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Type theories with higher-order subtyping or singleton types are examples of systems where computation rules for variables are affected by type information in the context. A complication for these systems is that bounds declared in the…

Logic in Computer Science · Computer Science 2011-01-25 Adriana Compagnoni , Healfdene Goguen

Class invariants are both a core concept of object-oriented programming and the source of the two key open OO verification problems: furtive access (from callbacks) and reference leak. Existing approaches force on programmers an…

Software Engineering · Computer Science 2021-05-28 Bertrand Meyer

Categorical regressor variables are usually handled by introducing a set of indicator variables, and imposing a linear constraint to ensure identifiability in the presence of an intercept, or equivalently, using one of various coding…

Computation · Statistics 2018-05-21 Felicitas J. Detmer , Martin Slawski

We address the recently suggested problem of causal lossless coding of a randomly arriving source samples. We construct variable-to-fixed coding schemes and show that they outperform the previously considered fixed-to-variable schemes when…

Information Theory · Computer Science 2020-10-27 Uri Abend , Anatoly Khina

Migration to OCaml 5 requires updating a lot of C bindings due to the removal of naked pointer support. Writing OCaml user-defined primitives in C is a necessity, but is unsafe and error-prone. It does not benefit from either OCaml's or C's…

Programming Languages · Computer Science 2023-07-31 Edwin Török

We present a novel and well automatable approach to formal verification of C programs with underspecified semantics, i.e., a language semantics that leaves open the order of certain evaluations. First, we reduce this problem to…

Programming Languages · Computer Science 2022-08-10 Eduard Kamburjan , Nathan Wasser

We present a generic programming framework for OCAML which makes it possible to implement extensible transformations for a large scale of type definitions. Our framework makes use of objectoriented features of OCAML, utilising late binding…

Programming Languages · Computer Science 2021-06-03 Dmitrii Kosarev , Dmitry Boulytchev

A mathematical framework for modelling constrained mixed-variable optimization problems is presented in a blackbox optimization context. The framework introduces a new notation and allows solution strategies. The notation framework allows…

Optimization and Control · Mathematics 2022-04-05 Charles Audet , Edward Hallé-Hannan , Sébastien Le Digabel

Conditional Monte Carlo (CMC) has been widely used for sensitivity estimation with discontinuous integrands as a standard simulation technique. A major limitation of using CMC in this context is that finding conditioning variables to ensure…

Probability · Mathematics 2016-03-22 Guiyun Feng , Guangwu Liu

The Bindlib library for OCaml provides a set of tools for the manipulation of data structures with variable binding. It is very well suited for the representation of abstract syntax trees, and has already been used for the implementation of…

Programming Languages · Computer Science 2018-07-06 Rodolphe Lepigre , Christophe Raffalli

We introduce SecRef*, a secure compilation framework protecting stateful programs verified in F* against linked unverified code, with which the program dynamically shares ML-style mutable references. To ease program verification in this…

In dependently typed programming, proofs of basic, structural properties can be embedded implicitly into programs and do not need to be written explicitly. Besides saving the effort of writing separate proofs, a most distinguishing and…

Programming Languages · Computer Science 2021-03-09 Hsiang-Shang Ko

The inferential model (IM) framework provides valid prior-free probabilistic inference by focusing on predicting unobserved auxiliary variables. But, efficient IM-based inference can be challenging when the auxiliary variable is of higher…

Statistics Theory · Mathematics 2015-01-20 Ryan Martin , Chuanhai Liu

Local variable selection aims to test for the effect of covariates on an outcome within specific regions. We outline a challenge that arises in the presence of non-linear effects and model misspecification. Specifically, for common…

Methodology · Statistics 2024-08-02 David Rossell , Arnold Kisuk Kseung , Ignacio Saez , Michele Guindani

The validity OF a causal model can be tested ONLY IF the model imposes constraints ON the probability distribution that governs the generated data. IN the presence OF unmeasured variables, causal models may impose two types OF constraints :…

Artificial Intelligence · Computer Science 2013-01-07 Jin Tian , Judea Pearl

We introduce an exploratory study on Mutation Validation (MV), a model validation method using mutated training labels for supervised learning. MV mutates training data labels, retrains the model against the mutated data, then uses the…

Machine Learning · Computer Science 2021-10-22 Jie M. Zhang , Mark Harman , Benjamin Guedj , Earl T. Barr , John Shawe-Taylor

Computing systems have become increasingly complex with the emergence of heterogeneous hardware combining multicore CPUs and GPUs. These parallel systems exhibit tremendous computational power at the cost of increased programming effort.…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-02-10 Michel Steuwer , Christian Fensch , Christophe Dubach

Type systems usually characterize the shape of values but not their free variables. However, there are many desirable safety properties one could guarantee if one could track how references can escape. For example, one may implement…

Programming Languages · Computer Science 2021-05-26 Aleksander Boruch-Gruszecki , Jonathan Immanuel Brachthäuser , Edward Lee , Ondřej Lhoták , Martin Odersky

We introduce a conditional generative model for learning to disentangle the hidden factors of variation within a set of labeled observations, and separate them into complementary codes. One code summarizes the specified factors of variation…

Machine Learning · Computer Science 2016-11-11 Michael Mathieu , Junbo Zhao , Pablo Sprechmann , Aditya Ramesh , Yann LeCun

Automatic source code analysis in key areas of software engineering, such as code security, can benefit from Machine Learning (ML). However, many standard ML approaches require a numeric representation of data and cannot be applied directly…

Machine Learning · Computer Science 2020-04-08 Rhys Compton , Eibe Frank , Panos Patros , Abigail Koay