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Nelson Vadori
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2020 – today
- 2024
- [c8]Nelson Vadori, Rahul Savani:
Ordinal Potential-based Player Rating. AISTATS 2024: 118-126 - [i10]Antoine Gorceix, Bastien Le Chenadec, Ahmad Rammal, Nelson Vadori, Manuela Veloso:
Learning Mathematical Rules with Large Language Models. CoRR abs/2410.16973 (2024) - 2023
- [c7]Nelson Vadori
:
Calibration of Derivative Pricing Models: a Multi-Agent Reinforcement Learning Perspective. ICAIF 2023: 253-260 - [c6]Xuxi Chen, Nelson Vadori, Tianlong Chen, Zhangyang Wang:
Learning to Optimize Differentiable Games. ICML 2023: 5036-5051 - [i9]Nelson Vadori, Rahul Savani:
Ordinal Potential-based Player Rating. CoRR abs/2306.05366 (2023) - 2022
- [c5]Nelson Vadori, Rahul Savani, Thomas Spooner, Sumitra Ganesh:
Consensus Multiplicative Weights Update: Learning to Learn using Projector-based Game Signatures. ICML 2022: 21901-21926 - [i8]Nelson Vadori:
Calibration of Derivative Pricing Models: a Multi-Agent Reinforcement Learning Perspective. CoRR abs/2203.06865 (2022) - [i7]Nelson Vadori, Leo Ardon, Sumitra Ganesh, Thomas Spooner, Selim Amrouni, Jared Vann, Mengda Xu, Zeyu Zheng, Tucker Balch, Manuela Veloso:
Towards Multi-Agent Reinforcement Learning driven Over-The-Counter Market Simulations. CoRR abs/2210.07184 (2022) - 2021
- [c4]Leo Ardon, Nelson Vadori, Thomas Spooner, Mengda Xu, Jared Vann, Sumitra Ganesh:
Towards a fully rl-based market simulator. ICAIF 2021: 7:1-7:9 - [c3]Thomas Spooner, Nelson Vadori, Sumitra Ganesh:
Factored Policy Gradients: Leveraging Structure for Efficient Learning in MOMDPs. NeurIPS 2021: 5481-5493 - [i6]Thomas Spooner, Nelson Vadori, Sumitra Ganesh:
Causal Policy Gradients. CoRR abs/2102.10362 (2021) - [i5]Nelson Vadori, Rahul Savani
Consensus Multiplicative Weights Update: Learning to Learn using Projector-based Game Signatures. CoRR abs/2106.02615 (2021) - [i4]Leo Ardon, Nelson Vadori, Thomas Spooner, Mengda Xu, Jared Vann, Sumitra Ganesh:
Towards a fully RL-based Market Simulator. CoRR abs/2110.06829 (2021) - 2020
- [c2]Nelson Vadori, Sumitra Ganesh, Prashant P. Reddy, Manuela Veloso:
Risk-sensitive reinforcement learning: a martingale approach to reward uncertainty. ICAIF 2020: 28:1-28:9 - [c1]Nelson Vadori, Sumitra Ganesh, Prashant P. Reddy, Manuela Veloso:
Calibration of Shared Equilibria in General Sum Partially Observable Markov Games. NeurIPS 2020 - [i3]Nelson Vadori, Sumitra Ganesh, Prashant P. Reddy, Manuela Veloso:
Risk-Sensitive Reinforcement Learning: a Martingale Approach to Reward Uncertainty. CoRR abs/2006.12686 (2020) - [i2]Nelson Vadori, Sumitra Ganesh, Prashant P. Reddy, Manuela Veloso:
Calibration of Shared Equilibria in General Sum Partially Observable Markov Games. CoRR abs/2006.13085 (2020)
2010 – 2019
- 2019
- [i1]Sumitra Ganesh, Nelson Vadori, Mengda Xu, Hua Zheng, Prashant P. Reddy, Manuela Veloso:
Reinforcement Learning for Market Making in a Multi-agent Dealer Market. CoRR abs/1911.05892 (2019) - 2017
- [j1]Anatoliy Swishchuk, Nelson Vadori:
A Semi-Markovian Modeling of Limit Order Markets. SIAM J. Financial Math. 8(1): 240-273 (2017)
Coauthor Index
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last updated on 2024-11-28 20:34 CET by the dblp team
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