Academic literature on the topic 'Counterfactual evaluation'
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Journal articles on the topic "Counterfactual evaluation":
Markman, Keith D., Matthew N. McMullen, Ronald A. Elizaga, and Nobuko Mizoguchi. "Counterfactual thinking and regulatory fit." Judgment and Decision Making 1, no. 2 (November 2006): 98–107. http://dx.doi.org/10.1017/s193029750000231x.
Bertolotti, Mauro, and Patrizia Catellani. "The Effects of Counterfactual Attacks on the Morality and Leadership of Different Professionals." Social Psychology 49, no. 3 (May 2018): 154–67. http://dx.doi.org/10.1027/1864-9335/a000338.
Hannikainen, Ivar. "Might-counterfactuals and the principle of conditional excluded middle." Disputatio 4, no. 30 (May 1, 2011): 127–49. http://dx.doi.org/10.2478/disp-2011-0003.
Rylková, Žaneta, Karel Stelmach, and Petr Vlček. "Overall Equipment Effectiveness within Counterfactual Impact Evaluation Concept." Scientific Annals of Economics and Business 64, s1 (December 1, 2017): 29–40. http://dx.doi.org/10.1515/saeb-2017-0037.
Schleich, Maximilian, Zixuan Geng, Yihong Zhang, and Dan Suciu. "GeCo." Proceedings of the VLDB Endowment 14, no. 9 (May 2021): 1681–93. http://dx.doi.org/10.14778/3461535.3461555.
Wauters, Benedict, and Derek Beach. "Process tracing and congruence analysis to support theory-based impact evaluation." Evaluation 24, no. 3 (July 2018): 284–305. http://dx.doi.org/10.1177/1356389018786081.
Clark-Moorman, Kyleigh, Jason Rydberg, and Edmund F. McGarrell. "Impact Evaluation of a Parolee-Based Focused Deterrence Program on Community-Level Violence." Criminal Justice Policy Review 30, no. 9 (November 27, 2018): 1408–30. http://dx.doi.org/10.1177/0887403418812999.
Castaño, Javier, Maria Blanco, and Pilar Martinez. "Reviewing Counterfactual Analyses to Assess Impacts of EU Rural Development Programmes: What Lessons Can Be Learned from the 2007–2013 Ex-Post Evaluations?" Sustainability 11, no. 4 (February 20, 2019): 1105. http://dx.doi.org/10.3390/su11041105.
Zhang, Qiyuan, and Judith Covey. "Past and Future Implications of Near-Misses and Their Emotional Consequences." Experimental Psychology 61, no. 2 (October 1, 2014): 118–26. http://dx.doi.org/10.1027/1618-3169/a000231.
Snider, Todd, and Adam Bjorndahl. "Informative counterfactuals." Semantics and Linguistic Theory 25 (October 29, 2015): 1. http://dx.doi.org/10.3765/salt.v25i0.3077.
Dissertations / Theses on the topic "Counterfactual evaluation":
Orri, Stefansson Hlynur. "Decision theory and counterfactual evaluation." Thesis, London School of Economics and Political Science (University of London), 2014. http://etheses.lse.ac.uk/984/.
Swaminathan, Adith. "Counterfactual Evaluation and Learning From Logged User Feedback." Thesis, Cornell University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10258968.
Interactive systems that interact with and learn from user behavior are ubiquitous today. Machine learning algorithms are core components of such systems. In this thesis, we will study how we can re-use logged user behavior data to evaluate interactive systems and train their machine learned components in a principled way. The core message of the thesis is • Using simple techniques from causal inference, we can improve popular machine learning algorithms so that they interact reliably. • These improvements are effective and scalable, and complement current algorithmic and modeling advances in machine learning. • They open further avenues for research in Counterfactual Evaluation and Learning to ensure machine learned components interact reliably with users and with each other. This thesis explores two fundamental tasks—evaluation and training of interactive systems. Solving evaluation and training tasks using logged data is an exercise in counterfactual reasoning. So we will first review concepts from causal inference for counterfactual reasoning, assignment mechanisms, statistical estimation and learning theory. The thesis then contains two parts.
In the first part, we will study scenarios where unknown assignment mechanisms underlie the logged data we collect. These scenarios often arise in learning-to-rank and learning-to-recommend applications. We will view these applications through the lens of causal inference and modularize the problem of building a good ranking engine or recommender system into two components—first, infer a plausible assignment mechanism and second, reliably learn to rank or recommend assuming this mechanism was active when collecting data.
The second part of the thesis focuses on scenarios where we collect logged data from past interventions. We will formalize these scenarios as batch learning from logged contextual bandit feedback. We will first develop better off-policy estimators for evaluating online user-centric metrics in information retrieval applications. In subsequent chapters, we will study the bias-variance trade-off when learning from logged interventions. This study will yield new learning principles, algorithms and insights into the design of statistical estimators for counterfactual learning.
The thesis outlines a few principles, tools, datasets and software that hopefully prove to be useful to you as you build your interactive learning system.
GUCCIARDI, Gianluca. "Three Essays in Policy Impact Evaluation." Doctoral thesis, Università degli studi di Ferrara, 2018. http://hdl.handle.net/11392/2487965.
1. Valutazione della decentralizzazione della sanità e del relativo impatto sulla mortalità infantile: evidenze dai Paesi dell’Unione Europea In questo lavoro, ci proponiamo di testare gli effetti della decentralizzazione del settore sanitario sulla mortalità infantile, come proxy della qualità della salute dei cittadini, adottando come unità di analisi 25 Paesi dell’Unione Europea tra il 1995 e il 2013. Inoltre, discutiamo l’endogeneità del modello dovuta a un possibile errore di misurazione della decentralizzazione del settore sanitario, quando è approssimato dalla sola decentralizzazione fiscale. I risultati suggeriscono che gli effetti positivi della decentralizzazione fiscale sulla salute dei cittadini si verificano in contesti istituzionali nei quali le autorità centrali hanno delegato poteri politici o manageriali e hanno reso le autorità locali direttamente responsabili in materia sanitaria. Al contrario, quando i requisiti istituzionali o manageriali sono assenti, la sola decentralizzazione fiscale non è una garanzia di miglioramento della salute dei cittadini. 2. La centralizzazione degli acquisti riduce la spesa pubblica? Evidenze dal Sistema Sanitario italiano L’introduzione delle Centrali Uniche di Committenza all’interno dei sistemi sanitari regionali in Italia durante la prima decade degli anni 2000 ha rappresentato una spinta verso la riduzione dei costi e la limitazione della spesa pubblica nel settore della sanità pubblica. Infatti, le Centrali di Committenza regionali che operano a beneficio delle ASL sono state introdotte per centralizzare gli acquisti di beni e servizi, con l'obiettivo di ridurre i prezzi e favorire la riduzione dei costi, soprattutto sfruttando le economie di scala e il maggiore potere contrattuale. In questo lavoro, esaminiamo questa ipotesi adottando un modello difference-in-difference per testare la relazione causale dell'introduzione di Centrali di Committenza regionali che operano all’interno dei sistemi di sanitari. I nostri risultati mostrano che la spesa totale pro capite si è ridotta di un intervallo tra il 3 e il 4%, in base alle specifiche del modello, nei contesti in cui le ASL si approvvigionano attraverso una Centrale di Committenza regionale. In particolare, questa riduzione è principalmente guidata dai servizi sanitari, mentre l'impatto sulle spese per l’acquisto di beni e di altri servizi non sanitari non è significativo. Inoltre, la riduzione della spesa ottenuta è ottenuta senza un significativo ridimensionamento dei servizi locali ai cittadini. 3. L’impatto del Budget Act 1974 sulla Spesa e sul Debito degli Stati Uniti d’America: un’analisi con controllo sintetico Il Budget Act 1974 segnò un punto di svolta nella storia fiscale degli Stati Uniti. Con questa legge, il Congresso ha fortemente affermato il proprio potere in materia di bilancio, diventando più indipendente dal Presidente nel suo sviluppo e fissando i livelli totali della spesa federale. I legislatori del tempo credevano che lo status quo secondo il quale il Congresso approvava il budget in modo frammentario limitasse la loro autorità di bilancio e avesse causato un aumento del deficit e della spesa. In questo lavoro, mostriamo in che modo la soluzione del Congresso – il Congressional Budget and Impoundment Control Act del 1974 (o più semplicemente il Budget Act) – sia riuscito a frenare la spesa e il debito. Più specificatamente, adottiamo un modello di controllo sintetico per interrogarci su cosa sarebbe successo senza l’introduzione del Budget Act 1974 e otteniamo che, dopo l’introduzione della legge, il rapporto tra debito pubblico e PIL e tra spesa pubblica e PIL sono entrambi aumentati, ma meno di quanto sarebbe accaduto senza la legge.
Faury, Louis. "Variance-sensitive confidence intervals for parametric and offline bandits." Electronic Thesis or Diss., Institut polytechnique de Paris, 2021. http://www.theses.fr/2021IPPAT046.
In this dissertation we present recent contributions to the problem of optimization under bandit feedback through the design of variance-sensitive confidence intervals. We tackle two distincts topics: (1) the regret minimization task in Generalized Linear Bandits (GLBs), a broad class of non-linear parametric bandits and (2) the problem of off-line policy optimization under bandit feedback. For (1) we study the effects of non-linearity in GLBs and challenge the current understanding that a high level of non-linearity is detrimental to the exploration-exploitation trade-off. We introduce improved algorithms as well as a novel analysis that prove that if correctly handled, the regret minimization task in GLBs is not necessarily harder than for their linear counterparts. It can even be easier for some important members of the GLB family such as the Logistic Bandit. Our approach leverages a new confidence set which captures the non-linearity of the reward signal through its variance, along with a local treatment of the non-linearity through a so-called self-concordance analysis. For (2) we leverage results from the distributionally robust optimization framework to construct asymptotic variance-sensitive confidence intervals for the counterfactual evaluation of policies. This allows to ensure conservatism (sought out by risk-averse agents) while searching off-line for promising policies. Our confidence intervals lead to new counterfactual objectives which, contrary to their predecessors, are more suited for practical deployment thanks to their convex and composite natures
Cowell, Paul David. "Three essays in the economics of higher education." Thesis, University of Stirling, 2017. http://hdl.handle.net/1893/28037.
Švarc, Michal. "Empirická analýza projektu: Stáže ve firmách." Master's thesis, Vysoká škola ekonomická v Praze, 2013. http://www.nusl.cz/ntk/nusl-192454.
Špaček, Martin. "Mikroekonomické dopady strukturálních fondů v neziskovém sektoru." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-162872.
Galope, Reynold V. "Public Financing of Risky Early-Stage Technology." Digital Archive @ GSU, 2012. http://digitalarchive.gsu.edu/pmap_diss/46.
Cruz, Daniela Filipa Fonseca. "Counterfactual impact evaluation of vocational education in Portugal." Master's thesis, 2015. http://hdl.handle.net/10071/11572.
The Reform of the Portuguese education system, which took place in 2004, led to the introduction and rapid expansion of vocational education in public high schools. This thesis aims to assess the impacts of vocational education on students’ academic and labor market performance using a Counterfactual Impact Evaluation (CIE) approach. The dataset used in the analysis includes data for the academic years of 2008/2009, 2009/2010 and 2010/2011. For both methodological and data availability reasons, we restrict our analysis to Portuguese students without special educational needs, aged between 15 and 18 years old, who are enrolled in public high schools with tutelage of the Ministry of Education and Science, and that were enrolled in general education in the previous year (basic education). For this group of students, we find that being enrolled in vocational education has positive impacts in school performance (transition, graduation, and dropout rates) and in labor market performance (employment rate, average salary and average worked months per year). We also find that vocational education students have lower chances of proceeding to higher education. These results are robust to variations in the estimation method.
A reforma do sistema de ensino Português, que ocorreu em 2004, originou a introdução e rápida expansão do ensino profissional nas escolas secundárias públicas. Esta tese tem como objetivo avaliar os impactos da educação profissional no desempenho escolar e laboral dos alunos, utilizando a lógica de Avaliação Contrafactual de Impactos (CIE). A base de dados inclui informação dos anos letivos de 2008/2009, 2009/2010 e 2010/2011. Devido a questões metodológicas e de disponibilidade de dados restringimos a nossa análise a estudantes portugueses, sem necessidades educativas especiais, com idades entre os 15 e 18, que estão matriculados em escolas públicas sob tutela do Ministério da Educação e Ciência, e que frequentaram educação geral no ano anterior (ensino básico). Para este grupo de alunos concluímos que o ensino profissional apresenta impactos positivos no desempenho escolar (taxas de transição, de conclusão e desistência) e no desempenho laboral (taxa de emprego, salário médio e média de meses trabalhos por ano). Os nossos resultados também mostram que os estudantes do ensino profissional têm menor probabilidade de prosseguir para o ensino superior. Estes resultados são robustos face a variações do método de estimação.
DI, STEFANO ROBERTA. "Alternative approaches for counterfactual evaluation in the presence of a few units." Doctoral thesis, 2021. http://hdl.handle.net/11573/1553095.
Books on the topic "Counterfactual evaluation":
Dvoulety, Ondrej. Reflection on the Usage of the Counterfactual Impact Evaluation Method to Quantify the Effects of Public Subsidies at Firm Level. 1 Oliver’s Yard, 55 City Road, London EC1Y 1SP United Kingdom: SAGE Publications Inc., 2023. http://dx.doi.org/10.4135/9781529628913.
Stalnaker, Robert C. Knowledge and Conditionals. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198810346.001.0001.
Bjorkman, Bronwyn M., and Claire Halpert. In an imperfect world: Deriving the typology of counterfactual marking. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780198718208.003.0009.
Solstad, Torgrim, and Oliver Bott. Causality and Causal Reasoning in Natural Language. Edited by Michael R. Waldmann. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199399550.013.32.
Yen, Wendy. Debiasing the hindsight bias: A review. 2005.
Crespo, Inés, Hadil Karawani, and Frank Veltman. Expressing Expectations. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198739548.003.0009.
Roberts, John T. Laws of Nature. Edited by Paul Humphreys. Oxford University Press, 2015. http://dx.doi.org/10.1093/oxfordhb/9780199368815.013.20.
Hunt, Luke William. Entrapment, Prerogative Power, and the Rule of Law. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190904999.003.0006.
Pettit, Philip. The Birth of Ethics. Edited by Kinch Hoekstra. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190904913.001.0001.
Book chapters on the topic "Counterfactual evaluation":
Balke, Alexander, and Judea Pearl. "Probabilistic Evaluation of Counterfactual Queries." In Probabilistic and Causal Inference, 237–54. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3501714.3501733.
Pereira, Luís Moniz, Francisco C. Santos, and António Barata Lopes. "AI Modelling of Counterfactual Thinking for Judicial Reasoning and Governance of Law." In Multidisciplinary Perspectives on Artificial Intelligence and the Law, 263–79. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-41264-6_14.
Martins, Pedro S. "Public Policy, Big Data, and Counterfactual Evaluation: An Illustration from an Employment Activation Programme." In Data-Driven Policy Impact Evaluation, 149–63. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78461-8_10.
Guo, Ruocheng, Jundong Li, and Huan Liu. "Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data." In Proceedings of the 2020 SIAM International Conference on Data Mining, 271–79. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2020. http://dx.doi.org/10.1137/1.9781611976236.31.
Zhang, Xuezhong, Libin Dai, Qingming Peng, Ruizhi Tang, and Xinwei Li. "A Survey of Counterfactual Explanations: Definition, Evaluation, Algorithms, and Applications." In Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery, 905–12. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-20738-9_99.
d’Hombres, Beatrice, and Giulia Santangelo. "Use of Administrative Data for Counterfactual Impact Evaluation of Active Labour Market Policies in Europe: Country and Time Comparisons." In Data-Driven Policy Impact Evaluation, 271–87. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78461-8_17.
Jones, Kelly W., Allen Blackman, and Rodrigo Arriagada. "Methods to Advance Understanding of Tenure Security: Impact Evaluation for Rigorous Evidence on Tenure Interventions." In Land Tenure Security and Sustainable Development, 291–312. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-81881-4_14.
Battistin, Erich, and Marco Bertoni. "Counterfactuals with Experimental and Quasi-Experimental Variation." In Texts in Quantitative Political Analysis, 37–70. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-12982-7_3.
Andrade, Yan, Nícollas Silva, Adriano Pereira, Elisa Tuler, Cleverson Vieira, Marcelo Guimarães, Diego Dias, and Leonardo Rocha. "Integrating Counterfactual Evaluations into Traditional Interactive Recommendation Frameworks." In Computational Science and Its Applications – ICCSA 2023, 635–47. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-36805-9_41.
Höllig, Jacqueline, Aniek F. Markus, Jef de Slegte, and Prachi Bagave. "Semantic Meaningfulness: Evaluating Counterfactual Approaches for Real-World Plausibility and Feasibility." In Communications in Computer and Information Science, 636–59. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-44067-0_32.
Conference papers on the topic "Counterfactual evaluation":
Yang, Xiaoyu, Stephen Obadinma, Huasha Zhao, Qiong Zhang, Stan Matwin, and Xiaodan Zhu. "SemEval-2020 Task 5: Counterfactual Recognition." In Proceedings of the Fourteenth Workshop on Semantic Evaluation. Stroudsburg, PA, USA: International Committee for Computational Linguistics, 2020. http://dx.doi.org/10.18653/v1/2020.semeval-1.40.
Prado-Romero, Mario Alfonso, and Giovanni Stilo. "GRETEL: Graph Counterfactual Explanation Evaluation Framework." In CIKM '22: The 31st ACM International Conference on Information and Knowledge Management. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3511808.3557608.
Coston, Amanda, Alan Mishler, Edward H. Kennedy, and Alexandra Chouldechova. "Counterfactual risk assessments, evaluation, and fairness." In FAT* '20: Conference on Fairness, Accountability, and Transparency. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3351095.3372851.
Keane, Mark T., Eoin M. Kenny, Eoin Delaney, and Barry Smyth. "If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/609.
Saito, Yuta, and Thorsten Joachims. "Counterfactual Evaluation and Learning for Interactive Systems." In KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3534678.3542601.
Yuan, Yining, Kevin McAreavey, Shujun Li, and Weiru Liu. "Multi-Granular Evaluation of Diverse Counterfactual Explanations." In 16th International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and Technology Publications, 2024. http://dx.doi.org/10.5220/0012349900003636.
Felicioni, Nicolò. "Enhancing Counterfactual Evaluation and Learning for Recommendation Systems." In RecSys '22: Sixteenth ACM Conference on Recommender Systems. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3523227.3547429.
McInerney, James, Brian Brost, Praveen Chandar, Rishabh Mehrotra, and Benjamin Carterette. "Counterfactual Evaluation of Slate Recommendations with Sequential Reward Interactions." In KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3394486.3403229.
Xie, Zhongbin, Vid Kocijan, Thomas Lukasiewicz, and Oana-Maria Camburu. "Counter-GAP: Counterfactual Bias Evaluation through Gendered Ambiguous Pronouns." In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics. Stroudsburg, PA, USA: Association for Computational Linguistics, 2023. http://dx.doi.org/10.18653/v1/2023.eacl-main.272.
Huang, Po-Sen, Huan Zhang, Ray Jiang, Robert Stanforth, Johannes Welbl, Jack Rae, Vishal Maini, Dani Yogatama, and Pushmeet Kohli. "Reducing Sentiment Bias in Language Models via Counterfactual Evaluation." In Findings of the Association for Computational Linguistics: EMNLP 2020. Stroudsburg, PA, USA: Association for Computational Linguistics, 2020. http://dx.doi.org/10.18653/v1/2020.findings-emnlp.7.
Reports on the topic "Counterfactual evaluation":
Pais Mamede, Ricardo, Teresa Fernandes, and Ana Alexandrino Silva. Counterfactual impact evaluation of EU funded enterprise support in Portugal. DINÂMIA'CET-IUL, 2015. http://dx.doi.org/10.15847/dinamiacet-iul.wp.2015.05.
Cumberbatch, Janice, Fabian Hinds, Leonardo Corral, Cassandra Rogers, Maja Schling, Naijun Zhou, and Michele H. Lemay. The Impact of Coastal Infrastructure Improvements on Economic Growth: Evidence from Barbados. Inter-American Development Bank, October 2016. http://dx.doi.org/10.18235/0011763.
Bukstein, Daniel, and Néstor Gandelman. Glass Ceiling in Research: Evidence from a National Program in Uruguay. Inter-American Development Bank, April 2017. http://dx.doi.org/10.18235/0011792.
Bonhomme, Stéphane, and Angela Denis. Estimating individual responses when tomorrow matters. Madrid: Banco de España, February 2024. http://dx.doi.org/10.53479/36092.
Peña-Torres, Julio, Kailin Kroetz, James N. Sanchirico, and David Corderi. Evaluation of the Chilean Jack Mackerel ITQ System. Inter-American Development Bank, March 2016. http://dx.doi.org/10.18235/0011723.
Impact Evaluation of the Business Development Program for the Software Industry in Uruguay. Inter-American Development Bank, September 2010. http://dx.doi.org/10.18235/0008978.