Zobrazeno 1 - 10
of 9 679
pro vyhledávání: '"Luedtke A"'
Publikováno v:
Journal of Causal Inference, Vol 10, Iss 1, Pp 480-493 (2022)
Estimation and evaluation of individualized treatment rules have been studied extensively, but real-world treatment resource constraints have received limited attention in existing methods. We investigate a setting in which treatment is intervened up
Externí odkaz:
https://doaj.org/article/04dbd0458bd540fd8abfa42dc7cb1e41
Real-time systems are intrinsic components of many pivotal applications, such as self-driving vehicles, aerospace and defense systems. The trend in these applications is to incorporate multiple tasks onto fewer, more powerful hardware platforms, e.g.
Externí odkaz:
http://arxiv.org/abs/2410.01528
When assessing the causal effect of a binary exposure using observational data, confounder imbalance across exposure arms must be addressed. Matching methods, including propensity score-based matching, can be used to deconfound the causal relationshi
Externí odkaz:
http://arxiv.org/abs/2409.19230
Autor:
Marton, Sascha, Grams, Tim, Vogt, Florian, Lüdtke, Stefan, Bartelt, Christian, Stuckenschmidt, Heiner
Reinforcement learning (RL) has seen significant success across various domains, but its adoption is often limited by the black-box nature of neural network policies, making them difficult to interpret. In contrast, symbolic policies allow representi
Externí odkaz:
http://arxiv.org/abs/2408.08761
We consider a two-stage stochastic decision problem where the decision-maker has the opportunity to obtain information about the distribution of the random variables $\xi$ that appear in the problem through a set of discrete actions that we refer to
Externí odkaz:
http://arxiv.org/abs/2407.10669
Autor:
Tschalzev, Andrej, Marton, Sascha, Lüdtke, Stefan, Bartelt, Christian, Stuckenschmidt, Heiner
Tabular data is prevalent in real-world machine learning applications, and new models for supervised learning of tabular data are frequently proposed. Comparative studies assessing the performance of models typically consist of model-centric evaluati
Externí odkaz:
http://arxiv.org/abs/2407.02112
Autor:
Tschalzev, Andrej, Nitschke, Paul, Kirchdorfer, Lukas, Lüdtke, Stefan, Bartelt, Christian, Stuckenschmidt, Heiner
Neural networks often assume independence among input data samples, disregarding correlations arising from inherent clustering patterns in real-world datasets (e.g., due to different sites or repeated measurements). Recently, mixed effects neural net
Externí odkaz:
http://arxiv.org/abs/2407.01115
Autor:
Rossmann, Ramsey, Anitescu, Mihai, Bessac, Julie, Ferris, Michael, Krock, Mitchell, Luedtke, James, Roald, Line
Power grid expansion planning requires making large investment decisions in the present that will impact the future cost and reliability of a system exposed to wide-ranging uncertainties. Extreme temperatures can pose significant challenges to provid
Externí odkaz:
http://arxiv.org/abs/2405.18538
Autor:
Luedtke, Alex
We introduce an algorithm that simplifies the construction of efficient estimators, making them accessible to a broader audience. 'Dimple' takes as input computer code representing a parameter of interest and outputs an efficient estimator. Unlike st
Externí odkaz:
http://arxiv.org/abs/2405.08675
Autor:
Lüdtke, Martin
The Chabauty--Kim method and its refined variant by Betts and Dogra aim to cut out the $S$-integral points $X(\mathbb{Z}_S)$ on a curve inside the $p$-adic points $X(\mathbb{Z}_p)$ by producing enough Coleman functions vanishing on them. We derive ne
Externí odkaz:
http://arxiv.org/abs/2402.03573