Zobrazeno 1 - 10
of 191
pro vyhledávání: '"Mitiche, Amar"'
We introduce a Parametric Information Maximization (PIM) model for the Generalized Category Discovery (GCD) problem. Specifically, we propose a bi-level optimization formulation, which explores a parameterized family of objective functions, each eval
Externí odkaz:
http://arxiv.org/abs/2212.00334
We explore clustering the softmax predictions of deep neural networks and introduce a novel probabilistic clustering method, referred to as k-sBetas. In the general context of clustering discrete distributions, the existing methods focused on explori
Externí odkaz:
http://arxiv.org/abs/2208.00287
In this work we define and analyze the bilinear models which replace the conventional linear operation used in many building blocks of machine learning (ML). The main idea is to devise the ML algorithms which are adapted to the objects they treat. In
Externí odkaz:
http://arxiv.org/abs/1912.03354
Publikováno v:
In Expert Systems With Applications 1 December 2023 232
In the context of recent deep clustering studies, discriminative models dominate the literature and report the most competitive performances. These models learn a deep discriminative neural network classifier in which the labels are latent. Typically
Externí odkaz:
http://arxiv.org/abs/1810.04246
Akademický článek
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Autor:
Mezghani, Neila, Ouakrim, Youssef, Fuentes, Alexandre, Mitiche, Amar, Hagemeister, Nicola, Vendittoli, Pascal-André, de Guise, Jacques A.
Publikováno v:
In Journal of Biomechanics 8 February 2017 52:106-112