Scholar
Jack Mayo
Google Scholar ID: Qwhl1AEAAAAJ
Korteweg-de Vries Institute for Mathematics, University of Amsterdam
Citations & Impact
Citations
144
H-index
6
i10-index
4
Publications
10
Co-authors
13
list available
Contact
No contact links provided.
Resume (English only)
Academic Achievements
- - Publications: 'Scale-free Unconstrained Online Learning for Curved Losses' accepted to COLT 2022
- - Awards: October 5th, 2020 - 'Unravelling intra-aggregate structural disorder using single-molecule spectroscopy' awarded with an Editor's Pick in Journal of the American Chemical Society
- - June 17th, 2020 - 'Full Counting Statistics of Topological Defects after Crossing a Phase Transition' awarded with an Editor's Choice in PRL
- - Reviewing: NeurIPS, AIStats, and TMLR
Research Experience
- - Research Projects: Developing efficient and adaptive algorithms for online learning, drawing inspiration and techniques from information theory, statistics, and optimization.
- - Position: PhD Student
- - Work Experience: Research visit to Csaba Szepesvári and colleagues at the University of Alberta, Edmonton; attended NeurIPS conference.
Education
- - Degree: PhD
- - School: University of Amsterdam
- - Supervisor: Dr. Tim van Erven
- - Time: Ongoing
- - Major: Mathematics (Machine Learning Theory)
- - Other Educational Experiences: Studies in non-equilibrium thermodynamics and condensed matter theory during BSc and MSc
Background
- - Research Interests: Parameter-free online learning, connections between statistical learning and optimization methods, Bandits and reinforcement learning
- - Professional Field: Machine Learning Theory
- - Brief Introduction: A fourth-year PhD student at the Korteweg-de Vries Institute for Mathematics, University of Amsterdam, working on the theory and mathematics underlying a broad class of decision-theoretic problems and modern machine learning methods.
Miscellany
- - Personal Interests: Teaching Assistant for the Machine Learning Theory course, co-organizing the NeurIPS Debriefing event
