1) Randomized Jumplists
2) Randomization in Combinatorial Optimization
   (e.g. in Genetic Algorithms, Simulated Annealing, 
   Stochastic Gradient Descent, ...)
3) Randomized Geometric Algorithms
   (e.g. Randomized Incremental Convex Hull, Probabilistic Roadmap)
4) Randomized On-line Algorithms
   (e.g. Randomized Algorithms for the Paging Problem)
5) Randomized Distributed Algorithms
   (e.g. Asynchronous Binary Byzantine Agreement)
6) Smoothed Complexity
7) Randomized Algorithms in Data Stream Analysis
   (e.g. Sticky Sampling, Frequent, CountSketch, ... for 
   Heavy Hitters)
8) Generation of Random Variates
   (generating probability distributions: Normal, exponential, Poisson, ...)
9) Hidden Markov Chains
10) Variance Reduction in MonteCarlo Simulations
11) Approximate Membership Queries Filters
    (except Bloom filters)
12) Randomized Algorithms for Machine Learning
    (e.g., randomized feature reduction)
13) Randomization for Clustering
14) Randomization for Ranking and Social Choice
15) Bayesian Networks
16) Random Graphs and Phase Transitions
17) Locality-Sensitive Hashing
18) Randomization in Anomaly Detection