Zobrazeno 1 - 10
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pro vyhledávání: '"Laue, Soeren"'
Autor:
Laue, Sören, Prusina, Tomislav
Unconstrained optimization problems are typically solved using iterative methods, which often depend on line search techniques to determine optimal step lengths in each iteration. This paper introduces a novel line search approach. Traditional line s
Externí odkaz:
http://arxiv.org/abs/2405.10897
We present a novel approach to detecting noun abstraction within a large language model (LLM). Starting from a psychologically motivated set of noun pairs in taxonomic relationships, we instantiate surface patterns indicating hypernymy and analyze th
Externí odkaz:
http://arxiv.org/abs/2404.15848
Capsule neural networks replace simple, scalar-valued neurons with vector-valued capsules. They are motivated by the pattern recognition system in the human brain, where complex objects are decomposed into a hierarchy of simpler object parts. Such a
Externí odkaz:
http://arxiv.org/abs/2301.01583
The Hessian of a differentiable convex function is positive semidefinite. Therefore, checking the Hessian of a given function is a natural approach to certify convexity. However, implementing this approach is not straightforward since it requires a r
Externí odkaz:
http://arxiv.org/abs/2210.10430
Constrained optimization problems arise frequently in classical machine learning. There exist frameworks addressing constrained optimization, for instance, CVXPY and GENO. However, in contrast to deep learning frameworks, GPU support is limited. Here
Externí odkaz:
http://arxiv.org/abs/2203.16340
Computing derivatives of tensor expressions, also known as tensor calculus, is a fundamental task in machine learning. A key concern is the efficiency of evaluating the expressions and their derivatives that hinges on the representation of these expr
Externí odkaz:
http://arxiv.org/abs/2010.03313
Although optimization is the longstanding algorithmic backbone of machine learning, new models still require the time-consuming implementation of new solvers. As a result, there are thousands of implementations of optimization algorithms for machine
Externí odkaz:
http://arxiv.org/abs/1905.13587
Autor:
Laue, Soeren
We show that reverse mode automatic differentiation and symbolic differentiation are equivalent in the sense that they both perform the same operations when computing derivatives. This is in stark contrast to the common claim that they are substantia
Externí odkaz:
http://arxiv.org/abs/1904.02990
Autor:
Giesen, Joachim, Kahlmeyer, Paul, Laue, Sören, Mitterreiter, Matthias, Nussbaum, Frank, Staudt, Christoph
Publikováno v:
In Journal of Multivariate Analysis May 2023 195
Akademický článek
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