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2020 – today
- 2024
[c13]Jacob D. Abernethy, Alekh Agarwal, Teodor Vanislavov Marinov, Manfred K. Warmuth:
A Mechanism for Sample-Efficient In-Context Learning for Sparse Retrieval Tasks. ALT 2024: 3-46- [i14]Teodor V. Marinov, Alekh Agarwal, Mircea Trofin:
Offline Imitation Learning from Multiple Baselines with Applications to Compiler Optimization. CoRR abs/2403.19462 (2024) - [i13]Julian Zimmert, Teodor V. Marinov:
Incentive-compatible Bandits: Importance Weighting No More. CoRR abs/2405.06480 (2024) - 2023
- [c12]Christoph Dann, Mohammad Ghavamzadeh, Teodor V. Marinov:
Multiple-policy High-confidence Policy Evaluation. AISTATS 2023: 9470-9487 - [i12]Alekh Agarwal, Claudio Gentile, Teodor V. Marinov:
Leveraging User-Triggered Supervision in Contextual Bandits. CoRR abs/2302.03784 (2023) - [i11]Jacob D. Abernethy, Alekh Agarwal, Teodor V. Marinov, Manfred K. Warmuth:
A Mechanism for Sample-Efficient In-Context Learning for Sparse Retrieval Tasks. CoRR abs/2305.17040 (2023) - 2022
- [c11]Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert:
Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality. NeurIPS 2022 - [i10]Yi-An Ma, Teodor Vanislavov Marinov, Tong Zhang:
Dimension Independent Generalization of DP-SGD for Overparameterized Smooth Convex Optimization. CoRR abs/2206.01836 (2022) - [i9]Teodor V. Marinov, Mehryar Mohri, Julian Zimmert:
Stochastic Online Learning with Feedback Graphs: Finite-Time and Asymptotic Optimality. CoRR abs/2206.10022 (2022) - 2021
- [c10]Raman Arora, Teodor Vanislavov Marinov, Mehryar Mohri:
Corralling Stochastic Bandit Algorithms. AISTATS 2021: 2116-2124 - [c9]Christoph Dann, Teodor Vanislavov Marinov, Mehryar Mohri, Julian Zimmert:
Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning. NeurIPS 2021: 1-12 - [c8]Teodor Vanislavov Marinov, Julian Zimmert:
The Pareto Frontier of model selection for general Contextual Bandits. NeurIPS 2021: 17956-17967 - [i8]Christoph Dann, Teodor V. Marinov, Mehryar Mohri, Julian Zimmert:
Beyond Value-Function Gaps: Improved Instance-Dependent Regret Bounds for Episodic Reinforcement Learning. CoRR abs/2107.01264 (2021) - [i7]Teodor V. Marinov, Julian Zimmert:
The Pareto Frontier of model selection for general Contextual Bandits. CoRR abs/2110.13282 (2021) - 2020
- [i6]Raman Arora, Teodor V. Marinov, Enayat Ullah:
Private Stochastic Convex Optimization: Efficient Algorithms for Non-smooth Objectives. CoRR abs/2002.09609 (2020) - [i5]Raman Arora, Teodor V. Marinov, Mehryar Mohri:
Corralling Stochastic Bandit Algorithms. CoRR abs/2006.09255 (2020)
2010 – 2019
- 2019
- [c7]Raman Arora, Teodor Vanislavov Marinov, Mehryar Mohri:
Bandits with Feedback Graphs and Switching Costs. NeurIPS 2019: 10397-10407 - [c6]Raman Arora, Teodor Vanislavov Marinov:
Efficient Convex Relaxations for Streaming PCA. NeurIPS 2019: 10496-10505 - [i4]Raman Arora, Teodor V. Marinov, Mehryar Mohri:
Bandits with Feedback Graphs and Switching Costs. CoRR abs/1907.12189 (2019) - 2018
- [c5]Teodor Vanislavov Marinov, Poorya Mianjy, Raman Arora:
Streaming Principal Component Analysis in Noisy Settings. ICML 2018: 3410-3419 - [c4]Raman Arora, Michael Dinitz
, Teodor Vanislavov Marinov, Mehryar Mohri:
Policy Regret in Repeated Games. NeurIPS 2018: 6733-6742 - [c3]Enayat Ullah, Poorya Mianjy, Teodor Vanislavov Marinov, Raman Arora:
Streaming Kernel PCA with \tilde{O}(\sqrt{n}) Random Features. NeurIPS 2018: 7322-7332 - [i3]Enayat Ullah, Poorya Mianjy, Teodor V. Marinov, Raman Arora:
Streaming Kernel PCA with Õ(√n) Random Features. CoRR abs/1808.00934 (2018) - [i2]Raman Arora, Michael Dinitz, Teodor V. Marinov, Mehryar Mohri:
Policy Regret in Repeated Games. CoRR abs/1811.04127 (2018) - 2017
- [c2]Raman Arora, Teodor Vanislavov Marinov, Poorya Mianjy, Nati Srebro:
Stochastic Approximation for Canonical Correlation Analysis. NIPS 2017: 4775-4784 - [i1]Raman Arora, Teodor V. Marinov, Poorya Mianjy:
Stochastic Approximation for Canonical Correlation Analysis. CoRR abs/1702.06818 (2017) - 2016
- [c1]Raman Arora, Poorya Mianjy, Teodor V. Marinov:
Stochastic Optimization for Multiview Representation Learning using Partial Least Squares. ICML 2016: 1786-1794
Coauthor Index
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