Max Vladymyrov, PhD

Max Vladymyrov is currently a Senior Research Engineer with Google Research at Mountain View, CA. He possesses extensive background in Machine Learning, with more than ten years of both academic and industrial experience in research, first as a PhD student and further as a researcher at Yahoo Labs and Google Research.

Max has substantial experience in nonlinear optimization, dimensionality reduction, NLP and Information Retrieval, with papers presented at the top Machine Learning conferences, such as ICML and NeurIPS.

Keynote

Title of the talk: “Machine Learning: overview of the field”

Machine Learning is a rapidly evolving branch of a more general field of Artificial Intelligence. During the last ten years it has received a lot of attention due to a series of very impressive algorithmic results that slowly become comparable to a human-level performance on many real-world applications ranging from image recognition, speech generation to language translation and even playing strategy games.

During my talk, I’ll start by defining main components of machine learning algorithms, from collecting and preparing the data for training and evaluating the model performance. I will then give a historic overview of the progress in the field during the last decade or so. I will specifically focus on the methods and algorithms that made a substantial difference in accuracy and performance of the method. Moving to present, I will present my analysis of the current trends to try to understand the dynamics of the field and what is the current focus of the community.

Finally, I would like to give a brief overview of the main conferences, journals, venues and platforms that people could follow in order to get the most recent news in Machine Learning. I will also go over a typical paper structure and will talk about what makes a paper successful and what reviewers typically pay attention to when reviewing papers.