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Statistical latent class models are widely used in social and psychological researches, yet it is often difficult to establish the identifiability of the model parameters. In this paper we consider the identifiability issue of a family of…

Methodology · Statistics 2016-03-15 Gongjun Xu

Understanding the behavior of learned classifiers is an important task, and various black-box explanations, logical reasoning approaches, and model-specific methods have been proposed. In this paper, we introduce probabilistic sufficient…

Machine Learning · Computer Science 2021-05-24 Eric Wang , Pasha Khosravi , Guy Van den Broeck

The bifactor model and its extensions are multidimensional latent variable models, under which each item measures up to one subdimension on top of the primary dimension(s). Despite their wide applications to educational and psychological…

Statistics Theory · Mathematics 2020-12-23 Guanhua Fang , Xin Xu , Jinxin Guo , Zhiliang Ying , Susu Zhang

Metric Temporal Logic $\mathsf{MTL}[\until_I,\since_I]$ is one of the most studied real time logics. It exhibits considerable diversity in expressiveness and decidability properties based on the permitted set of modalities and the nature of…

Logic in Computer Science · Computer Science 2014-04-29 Khushraj Madnani , Shankara Narayanan Krishna , Paritosh Pandya

In this paper, using definability of types over indiscernible sequences as a template, we study a property of formulas and theories called "uniform definability of types over finite sets" (UDTFS). We explore UDTFS and show how it relates to…

Logic · Mathematics 2010-05-27 Vincent Guingona

We show that many models of choice can be alternatively represented as special cases of choice with limited attention (Masatlioglu, Nakajima, and Ozbay, 2012), singling out the properties of the unobserved attention filters that explain the…

Theoretical Economics · Economics 2025-07-31 Davide Carpentiere , Angelo Petralia

Adequacy for estimation between an inferential method and a model can be de{\ldots}ned through two main requirements: {\ldots}rstly the inferential tool should de{\ldots}ne a well posed problem when applied to the model; secondly the…

Statistics Theory · Mathematics 2025-07-30 Michel Broniatowski , Justin Moutsouka

We argue that Godel's completeness theorem is equivalent to completability of consistent theories, and Godel's incompleteness theorem is equivalent to the fact that this completion is not constructive, in the sense that there are some…

Logic · Mathematics 2019-07-02 Saeed Salehi

It has been argued that reduction procedures are closely connected to the question about identity of proofs and that accepting certain reductions would lead to a trivialization of identity of proofs in the sense that every derivation of the…

Logic in Computer Science · Computer Science 2023-10-25 Sara Ayhan

We prove that arithmetic is interpretable in any indecomposable polynomial ring (in any set of variables), and in addition we provide an alternative uniform proof of undecidability for all members in this class of rings.

Logic · Mathematics 2023-09-28 Marco Barone , Nicolás Caro-Montoya , Eudes Naziazeno

An important question in dynamical systems is the classification problem, i.e., the ability to distinguish between two isomorphic systems. In this work, we study the topological factors between a family of multidimensional substitutive…

Dynamical Systems · Mathematics 2025-06-11 Christopher Cabezas , Julien Leroy

There exist NIP and non-NTP$_2$ theories satisfying all the following conditions: It is not o-minimal; All models are strongly locally o-minimal; It has a model which is an expansion of the linearly ordered abelian group over the reals…

Logic · Mathematics 2022-08-18 Masato Fujita

This paper presents a theory of systemic undecidability, reframing incomputability as a structural property of systems rather than a localized feature of specific functions or problems. We define a notion of causal embedding and prove a…

Logic in Computer Science · Computer Science 2025-09-03 Seth Bulin

We find new "reasons" for a class of models for not having a universal model in a cardinal $\lambda$. This work, though it has consequences in model theory, is really in combinatorial set theory. We concentrate on a prototypical class which…

Logic · Mathematics 2022-03-15 Saharon Shelah

Given a machine learning (ML) model and a prediction, explanations can be defined as sets of features which are sufficient for the prediction. In some applications, and besides asking for an explanation, it is also critical to understand…

Machine Learning · Computer Science 2023-02-08 Xuanxiang Huang , Martin C. Cooper , Antonio Morgado , Jordi Planes , Joao Marques-Silva

Multi-label classification consists in classifying an instance into two or more classes simultaneously. It is a very challenging task present in many real-world applications, such as classification of biology, image, video, audio, and text.…

Machine Learning · Computer Science 2020-04-03 Thiago Zafalon Miranda , Diorge Brognara Sardinha , Márcio Porto Basgalupp , Yaochu Jin , Ricardo Cerri

When predictive models are used to support complex and important decisions, the ability to explain a model's reasoning can increase trust, expose hidden biases, and reduce vulnerability to adversarial attacks. However, attempts at…

Machine Learning · Computer Science 2019-07-11 Dimitris Bertsimas , Arthur Delarue , Patrick Jaillet , Sebastien Martin

In empirical studies, the data usually don't include all the variables of interest in an economic model. This paper shows the identification of unobserved variables in observations at the population level. When the observables are distinct…

Econometrics · Economics 2022-12-07 Yingyao Hu

We classify localising subcategories of the stable module category of a finite group that are closed under tensor product with simple (or, equivalently all) modules. One application is a proof of the telescope conjecture in this context.…

Representation Theory · Mathematics 2011-04-18 Dave Benson , Srikanth B. Iyengar , Henning Krause

The principle of minimal change in belief revision theory requires that, when accepting new information, one keeps one's belief state as close to the initial belief state as possible. This is precisely what the method known as minimal…

Artificial Intelligence · Computer Science 2025-12-01 Edoardo Baccini , Zoé Christoff , Nina Gierasimczuk , Rineke Verbrugge
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