Zobrazeno 1 - 10
of 168
pro vyhledávání: '"Spindler, Martin"'
Collusion is a complex phenomenon in which companies secretly collaborate to engage in fraudulent practices. This paper presents an innovative methodology for detecting and predicting collusion patterns in different national markets using neural netw
Externí odkaz:
http://arxiv.org/abs/2410.07091
Autor:
Wasserbacher, Helmut, Spindler, Martin
Why do companies choose particular capital structures? A compelling answer to this question remains elusive despite extensive research. In this article, we use double machine learning to examine the heterogeneous causal effect of credit ratings on le
Externí odkaz:
http://arxiv.org/abs/2406.18936
Autor:
Schwarz, Philipp, Schacht, Oliver, Klaassen, Sven, Grünbaum, Daniel, Imhof, Sebastian, Spindler, Martin
In this paper, we present a data-driven model for estimating optimal rework policies in manufacturing systems. We consider a single production stage within a multistage, lot-based system that allows for optional rework steps. While the rework decisio
Externí odkaz:
http://arxiv.org/abs/2406.11308
Autor:
Chernozhukov, Victor, Hansen, Christian, Kallus, Nathan, Spindler, Martin, Syrgkanis, Vasilis
An introduction to the emerging fusion of machine learning and causal inference. The book presents ideas from classical structural equation models (SEMs) and their modern AI equivalent, directed acyclical graphs (DAGs) and structural causal models (S
Externí odkaz:
http://arxiv.org/abs/2403.02467
Proper hyperparameter tuning is essential for achieving optimal performance of modern machine learning (ML) methods in predictive tasks. While there is an extensive literature on tuning ML learners for prediction, there is only little guidance availa
Externí odkaz:
http://arxiv.org/abs/2402.04674
Autor:
Klaassen, Sven, Teichert-Kluge, Jan, Bach, Philipp, Chernozhukov, Victor, Spindler, Martin, Vijaykumar, Suhas
This paper explores the use of unstructured, multimodal data, namely text and images, in causal inference and treatment effect estimation. We propose a neural network architecture that is adapted to the double machine learning (DML) framework, specif
Externí odkaz:
http://arxiv.org/abs/2402.01785
Autor:
Schacht, Oliver, Klaassen, Sven, Schwarz, Philipp, Spindler, Martin, Grünbaum, Daniel, Imhof, Sebastian
In manufacturing, rework refers to an optional step of a production process which aims to eliminate errors or remedy products that do not meet the desired quality standards. Reworking a production lot involves repeating a previous production stage wi
Externí odkaz:
http://arxiv.org/abs/2306.04223
Autor:
Yuan, Zihao, Spindler, Martin
The major contributions of this paper lie in two aspects. Firstly, we focus on deriving Bernstein-type inequalities for both geometric and algebraic irregularly-spaced NED random fields, which contain time series as special case. Furthermore, by intr
Externí odkaz:
http://arxiv.org/abs/2208.11433
Autor:
Yuan, Zihao, Spindler, Martin
There are many processes, particularly dynamic systems, that cannot be described as strong mixing processes. \citet{maume2006exponential} introduced a new mixing coefficient called C-mixing, which includes a large class of dynamic systems. Based on t
Externí odkaz:
http://arxiv.org/abs/2208.11481