Results 1 to 10 of about 55,495 (230)
Randomized and Deterministic Attention Sparsification Algorithms for Over-parameterized Feature Dimension [PDF]
arXiv.org, 2023 Large language models (LLMs) have shown their power in different areas. Attention computation, as an important subroutine of LLMs, has also attracted interests in theory. Recently the static computation and dynamic maintenance of attention matrix has been studied by [Alman and Song 2023] and [Brand, Song and Zhou 2023] from both algorithmic perspective
Deng, Yichuan +2 more
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The Intersection of Algorithmically Random Closed Sets and Effective Dimension
ACM Transactions on Computational Logic, 2022 In this article, we study several aspects of the intersections of algorithmically random closed sets. First, we answer a question of Cenzer and Weber, showing that the operation of intersecting relatively random closed sets (random with respect to certain underlying measures induced by Bernoulli measures on the space of codes of closed sets), which ...
Adam Case, Christopher P. Porter
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Data Dimension Reduction makes ML Algorithms efficient [PDF]
2022 International Conference on Emerging Technologies in Electronics, Computing and Communication (ICETECC), 2022 Data dimension reduction (DDR) is all about mapping data from high dimensions to low dimensions, various techniques of DDR are being used for image dimension reduction like Random Projections, Principal Component Analysis (PCA), the Variance approach ...
Wisal Khan +5 more
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Journal of Global Optimization, 2023 AbstractWe consider global optimization problems, where the feasible region $${\mathcal {X}}$$ X is a compact subset of $$\mathbb {R}^d$$ R d with $$d \ge 10$$
Jack Noonan, Anatoly Zhigljavsky
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SignDS-FL: Local Differentially Private Federated Learning with Sign-based Dimension Selection
ACM Transactions on Intelligent Systems and Technology, 2022 Federated Learning (FL) [31] is a decentralized learning mechanism that has attracted increasing attention due to its achievements in computational efficiency and privacy preservation.
Xue Jiang, Xuebing Zhou, Jens Grossklags
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Polynomial Representations of Threshold Functions and Algorithmic Applications [PDF]
IEEE Annual Symposium on Foundations of Computer Science, 2016 We design new polynomials for representing threshold functions in three different regimes: probabilistic polynomials of low degree, which need far less randomness than previous constructions, polynomial threshold functions (PTFs) with "nice" threshold ...
Josh Alman +2 more
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Fractal dimension of coastline of Australia
Scientific Reports, 2021 Coastlines are irregular in nature having (random) fractal geometry and are formed by various natural activities. Fractal dimension is a measure of degree of geometric irregularity present in the coastline. A novel multicore parallel processing algorithm
A. Husain +3 more
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Random field Ising model in two dimensions: Bethe approximation, cluster variational method and message passing algorithms [PDF]
Journal of Statistical Mechanics: Theory and Experiment, 2015 We study two free energy approximations (Bethe and plaquette-CVM) for the Random Field Ising Model in two dimensions. We compare results obtained by these two methods in single instances of the model on the square grid, showing the difficulties arising in defining a robust critical line.
DomÃnguez, Eduardo +2 more
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Performance Analysis of Turbo-Code with Random (and s-random) Interleaver based on 3-Dimension Algorithm [PDF]
The KIPS Transactions:PartA, 2002 In this paper, we apply the 3-dimension algorithm to the random interleaver and s-random interleaver and analyze the performance of the turbo code system with random interleaver (or s-random interleaver). In general, the performance of interleaver is determined by minimum distance between neighbor data, thus we could improve the performance of ...
Hyung-Yun Kong, Ji-Woong Choi
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Strong Quantum Computational Advantage Using a Superconducting Quantum Processor. [PDF]
Physical Review Letters, 2021 Scaling up to a large number of qubits with high-precision control is essential in the demonstrations of quantum computational advantage to exponentially outpace the classical hardware and algorithmic improvements.
Yulin Wu +53 more
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