking flow+11