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Disambiguation of "Du, Simon S."

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Fast and Sample Efficient Inductive Matrix Completion via Multi-Phase Procrustes Flow.

, , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 5751-5760. PMLR, (2018)

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To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Simon S Lee

Marcus Simon

Erstellung und Validierung eines Fragebogens für die Patientenbeurteilung der perioperativen Phase, PPP-Fragebogen. Uni Marburg, (2009)

Christine Simon

Vollblutaggregation beim Hund: Vergleich der Methode nach Born mit einer errechneten Aggregation nach Thrombozytenzählung mittels konventioneller Hämatologiesysteme. Uni Gießen, (2009)

Juan Du

Fei Du

 

Other publications of authors with the same name

Over-Parameterization Exponentially Slows Down Gradient Descent for Learning a Single Neuron., and . COLT, volume 195 of Proceedings of Machine Learning Research, page 1155-1198. PMLR, (2023)Fine-Grained Gap-Dependent Bounds for Tabular MDPs via Adaptive Multi-Step Bootstrap., , and . COLT, volume 134 of Proceedings of Machine Learning Research, page 4438-4472. PMLR, (2021)On Reinforcement Learning with Adversarial Corruption and Its Application to Block MDP., , , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 11296-11306. PMLR, (2021)Improved Corruption Robust Algorithms for Episodic Reinforcement Learning., , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 1561-1570. PMLR, (2021)First-Order Regret in Reinforcement Learning with Linear Function Approximation: A Robust Estimation Approach., , , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 22384-22429. PMLR, (2022)Is Long Horizon RL More Difficult Than Short Horizon RL?, , , and . NeurIPS, (2020)On Reward-Free Reinforcement Learning with Linear Function Approximation., , , and . NeurIPS, (2020)Planning with General Objective Functions: Going Beyond Total Rewards., , , , and . NeurIPS, (2020)Agnostic $Q$-learning with Function Approximation in Deterministic Systems: Near-Optimal Bounds on Approximation Error and Sample Complexity., , , and . NeurIPS, (2020)Near-Optimal Randomized Exploration for Tabular Markov Decision Processes., , , , and . NeurIPS, (2022)