Christina Lee Yu

Cornell University — United States

Decision Sciences · Social Sciences

8h-index197citations55works1.02yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Advanced Bandit Algorithms Research(14), Reinforcement Learning in Robotics(12), Sparse and Compressive Sensing Techniques(12), Tensor decomposition and applications(7), Smart Grid Energy Management(6)

Publications55 total

Experimentation Under Non-stationary Interference
arXiv (Cornell University)·2025Open Access
The asymptotics of the expected Betti numbers of preferential attachment clique complexes
Advances in Applied Probability·2025· 4 citedOpen Access
The Limits of Transfer Reinforcement Learning with Latent Low-rank Structure
arXiv (Cornell University)·2024Open Access
Entry-Specific Matrix Estimation under Arbitrary Sampling Patterns through the Lens of Network Flows
arXiv (Cornell University)·2024Open Access
Hierarchical Generalization Bounds for Deep Neural Networks
2024· 1 cited
Low-order outcomes and clustered designs: combining design and analysis for causal inference under network interference
arXiv (Cornell University)·2024· 2 citedOpen Access
Analysis of Two-Stage Rollout Designs with Clustering for Causal Inference under Network Interference
arXiv (Cornell University)·2024· 1 citedOpen Access
Information-Theoretic Generalization Bounds for Deep Neural Networks
arXiv (Cornell University)·2024· 1 citedOpen Access
Detection of small holes by the scale-invariant robust density-aware distance (RDAD) filtration
Journal of Applied and Computational Topology·2024· 1 cited
The SMART approach to instance-optimal online learning
arXiv (Cornell University)·2024Open Access
Overcoming the Long Horizon Barrier for Sample-Efficient Reinforcement Learning with Latent Low-Rank Structure
ACM SIGMETRICS Performance Evaluation Review·2023
Entry-Specific Bounds for Low-Rank Matrix Completion under Highly Non-Uniform Sampling
2023Open Access
Overcoming the Long Horizon Barrier for Sample-Efficient Reinforcement Learning with Latent Low-Rank Structure
2023
Matrix Estimation for Offline Reinforcement Learning with Low-Rank Structure
arXiv (Cornell University)·2023Open Access
Overcoming the Long Horizon Barrier for Sample-Efficient Reinforcement Learning with Latent Low-Rank Structure
Proceedings of the ACM on Measurement and Analysis of Computing Systems·2023· 4 cited
The Asymptotics of the Expected Betti Numbers of Preferential Attachment Clique Complexes
arXiv (Cornell University)·2023Open Access
Overcoming the Long Horizon Barrier for Sample-Efficient Reinforcement Learning with Latent Low-Rank Structure
ACM SIGMETRICS Performance Evaluation Review·2023
Robust Max Entrywise Error Bounds for Tensor Estimation From Sparse Observations via Similarity-Based Collaborative Filtering
IEEE Transactions on Information Theory·2023Open Access
Exploiting neighborhood interference with low-order interactions under unit randomized design
Journal of Causal Inference·2023· 5 citedOpen Access
Adaptive Discretization in Online Reinforcement Learning
Operations Research·2022· 11 citedOpen Access
page 1 of 3Next →

Frequent Co-authors

Siddhartha Banerjee(14), Sean R. Sinclair(13), Devavrat Shah(9), Matthew Eichhorn(5), Tyler Sam(5), Christian Borgs(4), Jennifer Chayes(4), Xumei Xi(4), Chunyin Siu(4), Gennady Samorodnitsky(4), Yudong Chen(4), Gauri Jain(3), Mayleen Cortez-Rodriguez(3), Edoardo M. Airoldi(2), Mayleen Cortez(2), Asuman Ozdaglar(2), Rongyi He(2), Nirandika Wanigasekara(2), Yudong Chen(2), Andrey Yao(2)