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We study the weak call-by-value $\lambda$-calculus as a model for computational complexity theory and establish the natural measures for time and space -- the number of beta-reductions and the size of the largest term in a computation -- as…

Computational Complexity · Computer Science 2022-12-09 Yannick Forster , Fabian Kunze , Marc Roth

The $\pi$-calculus is used as a model for programming languages. Its contexts exhibit arbitrary concurrency, making them very discriminating. This may prevent validating desirable behavioural equivalences in cases when more disciplined…

Logic in Computer Science · Computer Science 2021-12-14 Daniel Hirschkoff , Enguerrand Prebet , Davide Sangiorgi

We present a C-language implementation of the lambda-pi calculus by extending the (call-by-need) stack machine of Ariola, Chang and Felleisen to hold types, using a typeless- tagless- final interpreter strategy. It has the advantage of…

Programming Languages · Computer Science 2015-09-24 David M. Rogers

With the explosion of massive, widely available unlabeled data in the past years, finding label and time efficient, robust learning algorithms has become ever more important in theory and in practice. We study the paradigm of active…

Machine Learning · Computer Science 2020-01-17 Max Hopkins , Daniel Kane , Shachar Lovett , Gaurav Mahajan

Probabilistic linear discriminant analysis (PLDA) has broad application in open-set verification tasks, such as speaker verification. A key concern for PLDA is that the model is too simple (linear Gaussian) to deal with complicated data;…

Sound · Computer Science 2021-11-25 Di Wang , Lantian Li , Hongzhi Yu , Dong Wang

The human ability to flexibly reason using analogies with domain-general content depends on mechanisms for identifying relations between concepts, and for mapping concepts and their relations across analogs. Building on a recent model of…

Artificial Intelligence · Computer Science 2021-10-06 Hongjing Lu , Nicholas Ichien , Keith J. Holyoak

We introduce a batched lazy algorithm for supervised classification using decision trees. It avoids unnecessary visits to irrelevant nodes when it is used to make predictions with either eagerly or lazily trained decision trees. A set of…

Machine Learning · Computer Science 2016-03-09 Mathieu Guillame-Bert , Artur Dubrawski

Interactive behaviors are ubiquitous in modern cryptography, but are also present in $\lambda$-calculi, in the form of higher-order constructions. Traditionally, however, typed $\lambda$-calculi simply do not fit well into cryptography,…

Logic in Computer Science · Computer Science 2015-06-12 Alberto Cappai , Ugo Dal Lago

Weak-head normalization is inconsistent with functional extensionality in the call-by-name $\lambda$-calculus. We explore this problem from a new angle via the conflict between extensionality and effects. Leveraging ideas from work on the…

Programming Languages · Computer Science 2016-06-22 Philip Johnson-Freyd , Paul Downen , Zena M. Ariola

Assumption-based Argumentation (ABA) is advocated as a unifying formalism for various forms of non-monotonic reasoning, including logic programming. It allows capturing defeasible knowledge, subject to argumentative debate. While, in much…

Artificial Intelligence · Computer Science 2024-11-11 Emanuele De Angelis , Maurizio Proietti , Francesca Toni

We prove an impossibility result for conditional Probably Approximately Correct (PAC)-efficient reasoning in large language models. While recent work has established marginal PAC efficiency guarantees for composite models that switch…

Machine Learning · Statistics 2025-12-04 Hao Zeng

A predicate linear temporal logic LTL_{\lambda,=} without quantifiers but with predicate abstraction mechanism and equality is considered. The models of LTL_{\lambda,=} can be naturally seen as the systems of pebbles (flexible constants)…

Logic in Computer Science · Computer Science 2007-05-23 Alexei Lisitsa , Igor Potapov

Bayesian inference typically relies on specifying a parametric model that approximates the data-generating process. However, misspecified models can yield poor convergence rates and unreliable posterior calibration. Bayesian empirical…

Methodology · Statistics 2025-10-27 Kenyon Ng , Weichang Yu , Howard D. Bondell

Describing systems in terms of choices and their resulting costs and rewards offers the promise of freeing algorithm designers and programmers from specifying how those choices should be made; in implementations, the choices can be realized…

Logic in Computer Science · Computer Science 2024-02-14 Martin Abadi , Gordon Plotkin

We consider principled alternatives to unsupervised learning in data mining by situating the learning task in the context of the subsequent analysis task. Specifically, we consider a query-answering (hypothesis-testing) task: In the…

Data Structures and Algorithms · Computer Science 2013-04-18 Brendan Juba

Probabilistic Answer Set Programming under the credal semantics (PASP) extends Answer Set Programming with probabilistic facts that represent uncertain information. The probabilistic facts are discrete with Bernoulli distributions. However,…

Artificial Intelligence · Computer Science 2025-02-19 Damiano Azzolini , Fabrizio Riguzzi

We study the bisimilarity problem for probabilistic pushdown automata (pPDA) and subclasses thereof. Our definition of pPDA allows both probabilistic and non-deterministic branching, generalising the classical notion of pushdown automata…

Logic in Computer Science · Computer Science 2023-06-22 Vojtěch Forejt , Petr Jančar , Stefan Kiefer , James Worrell

Designing models that are both expressive and preserve known invariances of tasks is an increasingly hard problem. Existing solutions tradeoff invariance for computational or memory resources. In this work, we show how to leverage…

Machine Learning · Computer Science 2023-09-29 Leonardo Cotta , Gal Yehuda , Assaf Schuster , Chris J. Maddison

We investigate the possibility of a semantic account of the execution time (i.e. the number of beta-steps leading to the normal form, if any) for the shuffling calculus, an extension of Plotkin's call-by-value lambda-calculus. For this…

Logic in Computer Science · Computer Science 2019-04-25 Giulio Guerrieri

We present a call-by-need $\lambda$-calculus that enables strong reduction (that is, reduction inside the body of abstractions) and guarantees that arguments are only evaluated if needed and at most once. This calculus uses explicit…

Logic in Computer Science · Computer Science 2023-06-22 Thibaut Balabonski , Antoine Lanco , Guillaume Melquiond