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Concepts25

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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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AllBeginnerIntermediate
∑MathIntermediate

Hidden Markov Models

A Hidden Markov Model (HMM) describes sequences where you cannot see the true state directly, but you can observe outputs generated by those hidden states.

#hidden markov model#forward algorithm#viterbi+12
∑MathIntermediate

Markov Decision Processes (MDP)

A Markov Decision Process (MDP) models decision-making in situations where outcomes are partly random and partly under the control of a decision maker.

#markov decision process
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Filtering by:
#dynamic programming
#value iteration
#policy iteration
+12
⚙️AlgorithmIntermediate

State Space Reduction

State space reduction shrinks the number of dynamic programming or search states by keeping only the information that truly affects future decisions.

#state space reduction#dynamic programming#equivalence relation+12
📚TheoryIntermediate

Bellman Equations

Bellman equations express how the value of a state or action equals immediate reward plus discounted value of what follows.

#bellman equation#value iteration#policy iteration+12
∑MathIntermediate

Derangements

A derangement is a permutation with no element left in its original position, often written as !n or D(n).

#derangement#subfactorial#inclusion-exclusion+11
∑MathIntermediate

Stars and Bars

Stars and Bars counts the ways to distribute n identical items into k distinct bins using combinations.

#stars and bars#combinatorics#binomial coefficient+12
∑MathIntermediate

Permutations and Combinations

Permutations count ordered selections, while combinations count unordered selections.

#permutations#combinations#binomial coefficient+12
⚙️AlgorithmIntermediate

Matrix Exponentiation

Matrix exponentiation turns repeated linear transitions into a single fast power of a matrix using exponentiation by squaring.

#matrix exponentiation#binary exponentiation#companion matrix+11
⚙️AlgorithmIntermediate

Exchange Arguments in DP

An exchange argument proves that any optimal solution can be reordered to satisfy a simple sorting rule by showing that swapping adjacent out-of-order elements never helps.

#exchange argument#adjacent swap#smith rule+12
⚙️AlgorithmIntermediate

Interval DP

Interval DP solves problems where the optimal answer for a segment [i, j] depends on answers of its subsegments.

#interval dp#matrix chain multiplication#burst balloons+12
⚙️AlgorithmIntermediate

Tree DP - Rerooting Technique

Rerooting (a.k.a. 换根 DP) computes a per-node answer as if each node were the root, in total O(n) time on trees.

#rerooting#tree dp#prefix suffix+11
⚙️AlgorithmIntermediate

Digit DP

Digit DP is a dynamic programming technique for counting or aggregating values over all integers in a range that satisfy a digit-based property.

#digit dp#dynamic programming#tight constraint+12