Advanced Algorithms

The content here-in has been influenced by Mung Chiang’s Networked Life and Introduction to Algorithms by CLRS.

Graph, Network#

PageRank#

A* Search#

Min-Cut / Max-Flow (Ford-Fulkerson, Edmonds-Karp)#

Distributed Power Control#

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Machine Learning & Signal Processing#

CNNs (Convolutional Neural Networks)#

LSTMs (Long Short-Term Memory Networks)#

Transformers (Attention Mechanism)#

FFT (Fast Fourier Transform)#

PCA & SVD#

Twin-Tower Models#

Recommender Systems#

Bayesian Rankings (could also be considered as an ensemble)#

Collaborative Filtering#

Matrix Factorisation#

Twin-Tower Neural Architecture#

Compression & Optimisation#

Huffman Encoding#

Linear Programming (Simplex)#

Backpropagation#

Expectation-Maximisation#

Probabilistic Data Structures#

Bloom Filters#

Monte Carlo Tree Search#

Ensemble Architectures#

Bagging (Random Forests)#

Boosting (Gradient Boosting, AdaBoost)#

Stacking / Blending (different to MoE (below), difference lies in how and when models are weighted or selected)#

Mixture of Experts (soft and hard gating)#

Cryptography & Security#

RSA (Rivest-Shamir-Adleman)#

Diffie-Hellman Key Exchange#

AES (Advanced Encryption Standard)#

SHA (Secure Hash Algorithm)#

Elliptic Curve Cryptography (ECC)#

String Algorithms#

Knuth-Morris-Pratt (KMP)#

Rabin-Karp#

Boyer-Moore#

Suffix Arrays / Suffix Trees#