Hello! I am a final year PhD student at Boston University, advised by Prof. Yannis Paschalidis and Prof. Ashok Cutkosky.
I am broadly interested in the theoretical aspects of machine learning, optimization and control theory. Specifically, I work on adaptive online learning, i.e., designing online decision making algorithms that optimally exploit problem structures.
Recently I am thinking about how to systematically simplify the design and verification of online learning algorithms, from a continuous-time perspective. I am looking for a postdoc position starting in Fall 2023.
Prior to BU, I studied mechanical engineering at Tsinghua University.
Email address: zhiyuz [at] bu (dot) edu
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Research
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Unconstrained Dynamic Regret via Sparse Coding
ZZ, Ashok Cutkosky, Ioannis Paschalidis.
Preprint. -
Optimal Comparator Adaptive Online Learning with Switching Cost
ZZ, Ashok Cutkosky, Ioannis Paschalidis.
NeurIPS 2022. Also presented at ICML 2022 workshop. -
PDE-Based Optimal Strategy for Unconstrained Online Learning
ZZ, Ashok Cutkosky, Ioannis Paschalidis.
ICML 2022. -
Adversarial Tracking Control via Strongly Adaptive Online Learning with Memory
ZZ, Ashok Cutkosky, Ioannis Paschalidis.
AISTATS 2022. -
Provable Hierarchical Imitation Learning via EM
ZZ, Ioannis Paschalidis.
AISTATS 2021. Also presented at ICML 2020 Workshop.
Service
Reviewer for ICML, NeurIPS, AISTATS.
Top reviewer (10%) at AISTATS’22, ICML’22, NeurIPS’22.