Zobrazeno 1 - 10
of 35
pro vyhledávání: '"GRØNLUND, ALLAN"'
Autor:
Grønlund, Allan, Larsen, Kasper Green
Achieving a provable exponential quantum speedup for an important machine learning task has been a central research goal since the seminal HHL quantum algorithm for solving linear systems and the subsequent quantum recommender systems algorithm by Ke
Externí odkaz:
http://arxiv.org/abs/2411.02087
Publikováno v:
TheoretiCS, Volume 3 (October 4, 2024) theoretics:13000
We pose the fine-grained hardness hypothesis that the textbook algorithm for the NFA Acceptance problem is optimal up to subpolynomial factors, even for dense NFAs and fixed alphabets. We show that this barrier appears in many variations throughout t
Externí odkaz:
http://arxiv.org/abs/2311.10204
Computing a shortest path between two nodes in an undirected unweighted graph is among the most basic algorithmic tasks. Breadth first search solves this problem in linear time, which is clearly also a lower bound in the worst case. However, several
Externí odkaz:
http://arxiv.org/abs/2307.06113
Explaining the surprising generalization performance of deep neural networks is an active and important line of research in theoretical machine learning. Influential work by Arora et al. (ICML'18) showed that, noise stability properties of deep nets
Externí odkaz:
http://arxiv.org/abs/2106.07989
Autor:
Grønlund, Allan, Tranberg, Jonas
High resolution data models like grid terrain models made from LiDAR data are a prerequisite for modern day Geographic Information Systems applications. Besides providing the foundation for the very accurate digital terrain models, LiDAR data is also
Externí odkaz:
http://arxiv.org/abs/2105.12385
Boosting is one of the most successful ideas in machine learning, achieving great practical performance with little fine-tuning. The success of boosted classifiers is most often attributed to improvements in margins. The focus on margin explanations
Externí odkaz:
http://arxiv.org/abs/2011.04998
Support Vector Machines (SVMs) are among the most fundamental tools for binary classification. In its simplest formulation, an SVM produces a hyperplane separating two classes of data using the largest possible margin to the data. The focus on maximi
Externí odkaz:
http://arxiv.org/abs/2006.02175
Autor:
Grønlund, Allan
By investigating the code for the KASS algorithm implementation used in the paper "Exploring the quantum speed limit with computer games" [1, arXiv:1506.09091] by S{\o}rensen et al. (provided by the authors), we describe how the poor performance of t
Externí odkaz:
http://arxiv.org/abs/2003.05808
Boosting is one of the most successful ideas in machine learning. The most well-accepted explanations for the low generalization error of boosting algorithms such as AdaBoost stem from margin theory. The study of margins in the context of boosting al
Externí odkaz:
http://arxiv.org/abs/1909.12518
High resolution Digital Elevation models, such as the (Big) grid terrain model of Denmark with more than 200 billion measurements, is a basic requirement for water flow modelling and flood risk analysis. However, a large number of modifications often
Externí odkaz:
http://arxiv.org/abs/1909.07685