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yuriy nevmyvaka
yuriy nevmyvaka
Managing Director, ML Research, Morgan Stanley
Adresse e-mail validée de morganstanley.com
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Reinforcement learning for optimized trade execution
Y Nevmyvaka, Y Feng, M Kearns
Proceedings of the 23rd international conference on Machine learning, 673-680, 2006
3802006
The Penn-Lehman automated trading project
M Kearns, L Ortiz
IEEE Intelligent systems 18 (6), 22-31, 2003
1292003
Machine learning for market microstructure and high frequency trading
M Kearns, Y Nevmyvaka
High Frequency Trading: New Realities for Traders, Markets, and Regulators 72, 2013
1052013
Empirical limitations on high frequency trading profitability
M Kearns, A Kulesza, Y Nevmyvaka
arXiv preprint arXiv:1007.2593, 2010
1052010
Lag-llama: Towards foundation models for time series forecasting
K Rasul, A Ashok, AR Williams, A Khorasani, G Adamopoulos, ...
R0-FoMo: Robustness of Few-shot and Zero-shot Learning in Large Foundation …, 2023
1042023
Censored exploration and the dark pool problem
K Ganchev, Y Nevmyvaka, M Kearns, JW Vaughan
Communications of the ACM 53 (5), 99-107, 2010
912010
Market making and mean reversion
T Chakraborty, M Kearns
Proceedings of the 12th ACM conference on Electronic commerce, 307-314, 2011
792011
Lag-llama: Towards foundation models for probabilistic time series forecasting
K Rasul, A Ashok, AR Williams, H Ghonia, R Bhagwatkar, A Khorasani, ...
Preprint, 2024
502024
Modeling temporal data as continuous functions with stochastic process diffusion
M Biloš, K Rasul, A Schneider, Y Nevmyvaka, S Günnemann
International Conference on Machine Learning, 2452-2470, 2023
392023
Empowering Time Series Analysis with Large Language Models: A Survey
Y Jiang, Z Pan, X Zhang, S Garg, A Schneider, Y Nevmyvaka, D Song
arXiv preprint arXiv:2402.03182, 2024
342024
High-frequency trading: New realities for traders, markets and regulators
D Easley, L de Prado, M Mailoc, M O'Hara
(No Title), 2013
332013
Provably convergent Schrödinger bridge with applications to probabilistic time series imputation
Y Chen, W Deng, S Fang, F Li, NT Yang, Y Zhang, K Rasul, S Zhe, ...
International Conference on Machine Learning, 4485-4513, 2023
282023
IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
Z Pan, Y Jiang, S Garg, A Schneider, Y Nevmyvaka, D Song
Forty-first International Conference on Machine Learning, 2024
272024
Electronic trading in order-driven markets: efficient execution
Y Nevmyvaka, M Kearns, M Papandreou, K Sycara
Seventh IEEE International Conference on E-Commerce Technology (CEC'05), 190-197, 2005
272005
Modeling temporal data as continuous functions with process diffusion
M Biloš, K Rasul, A Schneider, Y Nevmyvaka, S Günnemann
182022
Machine learning for market microstructure and high frequency trading, High Frequency Trading: New Realities for Traders, Markets, and Regulators
M Kearns, Y Nevmyvaka
Risk Books, 2013
142013
Automl decathlon: Diverse tasks, modern methods, and efficiency at scale
N Roberts, S Guo, C Xu, A Talwalkar, D Lander, L Tao, L Cai, S Niu, ...
NeurIPS 2022 Competition Track, 151-170, 2023
82023
Variational Schr\" odinger Diffusion Models
W Deng, W Luo, Y Tan, M Biloš, Y Chen, Y Nevmyvaka, RTQ Chen
arXiv preprint arXiv:2405.04795, 2024
72024
Empirical Limitations On High-Frequency Trading Profitability SSRN Working Paper, 17
M Kearns, A Kulesza, Y Nevmyvaka
September, 2010
72010
Risk Bounds on Aleatoric Uncertainty Recovery
Y Zhang, J Lin, F Li, Y Adler, K Rasul, A Schneider, Y Nevmyvaka
International Conference on Artificial Intelligence and Statistics, 6015-6036, 2023
62023
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