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Semidefinite Programming (SDP) provides tight lower bounds for Optimal Power Flow problems. However, solving large-scale SDP problems requires exploiting sparsity. In this paper, we experiment several clique decomposition algorithms that…

Optimization and Control · Mathematics 2019-12-20 Julie Sliwak , Miguel Anjos , Lucas Létocart , Jean Maeght , Emiliano Traversi

A core challenge in Machine Learning is to learn to disentangle natural factors of variation in data (e.g. object shape vs. pose). A popular approach to disentanglement consists in learning to map each of these factors to distinct subspaces…

Machine Learning · Computer Science 2021-02-11 Diane Bouchacourt , Mark Ibrahim , Stéphane Deny

We present a novel distributed computing framework that is robust to slow compute nodes, and is capable of both approximate and exact computation of linear operations. The proposed mechanism integrates the concepts of randomized sketching…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-09-06 Burak Bartan , Mert Pilanci

Coded computation is a framework which provides redundancy in distributed computing systems to speed up largescale tasks. Although most existing works assume an error-free scenarios in a master-worker setup, the link failures are common in…

Information Theory · Computer Science 2019-01-14 Dong-Jun Han , Jy-yong Sohn , Jaekyun Moon

We propose a unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including: part-of-speech tagging, chunking, named entity recognition, and semantic role labeling. This…

Machine Learning · Computer Science 2011-03-03 Ronan Collobert , Jason Weston , Leon Bottou , Michael Karlen , Koray Kavukcuoglu , Pavel Kuksa

As the complexity and size of software projects increases in real-world environments, maintaining and creating maintainable and dependable code becomes harder and more costly. Refactoring is considered as a method for enhancing the internal…

Software Engineering · Computer Science 2018-11-27 Mohammad Raji

Coded compressed sensing is an algorithmic framework tailored to sparse recovery in very large dimensional spaces. This framework is originally envisioned for the unsourced multiple access channel, a wireless paradigm attuned to…

Information Theory · Computer Science 2019-10-23 Vamsi K. Amalladinne , Jean-Francois Chamberland , Krishna R. Narayanan

A Task Decomposition method for iterative learning Model Predictive Control (TDMPC) for linear time-varying systems is presented. We consider the availability of state-input trajectories which solve an original task T1, and design a…

Systems and Control · Electrical Eng. & Systems 2020-05-05 Charlott Vallon , Francesco Borrelli

Text style transfer aims to alter the style of a sentence while preserving its content. Due to the lack of parallel corpora, most recent work focuses on unsupervised methods and often uses cycle construction to train models. Since cycle…

Computation and Language · Computer Science 2022-12-20 Kangchen Zhu , Zhiliang Tian , Ruifeng Luo , Xiaoguang Mao

This paper describes a method for compiling a constraint-based grammar into a potentially more efficient form for processing. This method takes dependent disjunctions within a constraint formula and factors them into non-interacting groups…

cmp-lg · Computer Science 2008-02-03 John Griffith

Diagram chasing is not an easy task. The coherence holds in a generalized sense if we have a mechanical method to judge whether given two morphisms are equal to each other. A simple way to this end is to reform a concerned category into a…

Logic in Computer Science · Computer Science 2020-10-09 Ryu Hasegawa

We previously developed a polymorphic type system and a type checker for a multithreaded lock-based polymorphic typed assembly language (MIL) that ensures that well-typed programs do not encounter race conditions. This paper extends such…

Programming Languages · Computer Science 2010-02-05 Vasco T. Vasconcelos , Francisco Martins , Tiago Cogumbreiro

In order to reason about the behaviour of programs described in a programming language, a mathematically rigorous definition of that language is needed. In this paper, we present a machine-checked formalisation of concurrent Core Erlang (a…

Programming Languages · Computer Science 2023-11-20 Péter Bereczky , Dániel Horpácsi , Simon Thompson

We study hard constraint satisfaction problems with a decimation approach based on message passing algorithms. Decimation induces a renormalization flow in the space of problems, and we exploit the fact that this flow transforms some of the…

Disordered Systems and Neural Networks · Physics 2010-05-11 Saburo Higuchi , Marc Mézard

We consider the recently proposed Coded Distributed Computing (CDC) framework that leverages carefully designed redundant computations to enable coding opportunities that substantially reduce the communication load of distributed computing.…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-09-04 Mehrdad Kiamari , Chenwei Wang , A. Salman Avestimehr

The Timed Concurrent Constraint Language (tccp in short) is a concurrent logic language based on the simple but powerful concurrent constraint paradigm of Saraswat. In this paradigm, the notion of store-as-value is replaced by the notion of…

Programming Languages · Computer Science 2011-09-09 Marco Comini , Laura Titolo , Alicia Villanueva

In this paper, we study sliding window decoding of braided convolutional codes (BCCs) in the context of a streaming application, where decoder error propagation can be a serious problem. A window extension algorithm and a resynchronization…

Information Theory · Computer Science 2018-01-11 Min Zhu , David G. M. Mitchell , Michael Lentmaier , Daniel J. Costello, , Baoming Bai

We propose an operationally-based deductive proof method for program equivalence. It is based on encoding the language semantics as logically constrained term rewriting systems (LCTRSs) and the two programs as terms. The main feature of our…

Logic in Computer Science · Computer Science 2020-01-28 Ştefan Ciobâcă , Dorel Lucanu , Andrei Sebastian Buruiană

Large language models (LLMs) have achieved notable success in code generation. However, they still frequently produce uncompilable output because their next-token inference procedure does not model formal aspects of code. Although…

Machine Learning · Computer Science 2025-05-09 Niels Mündler , Jingxuan He , Hao Wang , Koushik Sen , Dawn Song , Martin Vechev

Computer-based systems have solved several domain problems, including industrial, military, education, and wearable. Nevertheless, such arrangements need high-quality software to guarantee security and safety as both are mandatory for…