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This paper deals with the factor modeling for high-dimensional time series based on a dimension-reduction viewpoint. Under stationary settings, the inference is simple in the sense that both the number of factors and the factor loadings are…

Statistics Theory · Mathematics 2012-06-05 Clifford Lam , Qiwei Yao

Non-deductive reasoning systems are often {\em representation dependent}: representing the same situation in two different ways may cause such a system to return two different answers. Some have viewed this as a significant problem. For…

Artificial Intelligence · Computer Science 2007-05-23 Joseph Y. Halpern , Daphne Koller

We examine normal form solutions of decision trees under typical choice functions induced by lower previsions. For large trees, finding such solutions is hard as very many strategies must be considered. In an earlier paper, we extended…

Statistics Theory · Mathematics 2018-08-10 Nathan Huntley , Matthias C. M. Troffaes

Consider the problem of imputing missing values in a dataset. One the one hand, conventional approaches using iterative imputation benefit from the simplicity and customizability of learning conditional distributions directly, but suffer…

Machine Learning · Statistics 2022-06-17 Daniel Jarrett , Bogdan Cebere , Tennison Liu , Alicia Curth , Mihaela van der Schaar

We show that strict deterministic propositional dynamic logic with intersection is highly undecidable, solving a problem in the Stanford Encyclopedia of Philosophy. In fact we show something quite a bit stronger. We introduce the…

Logic in Computer Science · Computer Science 2023-11-08 Robert Goldblatt , Marcel Jackson

An extension of the WHILE-language is developed for programming game-theoretic mechanisms involving multiple agents. Examples of such mechanisms include auctions, voting procedures, and negotiation protocols. A structured operational…

Logic in Computer Science · Computer Science 2007-05-23 Marc Pauly

Invariants are a set of properties over program attributes that are expected to be true during the execution of a program. Since developing those invariants manually can be costly and challenging, there are a myriad of approaches that…

Robotics · Computer Science 2020-12-15 Meriel Stein , Sebastian Elbaum , Lu Feng , Shili Sheng

In probabilistic programming, the inference problem asks to determine a program's posterior distribution conditioned on its "observe" instructions. Inference is challenging, especially when exact rather than approximate results are…

Formal Languages and Automata Theory · Computer Science 2025-11-26 Dominik Geißler , Tobias Winkler

Approximations during program analysis are a necessary evil, as they ensure essential properties, such as soundness and termination of the analysis, but they also imply not always producing useful results. Automatic techniques have been…

Programming Languages · Computer Science 2018-12-18 Isabel Garcia-Contreras , Jose F. Morales , Manuel V. Hermenegildo

Word embedding, specially with its recent developments, promises a quantification of the similarity between terms. However, it is not clear to which extent this similarity value can be genuinely meaningful and useful for subsequent tasks.…

Computation and Language · Computer Science 2018-04-05 Navid Rekabsaz , Mihai Lupu , Allan Hanbury

Parallel machine scheduling has been extensively studied in the past decades, with applications ranging from production planning to job processing in large computing clusters. In this work we study some of these fundamental optimization…

Data Structures and Algorithms · Computer Science 2015-09-08 Yael Mordechai

Algorithms are commonly used to predict outcomes under a particular decision or intervention, such as predicting whether an offender will succeed on parole if placed under minimal supervision. Generally, to learn such counterfactual…

Machine Learning · Statistics 2021-04-19 Amanda Coston , Edward H. Kennedy , Alexandra Chouldechova

Inferential models have been proposed for valid and efficient prior-free probabilistic inference. As it gradually gained popularity, this theory is subject to further developments for practically challenging problems. This paper considers…

Statistics Theory · Mathematics 2024-04-15 Jiasen Yang , Xiao Wang , Chuanhai Liu

Process equivalences are formal methods that relate programs and system which, informally, behave in the same way. Since there is no unique notion of what it means for two dynamic systems to display the same behaviour there are a multitude…

Logic in Computer Science · Computer Science 2012-10-10 Martin Lange , Etienne Lozes , Manuel Vargas Guzmán

Software verification has emerged as a key concern for ensuring the continued progress of information technology. Full verification generally requires, as a crucial step, equipping each loop with a "loop invariant". Beyond their role in…

Software Engineering · Computer Science 2014-01-14 Carlo A. Furia , Bertrand Meyer , Sergey Velder

Data integration methods aim to extract low-dimensional embeddings from high-dimensional outcomes to remove unwanted variations, such as batch effects and unmeasured covariates, across heterogeneous datasets. However, multiple hypothesis…

Methodology · Statistics 2025-12-15 Jin-Hong Du , Kathryn Roeder , Larry Wasserman

We study causal inference in a multi-environment setting, in which the functional relations for producing the variables from their direct causes remain the same across environments, while the distribution of exogenous noises may vary. We…

Machine Learning · Computer Science 2017-05-29 AmirEmad Ghassami , Saber Salehkaleybar , Negar Kiyavash , Kun Zhang

We show that equivalence of deterministic top-down tree-to-string transducers is decidable, thus solving a long standing open problem in formal language theory. We also present efficient algorithms for subclasses: polynomial time for total…

Formal Languages and Automata Theory · Computer Science 2017-01-30 Helmut Seidl , Sebastian Maneth , Gregor Kemper

We consider identification, inference and validation of linear panel data models when both factors and factor loadings are accounted for by a nonparametric function. This general specification encompasses rather popular models such as the…

Econometrics · Economics 2025-06-13 Juan M. Rodriguez-Poo , Alexandra Soberon , Stefan Sperlich

Precondition inference is a non-trivial task with several applications in program analysis and verification. We present a novel iterative method for automatically deriving sufficient preconditions for safety and unsafety of programs which…

Logic in Computer Science · Computer Science 2018-11-19 Bishoksan Kafle , Graeme Gange , Peter Schachte , Harald Sondergaard , Peter J. Stuckey
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