Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Zhang, Tongtao"'
Publikováno v:
Data Intelligence, Vol 1, Iss 2, Pp 99-120 (2019)
We propose a new framework for entity and event extraction based on generative adversarial imitation learning—an inverse reinforcement learning method using a generative adversarial network (GAN). We assume that instances and labels yield to variou
Externí odkaz:
https://doaj.org/article/3c09cf3d056e4f3796f50a523fc3bce5
Publikováno v:
Published at the DLDE Workshop in NeurIPS 2022
Transformer layers, which use an alternating pattern of multi-head attention and multi-layer perceptron (MLP) layers, provide an effective tool for a variety of machine learning problems. As the transformer layers use residual connections to avoid th
Externí odkaz:
http://arxiv.org/abs/2212.06011
Computational fluid dynamics (CFD) simulations, a critical tool in various engineering applications, often require significant time and compute power to predict flow properties. The high computational cost associated with CFD simulations significantl
Externí odkaz:
http://arxiv.org/abs/2205.08355
Incompressible fluid flow around a cylinder is one of the classical problems in fluid-dynamics with strong relevance with many real-world engineering problems, for example, design of offshore structures or design of a pin-fin heat exchanger. Thus lea
Externí odkaz:
http://arxiv.org/abs/2011.01456
In this paper, we address a practical scenario where training data is released in a sequence of small-scale batches and annotation in earlier phases has lower quality than the later counterparts. To tackle the situation, we utilize a pre-trained tran
Externí odkaz:
http://arxiv.org/abs/2002.04165
We present an end-to-end approach that takes unstructured textual input and generates structured output compliant with a given vocabulary. Inspired by recent successes in neural machine translation, we treat the triples within a given knowledge graph
Externí odkaz:
http://arxiv.org/abs/1807.01763
Autor:
Zhang, Tongtao, Ji, Heng
We propose a new method for event extraction (EE) task based on an imitation learning framework, specifically, inverse reinforcement learning (IRL) via generative adversarial network (GAN). The GAN estimates proper rewards according to the difference
Externí odkaz:
http://arxiv.org/abs/1804.07881
Publikováno v:
Journal of Vibration & Control; Jul2024, Vol. 30 Issue 13/14, p2894-2903, 10p
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Akademický článek
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