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1.
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Covariate distribution shifts and adversarial perturbations present robustness challenges to the conventional statistical learning framework: mild shifts in the test cova [...]
24 May 2024 |
Econometrics and Statistics |
Article |
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2.
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Opinion summarization and sentiment classification are key processes for understanding, analyzing, and leveraging information from customer opinions. The rapid and ceasel [...]
20 April 2024 |
Econometrics and Statistics |
Article |
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3.
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In this article, we introduce a package, ddml, for double/debiased machine learning in Stata. Estimators of causal parameters for five different econometric models are su [...]
19 March 2024 |
Econometrics and Statistics; Kenneth C. Griffin Department of Economics |
Article |
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4.
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Contains the code and datasets necessary to replicate all figures and tables in the paper.
Note: One dataset on the "Gaokao experiment" (Section 6.2 of main [...]
11 September 2023 |
Econometrics and Statistics |
Dataset |
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5.
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Measuring the effect of peers on individuals' outcomes is a challenging problem, in part because individuals often select peers who are similar in both observable and uno [...]
19 March 2024 |
Econometrics and Statistics |
Article |
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6.
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No abstract
20 May 2022 |
Econometrics and Statistics |
Article |
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7.
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The pystacked command implements stacked generalization (Wolpert, 1992, Neural Networks 5: 241–259) for regression and binary classification via Python’s scikit-learn [...]
21 December 2023 |
Econometrics and Statistics |
Article |
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8.
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We propose a new simulation-based estimation method, adversarial estimation, for structural models. The estimator is formulated as the solution to a minimax problem betwe [...]
07 December 2023 |
Econometrics and Statistics |
Article |
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9.
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In the field of artificial intelligence, a combination of scale in data and model capacity enabled by unsupervised learning has led to major advances in representation le [...]
05 April 2021 |
Econometrics and Statistics |
Article |
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10.
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This paper briefly reviews the recent research in matrix-variate time series analysis, discusses some new developments, especially for seasonal time series, and demonstra [...]
02 November 2023 |
Econometrics and Statistics |
Article |
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11.
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A security price volatility estimator that is capable of accurately estimating price volatility in real-time or near real-time, and in low noise and high noise environmen [...]
27 August 2020 |
Econometrics and Statistics |
Patent |
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12.
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Systems, methods, and computer-readable storage media facilitating automated testing of datasets including natural language data are disclosed. In the disclosed embodimen [...]
24 September 2020 |
Econometrics and Statistics |
Patent |
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13.
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We propose a neural network-based approach to calculate the value of a chess square–piece combination. Our model takes a triplet (color, piece, square) as the input and [...]
24 September 2023 |
Econometrics and Statistics |
Article |
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14.
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Human disease studies using DNA microarrays in both clinical/observational and experimental/controlled studies are having increasing impact on our understanding of the co [...]
19 February 2009 |
Econometrics and Statistics |
Article |
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15.
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Systems, methods, and computer-readable storage media facilitating automated testing of datasets including natural language data are disclosed. In the disclosed embodimen [...]
04 October 2022 |
Econometrics and Statistics |
Patent |
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16.
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In this paper, we propose deep partial least squares for the estimation of high-dimensional nonlinear instrumental variable regression. As a precursor to a flexible deep [...]
19 June 2023 |
Econometrics and Statistics |
Article |
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17.
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Factor models have been widely used in recent years to model high-dimensional spatio-temporal data. However, the validity of employing factor models in a specific applica [...]
14 June 2023 |
Econometrics and Statistics |
Article |
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18.
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We study nonlinear optimization problems with a stochastic objective and deterministic equality and inequality constraints, which emerge in numerous applications includin [...]
02 March 2023 |
Econometrics and Statistics |
Article |
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19.
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We propose a computationally efficient method to construct nonparametric, heteroscedastic prediction bands for uncertainty quantification, with or without any user-specif [...]
19 August 2022 |
Econometrics and Statistics |
Article |
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20.
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Graphs representing complex systems often share a partial underlying structure across domains while retaining individual features. Thus, identifying common structures [...]
06 April 2022 |
Econometrics and Statistics |
Article |
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