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Concepts9

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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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🔷All∑Math⚙️Algo🗂️DS📚Theory

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⚙️AlgorithmIntermediate

Bipartite Matching - Hopcroft-Karp

Hopcroft–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
⚙️AlgorithmAdvanced

Hungarian Algorithm

The Hungarian algorithm solves the square assignment problem (matching n workers to n jobs) in O(n^{3}) time using a clever potential (label) function on vertices.

#hungarian algorithm
Advanced
Filtering by:
#bipartite matching
#assignment problem
#bipartite matching
+11
⚙️AlgorithmIntermediate

Bipartite Matching - Kuhn's Algorithm

Kuhn’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
⚙️AlgorithmIntermediate

König's Theorem

König'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
⚙️AlgorithmIntermediate

Flow - Modeling Techniques

Many classic problems can be modeled as a maximum flow problem by building the right network and capacities.

#max flow#dinic#bipartite matching+12
⚙️AlgorithmAdvanced

Minimum Cost Maximum Flow

Minimum Cost Maximum Flow (MCMF) finds the maximum possible flow from a source to a sink while minimizing the total cost paid per unit of flow along edges.

#minimum cost maximum flow#successive shortest augmenting path#reduced cost+11
⚙️AlgorithmIntermediate

Min-Cut Max-Flow Theorem

The Max-Flow Min-Cut Theorem says the maximum amount you can push from source to sink equals the minimum total capacity you must cut to disconnect them.

#max flow#min cut#edmonds karp+12
⚙️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
⚙️AlgorithmIntermediate

Maximum Flow - Ford-Fulkerson

Ford–Fulkerson finds the maximum possible flow from a source to a sink by repeatedly pushing flow along an augmenting path in the residual graph.

#maximum flow#ford-fulkerson#edmonds-karp+10