Stochastic Optimization for Multiview Representation Learning using Partial Least Squares. - Raman Arora; Poorya Mianjy; Teodor V. Marinov (ICML, 2016)

Stochastic Approximation for Canonical Correlation Analysis. - Raman Arora; Teodor Vanislavov Marinov; Poorya Mianjy; Nati Srebro (NIPS, 2017)

Stochastic Approximation for Canonical Correlation Analysis. - Raman Arora; Teodor V. Marinov; Poorya Mianjy (CoRR, 2017)

Streaming Principal Component Analysis in Noisy Settings. - Teodor Vanislavov Marinov; Poorya Mianjy; Raman Arora (ICML, 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 (NeurIPS, 2018)

Streaming Kernel PCA with Õ(√n) Random Features. - Enayat Ullah; Poorya Mianjy; Teodor V. Marinov; Raman Arora (CoRR, 2018)

Efficient Convex Relaxations for Streaming PCA. - Raman Arora; Teodor Vanislavov Marinov (NeurIPS, 2019)

Bandits with Feedback Graphs and Switching Costs. - Raman Arora; Teodor Vanislavov Marinov; Mehryar Mohri (NeurIPS, 2019)

Private Stochastic Convex Optimization: Efficient Algorithms for Non-smooth Objectives. - Raman Arora; Teodor V. Marinov; Enayat Ullah (CoRR, 2020)

Corralling Stochastic Bandit Algorithms. - Raman Arora; Teodor Vanislavov Marinov; Mehryar Mohri (AISTATS, 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, 2021)

Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality. - Teodor Vanislavov Marinov; Mehryar Mohri; Julian Zimmert (NeurIPS, 2022)

Dimension Independent Generalization of DP-SGD for Overparameterized Smooth Convex Optimization. - Yi-An Ma; Teodor Vanislavov Marinov; Tong Zhang 001 (CoRR, 2022)

Multiple-policy High-confidence Policy Evaluation. - Christoph Dann; Mohammad Ghavamzadeh; Teodor V. Marinov (AISTATS, 2023)

Leveraging User-Triggered Supervision in Contextual Bandits. - Alekh Agarwal; Claudio Gentile; Teodor V. Marinov (CoRR, 2023)

A Mechanism for Sample-Efficient In-Context Learning for Sparse Retrieval Tasks. - Jacob D. Abernethy; Alekh Agarwal; Teodor Vanislavov Marinov; Manfred K. Warmuth (ALT, 2024)

PRODuctive bandits: Importance Weighting No More. - Julian Zimmert; Teodor Vanislavov Marinov (NeurIPS, 2024)

Offline Imitation Learning from Multiple Baselines with Applications to Compiler Optimization. - Teodor V. Marinov; Alekh Agarwal; Mircea Trofin (CoRR, 2024)

Incentive-compatible Bandits: Importance Weighting No More. - Julian Zimmert; Teodor V. Marinov (CoRR, 2024)

Design Considerations in Offline Preference-based RL. - Alekh Agarwal; Christoph Dann; Teodor V. Marinov (CoRR, 2025)