Zobrazeno 1 - 10
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pro vyhledávání: '"A. A. Bokun"'
Autor:
Elezović, Stefan
Publikováno v:
NOVI IZRAZ, časopis za književnu i umjetničku kritiku / NEW EXPRESSION, magazine for literary and art criticism. (79-80):103-105
Externí odkaz:
https://www.ceeol.com/search/article-detail?id=924882
We study the discriminative probabilistic modeling problem on a continuous domain for (multimodal) self-supervised representation learning. To address the challenge of computing the integral in the partition function for each anchor data, we leverage
Externí odkaz:
http://arxiv.org/abs/2410.09156
Recent work has shown that 8-bit floating point (FP8) can be used for efficiently training neural networks with reduced computational overhead compared to training in FP32/FP16. In this work, we investigate the use of FP8 training in a federated lear
Externí odkaz:
http://arxiv.org/abs/2407.02610
Akademický článek
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Autor:
Mojaver, Kaveh Rahbardar, Zhao, Bokun, Leung, Edward, Safaee, S. Mohammad Reza, Liboiron-Ladouceur, Odile
Publikováno v:
Optics Express, vol. 31, no.15, pp. 23851-23866, July 2023
We demonstrate a novel mesh of Mach-Zehnder interferometers (MZIs) for programmable optical processors. The proposed mesh, referred to as Bokun mesh, is an architecture that merges the attributes of the prior topologies Diamond and Clements. Similar
Externí odkaz:
http://arxiv.org/abs/2303.04151
Autor:
Wang, Bokun, Yang, Tianbao
This paper revisits a class of convex Finite-Sum Coupled Compositional Stochastic Optimization (cFCCO) problems with many applications, including group distributionally robust optimization (GDRO), learning with imbalanced data, reinforcement learning
Externí odkaz:
http://arxiv.org/abs/2312.02277
As powerful tools for representation learning on graphs, graph neural networks (GNNs) have played an important role in applications including social networks, recommendation systems, and online web services. However, GNNs have been shown to be vulner
Externí odkaz:
http://arxiv.org/abs/2308.15614
Autor:
Woo-jin Kim
Publikováno v:
THE CHOSON DYNASTY HISTORY ASSOCIATION. 99:75-104
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::20b8cea2bb115f3c9e7ece99299049d5
https://doi.org/10.21568/cdha.2021.12.99.75
https://doi.org/10.21568/cdha.2021.12.99.75
This paper considers a novel application of deep AUC maximization (DAM) for multi-instance learning (MIL), in which a single class label is assigned to a bag of instances (e.g., multiple 2D slices of a CT scan for a patient). We address a neglected y
Externí odkaz:
http://arxiv.org/abs/2305.08040