Automatic, On-Line Tuning of YARN Container Memory and CPU Parameters. - Mikhail Genkin; Frank Dehne; Maria Pospelova; Yabing Chen; Pablo Navarro (HPCC/SmartCity/DSS, 2016)

Machine-Learning Based Spark and Hadoop Workload Classification Using Container Performance Patterns. - Mikhail Genkin; Frank Dehne; Pablo Navarro; Siyu Zhou (Bench, 2018)

Autonomic Workload Change Classification and Prediction for Big Data Workloads. - Mikhail Genkin; Frank Dehne (IEEE BigData, 2019)

Zero-Shot Machine Learning Technique for Classification of Multi-User Big Data Workloads. - Mikhail Genkin (IEEE BigData, 2020)

Learning non-stationary Langevin dynamics from stochastic observations of latent trajectories. - Mikhail Genkin; Owen Hughes; Tatiana A. Engel (CoRR, 2020)

Moving beyond generalization to accurate interpretation of flexible models. - Mikhail Genkin; Tatiana A. Engel (Nat. Mach. Intell., 2020)

Using Reinforcement Learning with Transfer Learning to Overcome Smart Building Cold Start. - Mikhail Genkin; J. J. McArthur (CSCI, 2022)

Autonomic Architecture for Big Data Performance Optimization. - Mikhail Genkin; Frank Dehne; Anousheh Shahmirza; Pablo Navarro; Siyu Zhou (CoRR, 2023)

ReLBOT: A Transfer Learning Approach to Minimize Reinforcement Learning Risks in Smart Buildings. - Mikhail Genkin; J. J. McArthur (CoRR, 2023)

B-SMART: A reference architecture for artificially intelligent autonomic smart buildings. - Mikhail Genkin; J. J. McArthur (Eng. Appl. Artif. Intell., 2023)