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The sheer sizes of modern datasets are forcing data-structure designers to consider seriously both parallel construction and compactness. To achieve those goals we need to design a parallel algorithm with good scalability and with low…

Data Structures and Algorithms · Computer Science 2017-05-02 Leo Ferres , José Fuentes-Sepúlveda , Travis Gagie , Meng He , Gonzalo Navarro

In recent years, manifold methods have moved into focus as tools for dimension reduction. Assuming that the high-dimensional data actually lie on or close to a low-dimensional nonlinear manifold, these methods have shown convincing results…

Machine Learning · Statistics 2020-12-23 Moritz Herrmann , Fabian Scheipl

This paper presents a method to detect and recognize symmetries in Boolean functions. The idea is to use information theoretic measures of Boolean functions to detect sub-space of possible symmetric variables. Coupled with the new…

Other Computer Science · Computer Science 2007-10-15 Denis V. Popel

We consider the problem of learning a function respecting a symmetry from among a class of symmetries. We develop a unified framework that enables symmetry discovery across a broad range of subgroups including locally symmetric, dihedral…

Machine Learning · Computer Science 2023-10-30 Pavan Karjol , Rohan Kashyap , Aditya Gopalan , Prathosh A. P

In this paper, a comprehensive performance review of a MPI-based high-order spectral and mortar element method C++ toolbox is presented. The focus is put on the performance evaluation of several aspects with a particular emphasis on the…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-09-10 Roland Bouffanais , Vincent Keller , Ralf Gruber , Michel O. Deville

We address the problem of finding optimal strategies for computing Boolean symmetric functions. We consider a collocated network, where each node's transmissions can be heard by every other node. Each node has a Boolean measurement and we…

Information Theory · Computer Science 2009-11-18 Hemant Kowshik , P. R. Kumar

In functional programming, monads are supposed to encapsulate computations, effectfully producing the final result, but keeping to themselves the means of acquiring it. For various reasons, we sometimes want to reveal the internals of a…

Programming Languages · Computer Science 2012-02-15 Maciej Piróg , Jeremy Gibbons

Synthesizing programs from examples requires searching over a vast, combinatorial space of possible programs. In this search process, a key challenge is representing the behavior of a partially written program before it can be executed, to…

Programming Languages · Computer Science 2021-04-21 Maxwell Nye , Yewen Pu , Matthew Bowers , Jacob Andreas , Joshua B. Tenenbaum , Armando Solar-Lezama

We describe generating functions for several important families of classical symmetric functions and shifted Schur functions. The approach is originated from vertex operator realization of symmetric functions and offers a unified method to…

Combinatorics · Mathematics 2020-08-10 Naihuan Jing , Natasha Rozhkovskaya

Consensus clustering fuses diverse basic partitions (i.e., clustering results obtained from conventional clustering methods) into an integrated one, which has attracted increasing attention in both academic and industrial areas due to its…

Machine Learning · Computer Science 2019-06-04 Hongfu Liu , Zhiqiang Tao , Zhengming Ding

Embedded spaces are a key feature in deep learning. Good embedded spaces represent the data well to support classification and advanced techniques such as open-set recognition, few-short learning and explainability. This paper presents a…

Machine Learning · Computer Science 2024-08-06 Stefan Scholl

Symmetry is fundamental in the description and simulation of quantum systems. Leveraging symmetries in classical simulations of many-body quantum systems can results in significant overhead due to the exponentially growing size of some…

Task based parallel programming has shown competitive outcomes in many aspects of parallel programming such as efficiency, performance, productivity and scalability. Different approaches are used by different software development frameworks…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-05-09 Afshin Zafari

This paper uses monads and comonads to establish a certain type of equivalence between two subcategories, one reflective and one coreflective, in a category whose objects represent compactifications of non-compact locally compact Hausdorff…

Operator Algebras · Mathematics 2026-01-14 Jeri Ann Spiker

Treating neural network inputs and outputs as random variables, we characterize the structure of neural networks that can be used to model data that are invariant or equivariant under the action of a compact group. Much recent research has…

Machine Learning · Statistics 2020-09-18 Benjamin Bloem-Reddy , Yee Whye Teh

The conjugate function method is an algorithm for numerical computation of conformal mappings for simply and doubly connected domains. In this paper the conjugate function method is generalized for multiply connected domains. The key…

Numerical Analysis · Mathematics 2017-07-06 Harri Hakula , Tri Quach , Antti Rasila

The explosive demand for artificial intelligence (AI) workloads has led to a significant increase in silicon area dedicated to lower-precision computations on recent high-performance computing hardware designs. However, mixed-precision…

Computational Engineering, Finance, and Science · Computer Science 2025-09-09 Aditya Kashi , Hao Lu , Wesley Brewer , David Rogers , Michael Matheson , Mallikarjun Shankar , Feiyi Wang

Similarity query is the family of queries based on some similarity metrics. Unlike the traditional database queries which are mostly based on value equality, similarity queries aim to find targets "similar enough to" the given data objects,…

Databases · Computer Science 2022-04-19 Yifan Wang

We give a short survey on plurisubharmonic interpolation, with focus on possibility of connecting two given plurisubharmonic functions by plurisubharmonic geodesic.

Complex Variables · Mathematics 2023-07-07 Alexander Rashkovskii

Submodular functions are a special class of set functions which naturally model the notion of representativeness, diversity, coverage etc. and have been shown to be computationally very efficient. A lot of past work has applied submodular…

Machine Learning · Computer Science 2022-02-24 Vishal Kaushal , Ganesh Ramakrishnan , Rishabh Iyer
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