ML Anthology

Marinov, Teodor Vanislavov

14 publications

ICML 2025 Design Considerations in Offline Preference-Based RL Alekh Agarwal, Christoph Dann, Teodor Vanislavov Marinov
NeurIPS 2025 Principled Model Routing for Unknown Mixtures of Source Domains Christoph Dann, Yishay Mansour, Teodor Vanislavov Marinov, Mehryar Mohri
ALT 2024 A Mechanism for Sample-Efficient In-Context Learning for Sparse Retrieval Tasks Jacob Abernethy, Alekh Agarwal, Teodor Vanislavov Marinov, Manfred K. Warmuth
NeurIPSW 2024 Domain Adaptation for Robust Model Routing Christoph Dann, Yishay Mansour, Teodor Vanislavov Marinov, Mehryar Mohri
COLT 2022 Open Problem: Finite-Time Instance Dependent Optimality for Stochastic Online Learning with Feedback Graphs Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert
NeurIPS 2022 Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert
NeurIPS 2021 Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning Christoph Dann, Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert
NeurIPS 2021 The Pareto Frontier of Model Selection for General Contextual Bandits Teodor Vanislavov Marinov, Julian Zimmert
NeurIPS 2019 Bandits with Feedback Graphs and Switching Costs Raman Arora, Teodor Vanislavov Marinov, Mehryar Mohri
NeurIPS 2019 Efficient Convex Relaxations for Streaming PCA Raman Arora, Teodor Vanislavov Marinov
NeurIPS 2018 Policy Regret in Repeated Games Raman Arora, Michael Dinitz, Teodor Vanislavov Marinov, Mehryar Mohri
NeurIPS 2018 Streaming Kernel PCA with $\tilde{O}(\sqrt{n})$ Random Features Enayat Ullah, Poorya Mianjy, Teodor Vanislavov Marinov, Raman Arora
ICML 2018 Streaming Principal Component Analysis in Noisy Setting Teodor Vanislavov Marinov, Poorya Mianjy, Raman Arora
NeurIPS 2017 Stochastic Approximation for Canonical Correlation Analysis Raman Arora, Teodor Vanislavov Marinov, Poorya Mianjy, Nati Srebro