Relevant bibliographies by topics / Conformal inference

Academic literature on the topic 'Conformal inference'

Author: Grafiati
Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Conformal inference"

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Lei, Lihua, and Emmanuel J. Candès. "Conformal inference of counterfactuals and individual treatment effects." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 83, no. 5 (October 7, 2021): 911–38. http://dx.doi.org/10.1111/rssb.12445.

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Chen, Wenyu, Kelli-Jean Chun, and Rina Foygel Barber. "Discretized conformal prediction for efficient distribution-free inference." Stat 7, no. 1 (2018): e173. http://dx.doi.org/10.1002/sta4.173.

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Heckman, Jonathan J. "Statistical inference and string theory." International Journal of Modern Physics A 30, no. 26 (September 18, 2015): 1550160. http://dx.doi.org/10.1142/s0217751x15501602.

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In this paper, we expose some surprising connections between string theory and statistical inference. We consider a large collective of agents sweeping out a family of nearby statistical models for an [Formula: see text]-dimensional manifold of statistical fitting parameters. When the agents making nearby inferences align along a [Formula: see text]-dimensional grid, we find that the pooled probability that the collective reaches a correct inference is the partition function of a nonlinear sigma model in [Formula: see text] dimensions. Stability under perturbations to the original inference scheme requires the agents of the collective to distribute along two dimensions. Conformal invariance of the sigma model corresponds to the condition of a stable inference scheme, directly leading to the Einstein field equations for classical gravity. By summing over all possible arrangements of the agents in the collective, we reach a string theory. We also use this perspective to quantify how much an observer can hope to learn about the internal geometry of a superstring compactification. Finally, we present some brief speculative remarks on applications to the AdS/CFT correspondence and Lorentzian signature space–times.
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Efron, Bradley. "Resampling Plans and the Estimation of Prediction Error." Stats 4, no. 4 (December 20, 2021): 1091–115. http://dx.doi.org/10.3390/stats4040063.

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This article was prepared for the Special Issue on Resampling methods for statistical inference of the 2020s. Modern algorithms such as random forests and deep learning are automatic machines for producing prediction rules from training data. Resampling plans have been the key technology for evaluating a rule’s prediction accuracy. After a careful description of the measurement of prediction error the article discusses the advantages and disadvantages of the principal methods: cross-validation, the nonparametric bootstrap, covariance penalties (Mallows’ Cp and the Akaike Information Criterion), and conformal inference. The emphasis is on a broad overview of a large subject, featuring examples, simulations, and a minimum of technical detail.
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Lei, J. "Fast exact conformalization of the lasso using piecewise linear homotopy." Biometrika 106, no. 4 (September 30, 2019): 749–64. http://dx.doi.org/10.1093/biomet/asz046.

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Summary Conformal prediction is a general method that converts almost any point predictor to a prediction set. The resulting set retains the good statistical properties of the original estimator under standard assumptions, and guarantees valid average coverage even when the model is mis-specified. A main challenge in applying conformal prediction in modern applications is efficient computation, as it generally requires an exhaustive search over the entire output space. In this paper we develop an exact and computationally efficient conformalization of the lasso and elastic net. The method makes use of a novel piecewise linear homotopy of the lasso solution under perturbation of a single input sample point. As a by-product, we provide a simpler and better-justified online lasso algorithm, which may be of independent interest. Our derivation also reveals an interesting accuracy-stability trade-off in conformal inference, which is analogous to the bias-variance trade-off in traditional parameter estimation. The practical performance of the new algorithm is demonstrated in both synthetic and real data examples.
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Hormoz, Sahand, Nicolas Desprat, and Boris I. Shraiman. "Inferring epigenetic dynamics from kin correlations." Proceedings of the National Academy of Sciences 112, no. 18 (April 22, 2015): E2281—E2289. http://dx.doi.org/10.1073/pnas.1504407112.

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Populations of isogenic embryonic stem cells or clonal bacteria often exhibit extensive phenotypic heterogeneity that arises from intrinsic stochastic dynamics of cells. The phenotypic state of a cell can be transmitted epigenetically in cell division, leading to correlations in the states of cells related by descent. The extent of these correlations is determined by the rates of transitions between the phenotypic states. Therefore, a snapshot of the phenotypes of a collection of cells with known genealogical structure contains information on phenotypic dynamics. Here, we use a model of phenotypic dynamics on a genealogical tree to define an inference method that allows extraction of an approximate probabilistic description of the dynamics from observed phenotype correlations as a function of the degree of kinship. The approach is tested and validated on the example of Pyoverdine dynamics in Pseudomonas aeruginosa colonies. Interestingly, we find that correlations among pairs and triples of distant relatives have a simple but nontrivial structure indicating that observed phenotypic dynamics on the genealogical tree is approximately conformal—a symmetry characteristic of critical behavior in physical systems. The proposed inference method is sufficiently general to be applied in any system where lineage information is available.
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Vlaeminck, H., J. Vennekens, M. Denecker, and M. Bruynooghe. "An approximative inference method for solving ∃∀SO satisfiability problems." Journal of Artificial Intelligence Research 45 (September 25, 2012): 79–124. http://dx.doi.org/10.1613/jair.3658.

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This paper considers the fragment ∃∀SO of second-order logic. Many interesting problems, such as conformant planning, can be naturally expressed as finite domain satisfiability problems of this logic. Such satisfiability problems are computationally hard (ΣP2) and many of these problems are often solved approximately. In this paper, we develop a general approximative method, i.e., a sound but incomplete method, for solving ∃∀SO satisfiability problems. We use a syntactic representation of a constraint propagation method for first-order logic to transform such an ∃∀SO satisfiability problem to an ∃SO(ID) satisfiability problem (second-order logic, extended with inductive definitions). The finite domain satisfiability problem for the latter language is in NP and can be handled by several existing solvers. Inductive definitions are a powerful knowledge representation tool, and this moti- vates us to also approximate ∃∀SO(ID) problems. In order to do this, we first show how to perform propagation on such inductive definitions. Next, we use this to approximate ∃∀SO(ID) satisfiability problems. All this provides a general theoretical framework for a number of approximative methods in the literature. Moreover, we also show how we can use this framework for solving practical useful problems, such as conformant planning, in an effective way.
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Spencer, Sharon L., and Jill Fitzgerald. "Validity and Structure, Coherence, and Quality Measures in Writing." Journal of Reading Behavior 25, no. 2 (June 1993): 209–31. http://dx.doi.org/10.1080/10862969309547811.

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The purpose of the present study was to investigate convergent and divergent validity of inferences from selected measures of struture, coherence, and quality for compositions. Thirty sixth-graders wrote two stories each. Each story was scored six times, for each of three constructs (structure, coherence, and quality), using two ways of measuring (reader- and text-based). Patterns in correlation matrices were examined for the extent to which they conformed to expectations which would support convergent and divergent validity. The major conclusions of the study were: (a) Overall, the findings strongly supported validity of inferences from the structure measures, called into serious question the validity of inferences from the coherence measures, and weakly supported it for inferences from the quality measures; (b) some evidence was provided for the distinctiveness of the three constructs, structure, coherence, and quality; and (c) some method/halo bias emerged in the reader-based method of assessment.
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Van den Broeck, Guy, and Jesse Davis. "Conditioning in First-Order Knowledge Compilation and Lifted Probabilistic Inference." Proceedings of the AAAI Conference on Artificial Intelligence 26, no. 1 (September 20, 2021): 1961–67. http://dx.doi.org/10.1609/aaai.v26i1.8404.

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Knowledge compilation is a powerful technique for compactly representing and efficiently reasoning about logical knowledge bases. It has been successfully applied to numerous problems in artificial intelligence, such as probabilistic inference and conformant planning. Conditioning, which updates a knowledge base with observed truth values for some propositions, is one of the fundamental operations employed for reasoning. In the propositional setting, conditioning can be efficiently applied in all cases. Recently, people have explored compilation for first-order knowledge bases. The majority of this work has centered around using first-order d-DNNF circuits as the target compilation language. However, conditioning has not been studied in this setting. This paper explores how to condition a first-order d-DNNF circuit. We show that it is possible to efficiently condition these circuits on unary relations. However, we prove that conditioning on higher arity relations is #P-hard. We study the implications of these findings on the application of performing lifted inference for first-order probabilistic models.This leads to a better understanding of which types of queries lifted inference can address.
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Kilián, Imre. "Contralog: a Prolog conform forward-chaining environment and its application for dynamic programming and natural language parsing." Acta Universitatis Sapientiae, Informatica 8, no. 1 (June 1, 2016): 41–62. http://dx.doi.org/10.1515/ausi-2016-0003.

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Abstract The backward-chaining inference strategy of Prolog is inefficient for a number of problems. The article proposes Contralog: a Prolog-conform, forward-chaining language and an inference engine that is implemented as a preprocessor-compiler to Prolog. The target model is Prolog, which ensures mutual switching from Contralog to Prolog and back. The Contralog compiler is implemented using Prolog's de facto standardized macro expansion capability. The article goes into details regarding the target model. We introduce first a simple application example for Contralog. Then the next section shows how a recursive definition of some problems is executed by their Contralog definition automatically in a dynamic programming way. Two examples, the well-known matrix chain multiplication problem and the Warshall algorithm are shown here. After this, the inferential target model of Prolog/Contralog programs is introduced, and the possibility for implementing the ReALIS natural language parsing technology is described relying heavily on Contralog's forward chaining inference engine. Finally the article also discusses some practical questions of Contralog program development.
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Books on the topic "Conformal inference"

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Gaviria Peña, Carlos, and Carlos Alberto Márquez Fernández. Estadística descriptiva y probabilidad. Universidad San Buenaventura, 2020. http://dx.doi.org/10.21500/9789588474779.

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"Si se considera un conjunto de objetos de interés y de dichos objetos se considera, por ejemplo, un escorzo medible, se espera que en todos ellos la medida asociada sea diferente objeto a objeto. Si bien la población de estudio es el conjunto formado por todos los objetos de interés, se puede asumir de manera teórica que la población está conformada solo por el escorzo. La estadística es la ciencia que se encarga de modelar las poblaciones así pensadas, es decir, la estadística explica la manera en la cual se comporta un escorzo particular sobre un conjunto de objetos de interés. Por otra parte, cuando de manera empírica se toma un conjunto particular de objetos de la población teórica y se estudia en dicho conjunto el escorzo de interés, se obtiene un conjunto de medidas o un conjunto de datos, las cuales pueden explicar la población teórica. De esta manera, la estadística se ocupa de explicar los objetos en términos de sus escorzos mediante un subconjunto de una población de interés, es decir, la estadística se encarga de relacionar el mundo teórico y práctico mediante modelos que permiten explicar algunos escorzos. Con el estudio de este libro se logra adquirir las bases teóricas necesarias para comprender conceptos de estadística que permiten establecer relaciones entre el mundo teórico y práctico. Además, cuando se está leyendo este texto se aprende a leer y escribir problemas de naturaleza estadística. De esta manera, además de construir las bases teóricas de la inferencia estadística, este texto permite fortalecer otro tipo de competencias tales como la lectura y la escritura, así como el apropiamiento de procedimientos que son útiles en la práctica."
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Book chapters on the topic "Conformal inference"

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LAGNADO, DAVID. "Thinking about Evidence1." In Evidence, Inference and Enquiry. British Academy, 2011. http://dx.doi.org/10.5871/bacad/9780197264843.003.0007.

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This chapter argues that people reason about legal evidence using small-scale qualitative networks. These cognitive networks are typically qualitative and incomplete, and based on people's causal beliefs about the specifics of the case as well as the workings of the physical and social world in general. A key feature of these networks is their ability to represent qualitative relations between hypotheses and evidence, allowing reasoners to capture the concepts of dependency and relevance critical in legal contexts. In support of this claim, the chapter introduces some novel empirical and formal work on alibi evidence, showing that people's reasoning conforms to the dictates of a qualitative Bayesian model. However, people's inferences do not always conform to Bayesian prescripts. Empirical studies are also discussed in which people over-extend the discredit of one item of evidence to other unrelated items. This bias is explained in terms of the propensity to group positive and negative evidence separately and the use of coherence-based inference mechanisms. It is argued that these cognitive processes are a natural response to deal with the complexity of legal evidence.
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Altwicker, Tilmann, and Alexandra Ellen Hansen. "Presumptions as Secondary Rules in the Judicial Interpretation of International Human Rights." In Secondary Rules of Primary Importance in International Law, 167—C9.P34. Oxford University PressOxford, 2022. http://dx.doi.org/10.1093/oso/9780192869012.003.0009.

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Abstract In legal contexts, presumptions constitute secondary rules designed to manage specific situations of uncertainty arising in adjudication. Presumptions guide the interpretation of legal rules in cases of factual, practical, or legal uncertainty. In human rights proceedings, in particular, they are used to overcome situations of information asymmetry, to reduce the complexity of the legal argument or to avoid a (potentially destructive) normative conflict with other actors. Their modus operandi is inference: presumptions provide a repository of knowledge from which new knowledge can be inferred, that is then given legal significance in the judicial proceedings. The use of presumptions in international human rights adjudication can be considered legitimate if the general conditions of inference conform to the demands of procedural justice. Furthermore, the use of presumptions may be justified under the ethical principle of “the lesser evil.”
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Okrent, Arika, and Sean O’Neill. "Blame Ourselves." In Highly Irregular, 181–242. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780197539408.003.0006.

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This chapter evaluates how, over the centuries, as English became increasingly used in official institutions, written, taught, codified, and standardized, not only did the language change, but our idea of what the language is changed. All languages have rules—even unwritten, uncodified vernaculars. Linguistic rules are patterns, conventions for making utterances, that conform to certain general (though much debated) principles of human language ability. Languages that are written, codified, and standardized also have explicitly endorsed or prescribed rules. Rules that are taught and enforced to a certain degree, but not necessarily followed. Correctness in language can be defined in relation to rules that are either tacit conventions or explicitly formalized prescriptions. Over time, because language is something people do, both kinds of rules will change. Language also interacts with formal logic, the axioms and rules of inference, but it plays by its own rules. Ultimately, when it comes to language, we are creatures of habit and creatures of creativity.
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Spiegel, Thais. "Influences of Personal Experience in Decision-Making." In Advances in Human Resources Management and Organizational Development, 76–97. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-2480-9.ch005.

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Among the aspects that conform the human cognition and therefore, the behavior observed in the choices, there is the individual experience. Researches point the experience performing either positive as negative roles in the process of decision-making. Motivated by the question, What is the role of the experience in the decision-making? this text sought to check in which way the state of art and the technique of Cognitive Sciences could contribute with the better understanding of the cognitive processing in the context of decision-making. It was adopted as a start the roles' structured exposition of the cognition elements during the decision process, as Spiegel's (2014) proposal. It was investigated through a systematic revision of the literature, the impacts of the decision-maker's experience in the manifestation of attention, categorization, memory and emotion. As a result, 17 inferences that present which is the role of the experience in the decision-making, and deeply, which are the implications of the experience in the cognitive process of the decision-maker, are presented.
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Pearson, Trais. "Spirits in a Material World." In Sovereign Necropolis, 158–64. Cornell University Press, 2020. http://dx.doi.org/10.7591/cornell/9781501740152.003.0009.

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This epilogue considers acquittal through the absolution of the apparition—where supernatural beings help to dictate the actions and fates of the living. It is only in the latter world that it makes sense for one to undertake kan-tham khwan, the action of making amends for a lost life through a compensatory payment made to the spirit of the deceased. The chapter illustrates that, insofar as kan-tham khwan masquerades as a payment made to placate the spirit of the deceased, it conforms to the logic and spirit of traditional forms of remediation for lost life. It is a testament to the survival of customary modes of action in an age of ostensibly normalized and homogeneous forms of law and order. At the same time, however, it is a form of action that imparts indemnification or legal protection for the injurer or culpable party. In this respect, kan-tham khwan participates in the long-standing logic of noblesse oblige, whereby social superiors are entitled to make amends for potentially wrongful actions that cost the lives of their subordinates. Within this backdrop, the chapter draws some inferences on the state of social and economic inequality in contemporary Thailand.
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Nieves Álvarez, Maybeth Josefina, Yamarú del Valle Chirinos Araque, Roberto Godínez López, and Dorkys Coromoto Rojas Nieves. "Gnoseologìa de la flexibilización laboral interna." In Tendencias en la investigación universitaria. Una visión desde Latinoamérica. Volumen XVI, 249–64. Fondo Editorial Universitario Servando Garcés de la Universidad Politécnica Territorial de Falcón Alonso Gamero / Alianza de Investigadores Internacionales S.A.S., 2021. http://dx.doi.org/10.47212/tendencias2021vol.xvi.19.

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Hoy en día el mundo del trabajo ha venido presentando cambios transcendentales, constituidos por procesos de adaptación y ajustes en el ámbito laboral lo que ha generado la adopción de nuevas formas de organización del trabajo, así como también nuevas formas para gestionar el talento humano, lo que ha favorecido el surgimiento y el crecimiento del proceso flexibilizador en estos aspectos. Es por ello que la presente investigación tiene como objetivo analizar la flexibilización laboral interna, desde sus dimensione e indicadores, desarrollada bajo el tipo de investigación documental, de alcance descriptivo, utilizando fuentes secundarias para la recolección de la información. Haciendo inferencia sobre los postulados de autores como Ganga (2014), Arancibia (2011), Rodríguez (2009); González (2011). Una vez realizado un análisis comparativo en las definiciones planteadas por los autores mencionados y a través de una sinopsis se puede concluir que existen dos tipos de dimensiones que conforman la flexibilización laboral interna, una de tipo cuantitativo numérico, referida específicamente a la disposición variable de la empresa en cuanto a jornadas laborales y niveles de producción y la otra de tipo cualitativo funcional, orientada a la organización del trabajo y de los procesos, cada una compuesta por indicadores que la definen ampliamente.
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Conference papers on the topic "Conformal inference"

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Qin, Xin, Yuan Xian, Aditya Zutshi, Chuchu Fan, and Jyotirmoy V. Deshmukh. "Statistical Verification of Cyber-Physical Systems using Surrogate Models and Conformal Inference." In 2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS). IEEE, 2022. http://dx.doi.org/10.1109/iccps54341.2022.00017.

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Vásquez, Claudia. "Statistical and Probabilistic Education in Primary Education in Chile: Where Do We Want to Go?" In Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. International Association for Statistical Education, 2022. http://dx.doi.org/10.52041/iase.icots11.t2g2.

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This study analyzes how the Chilean curriculum of primary education (6-14 years) approaches the teaching of statistics and probability, in terms of the sense proposed, as well as in the fundamental statistical ideas promoted. For this purpose, a theoretical and qualitative analysis was performed, focusing on content analysis. The results indicate that the ideas of data, data representation, distribution, variation, probability, sampling and inference, and association and correlation stand out from greater to lesser emphasis. It should be noted that these ideas are approached with different levels of depth according to the ages of the students and as progress is made in the different courses that make up the Primary Education. Este estudio analiza cómo el currículo chileno de Educación Primaria (6-14 años) aborda la enseñanza de la estadística y la probabilidad, en términos del sentido que se propone, así como en las ideas estadísticas fundamentales que se promueven. Para ello, se realizó un análisis teórico y cualitativo, centrado en el análisis de contenido. Los resultados nos indican que destacan de mayor a menor énfasis las ideas de datos, representación de datos, distribución, variación, probabilidad, muestreo e inferencia y asociación y correlación. Cabe señalar, que estas ideas se abordan con distintos niveles de profundidad acorde a las edades de los estudiantes y a medida que se avanza en los distintos cursos que conforman la Educación Primaria.
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Quan, Zongfeng, Nick J. C. Wang, Wei Chu, Tao Wei, Shaojun Wang, and Jing Xiao. "FFM: A Frame Filtering Mechanism To Accelerate Inference Speed For Conformer In Speech Recognition." In Interspeech 2022. ISCA: ISCA, 2022. http://dx.doi.org/10.21437/interspeech.2022-656.

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Reports on the topic "Conformal inference"

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Zhu, Yu, Kaspar Wüthrich, and Victor Chernozhukov. An exact and robust conformal inference method for counterfactual and synthetic controls. The IFS, December 2017. http://dx.doi.org/10.1920/wp.cem.2017.6217.

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Chernozhukov, Victor, Kaspar Wüthrich, and Yinchu Zhu. Exact and robust conformal inference methods for predictive machine learning with dependent data. The IFS, March 2018. http://dx.doi.org/10.1920/wp.cem.2018.1618.

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