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Lukasz Szpruch
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2020 – today
- 2024
- [j12]Lukasz Szpruch
, Tanut Treetanthiploet
Optimal Scheduling of Entropy Regularizer for Continuous-Time Linear-Quadratic Reinforcement Learning. SIAM J. Control. Optim. 62(1): 135-166 (2024) - [j11]David Siska, Lukasz Szpruch:
Gradient Flows for Regularized Stochastic Control Problems. SIAM J. Control. Optim. 62(4): 2036-2070 (2024) - [c6]Gholamali Aminian, Yixuan He, Gesine Reinert, Lukasz Szpruch, Samuel N. Cohen:
Generalization Error of Graph Neural Networks in the Mean-field Regime. ICML 2024 - [i26]Bekzhan Kerimkulov, David Siska, Lukasz Szpruch, Yufei Zhang:
Mirror Descent for Stochastic Control Problems with Measure-valued Controls. CoRR abs/2401.01198 (2024) - [i25]Gholamali Aminian, Yixuan He, Gesine Reinert, Lukasz Szpruch, Samuel N. Cohen:
Generalization Error of Graph Neural Networks in the Mean-field Regime. CoRR abs/2402.07025 (2024) - [i24]Razvan-Andrei Lascu, Mateusz B. Majka, Lukasz Szpruch:
Mirror Descent-Ascent for mean-field min-max problems. CoRR abs/2402.08106 (2024) - [i23]Lukasz Szpruch, Tanut Treetanthiploet, Yufei Zhang:
ε-Policy Gradient for Online Pricing. CoRR abs/2405.03624 (2024) - [i22]Razvan-Andrei Lascu, Mateusz B. Majka, Lukasz Szpruch:
A Fisher-Rao gradient flow for entropic mean-field min-max games. CoRR abs/2405.15834 (2024) - [i21]Emmanuel Gobet, Adrien Richou, Lukasz Szpruch:
Numerical approximation of ergodic BSDEs using non linear Feynman-Kac formulas. CoRR abs/2407.09034 (2024) - [i20]Gholamali Aminian, Lukasz Szpruch, Samuel N. Cohen:
Understanding Transfer Learning via Mean-field Analysis. CoRR abs/2410.17128 (2024) - 2023
- [j10]Andrew Duncan, Nikolas Nüsken, Lukasz Szpruch:
On the geometry of Stein variational gradient descent. J. Mach. Learn. Res. 24: 56:1-56:39 (2023) - [j9]Mateusz B. Majka
Multi-index antithetic stochastic gradient algorithm. Stat. Comput. 33(2): 49 (2023) - [c5]Samuel N. Cohen, Marc Sabate Vidales, David Siska, Lukasz Szpruch:
Inefficiency of CFMs: Hedging Perspective and Agent-Based Simulations. FC Workshops 2023: 303-319 - [i19]Gholamali Aminian, Samuel N. Cohen, Lukasz Szpruch:
Mean-field Analysis of Generalization Errors. CoRR abs/2306.11623 (2023) - [i18]Tanut Treetanthiploet, Yufei Zhang, Lukasz Szpruch, Isaac Bowers-Barnard, Henrietta Ridley, James Hickey, Chris Pearce:
Insurance pricing on price comparison websites via reinforcement learning. CoRR abs/2308.06935 (2023) - [i17]Carsten Maple, Lukasz Szpruch, Gregory Epiphaniou, Kalina Staykova, Simran Singh, William Penwarden, Yisi Wen, Zijian Wang, Jagdish Hariharan, Pavle Avramovic:
The AI Revolution: Opportunities and Challenges for the Finance Sector. CoRR abs/2308.16538 (2023) - [i16]Bekzhan Kerimkulov, James-Michael Leahy, David Siska, Lukasz Szpruch, Yufei Zhang:
A Fisher-Rao gradient flow for entropy-regularised Markov decision processes in Polish spaces. CoRR abs/2310.02951 (2023) - 2022
- [c4]James-Michael Leahy
Convergence of Policy Gradient for Entropy Regularized MDPs with Neural Network Approximation in the Mean-Field Regime. ICML 2022: 12222-12252 - [i15]Bekzhan Kerimkulov, James-Michael Leahy, David Siska, Lukasz Szpruch:
Convergence of policy gradient for entropy regularized MDPs with neural network approximation in the mean-field regime. CoRR abs/2201.07296 (2022) - [i14]James Jordon, Lukasz Szpruch, Florimond Houssiau, Mirko Bottarelli, Giovanni Cherubin, Carsten Maple, Samuel N. Cohen, Adrian Weller:
Synthetic Data - what, why and how? CoRR abs/2205.03257 (2022) - [i13]Lukasz Szpruch, Tanut Treetanthiploet, Yufei Zhang:
Optimal scheduling of entropy regulariser for continuous-time linear-quadratic reinforcement learning. CoRR abs/2208.04466 (2022) - [i12]Florimond Houssiau, James Jordon, Samuel N. Cohen, Owen Daniel, Andrew Elliott
TAPAS: a Toolbox for Adversarial Privacy Auditing of Synthetic Data. CoRR abs/2211.06550 (2022) - [i11]Florimond Houssiau, Samuel N. Cohen, Lukasz Szpruch, Owen Daniel, Michaela G. Lawrence
A Framework for Auditable Synthetic Data Generation. CoRR abs/2211.11540 (2022) - 2021
- [c3]Hao Ni, Lukasz Szpruch, Marc Sabate Vidales, Baoren Xiao, Magnus Wiese, Shujian Liao:
Sig-wasserstein GANs for time series generation. ICAIF 2021: 28:1-28:8 - [c2]Haoyang Cao, Samuel N. Cohen, Lukasz Szpruch:
Identifiability in inverse reinforcement learning. NeurIPS 2021: 12362-12373 - [e1]Anisoara Calinescu, Lukasz Szpruch:
ICAIF'21: 2nd ACM International Conference on AI in Finance, Virtual Event, November 3 - 5, 2021. ACM 2021, ISBN 978-1-4503-9148-1 [contents] - [i10]Haoyang Cao, Samuel N. Cohen, Lukasz Szpruch:
Identifiability in inverse reinforcement learning. CoRR abs/2106.03498 (2021) - [i9]Hao Ni, Lukasz Szpruch, Marc Sabate Vidales, Baoren Xiao, Magnus Wiese, Shujian Liao:
Sig-Wasserstein GANs for Time Series Generation. CoRR abs/2111.01207 (2021) - [i8]Lukasz Szpruch, Tanut Treetanthiploet, Yufei Zhang:
Exploration-exploitation trade-off for continuous-time episodic reinforcement learning with linear-convex models. CoRR abs/2112.10264 (2021) - 2020
- [j8]Michael B. Giles
Multi-level Monte Carlo methods for the approximation of invariant measures of stochastic differential equations. Stat. Comput. 30(3): 507-524 (2020) - [j7]Bekzhan Kerimkulov, David Siska
Exponential Convergence and Stability of Howard's Policy Improvement Algorithm for Controlled Diffusions. SIAM J. Control. Optim. 58(3): 1314-1340 (2020) - [c1]Imanol Pérez Arribas, Cristopher Salvi, Lukasz Szpruch:
Sig-SDEs model for quantitative finance. ICAIF 2020: 7:1-7:8 - [i7]Hao Ni, Lukasz Szpruch, Magnus Wiese, Shujian Liao, Baoren Xiao:
Conditional Sig-Wasserstein GANs for Time Series Generation. CoRR abs/2006.05421 (2020) - [i6]David Siska, Lukasz Szpruch:
Gradient Flows for Regularized Stochastic Control Problems. CoRR abs/2006.05956 (2020) - [i5]Mateusz B. Majka, Marc Sabate Vidales, Lukasz Szpruch:
Multi-index Antithetic Stochastic Gradient Algorithm. CoRR abs/2006.06102 (2020) - [i4]Patryk Gierjatowicz, Marc Sabate Vidales, David Siska, Lukasz Szpruch, Zan Zuric:
Robust pricing and hedging via neural SDEs. CoRR abs/2007.04154 (2020)
2010 – 2019
- 2019
- [j6]Andreas Neuenkirch
An Adaptive Euler-Maruyama Scheme for Stochastic Differential Equations with Discontinuous Drift and its Convergence Analysis. SIAM J. Numer. Anal. 57(1): 378-403 (2019) - [i3]Denis Belomestny, Lukasz Szpruch, Shuren Tan:
Iterative Multilevel density estimation for McKean-Vlasov SDEs via projections. CoRR abs/1909.11717 (2019) - [i2]Andrew Duncan, Nikolas Nüsken, Lukasz Szpruch:
On the geometry of Stein variational gradient descent. CoRR abs/1912.00894 (2019) - 2018
- [j5]Lukasz Szpruch, Xiling Zhang
V-integrability, asymptotic stability and comparison property of explicit numerical schemes for non-linear SDEs. Math. Comput. 87(310): 755-783 (2018) - [i1]Marc Sabate Vidales, David Siska, Lukasz Szpruch:
Martingale Functional Control variates via Deep Learning. CoRR abs/1810.05094 (2018) - 2014
- [j4]Andreas Neuenkirch
First order strong approximations of scalar SDEs defined in a domain. Numerische Mathematik 128(1): 103-136 (2014) - 2013
- [j3]Xuerong Mao
Strong convergence and stability of implicit numerical methods for stochastic differential equations with non-globally Lipschitz continuous coefficients. J. Comput. Appl. Math. 238: 14-28 (2013) - 2010
- [j2]Fuke Wu, Xuerong Mao
Almost sure exponential stability of numerical solutions for stochastic delay differential equations. Numerische Mathematik 115(4): 681-697 (2010)
2000 – 2009
- 2009
- [j1]Lukasz Szpruch, Desmond J. Higham:
Comparing Hitting Time Behavior of Markov Jump Processes and Their Diffusion Approximations. Multiscale Model. Simul. 8(2): 605-621 (2009)
Coauthor Index
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