Andrew Dzhoha
Research-driven engineering in machine learning, with a current focus on recommender systems. Proficient in backend stack development and data processing.
PhD in Statistical Machine Learning, Department of Applied Statistics, Computer Science.
Master's and bachelor's degrees in Computer Engineering.
Publications
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Reducing Popularity Influence by Addressing Position Bias,
RobustRecSys workshop, collocated with the 18th ACM Conference on Recommender Systems (RecSys).
11 Dec 2024
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Building a Scalable, Effective, and Steerable Search and Ranking Platform,
CARS workshop, collocated with the 18th ACM Conference on Recommender Systems (RecSys).
4 Sep 2024
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Beta Upper Confidence Bound Policy for the Design of Clinical Trials,
Austrian Journal of Statistics.
15 Aug 2023
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Multi-armed bandit problem with online clustering as side information,
Journal of Computational and Applied Mathematics, Elsevier.
16 Feb 2023
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Bernoulli multi-armed bandit problem under delayed feedback,
Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics.
19 Feb 2021
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Engineering
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Contextual multi-armed bandit problem with online clustering
03 Jun 2022
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Data Analysis course notebooks in R
21 Apr 2022
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Multi-armed bandit problem under delayed feedback
14 Feb 2020
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Deep Learning Nanodegree Program
10 Apr 2019
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Circuit Breaker in Go based on sync/atomic
15 Mar 2018
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Machine Learning by Stanford University on Coursera
10 Apr 2016
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Leader Election algorithm in Erlang
18 Apr 2014
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Functional Programming Principles in Scala on Coursera
04 Jun 2013
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HTTP Long Polling in Erlang and JavaScript
15 Mar 2013
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Some solutions of Google Code Jam problems
26 Feb 2013
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