Zobrazeno 1 - 10
of 77
pro vyhledávání: '"Tran, Dat Thanh"'
Many cryptocurrency brokers nowadays offer a variety of derivative assets that allow traders to perform hedging or speculation. This paper proposes an effective algorithm based on neural networks to take advantage of these investment products. The pr
Externí odkaz:
http://arxiv.org/abs/2310.01148
Mineral wool production is a non-linear process that makes it hard to control the final quality. Therefore, having a non-destructive method to analyze the product quality and recognize defective products is critical. For this purpose, we developed a
Externí odkaz:
http://arxiv.org/abs/2211.00466
Deep Learning models have become dominant in tackling financial time-series analysis problems, overturning conventional machine learning and statistical methods. Most often, a model trained for one market or security cannot be directly applied to ano
Externí odkaz:
http://arxiv.org/abs/2207.11577
Bayesian Neural Networks (BNNs) provide a tool to estimate the uncertainty of a neural network by considering a distribution over weights and sampling different models for each input. In this paper, we propose a method for uncertainty estimation in n
Externí odkaz:
http://arxiv.org/abs/2207.01524
Research on limit order book markets has been rapidly growing and nowadays high-frequency full order book data is widely available for researchers and practitioners. However, it is common that research papers use the best level data only, which motiv
Externí odkaz:
http://arxiv.org/abs/2203.07922
Financial time-series forecasting is one of the most challenging domains in the field of time-series analysis. This is mostly due to the highly non-stationary and noisy nature of financial time-series data. With progressive efforts of the community t
Externí odkaz:
http://arxiv.org/abs/2201.05459
Multilinear Compressive Learning (MCL) is an efficient signal acquisition and learning paradigm for multidimensional signals. The level of signal compression affects the detection or classification performance of a MCL model, with higher compression
Externí odkaz:
http://arxiv.org/abs/2109.01184
Data normalization is one of the most important preprocessing steps when building a machine learning model, especially when the model of interest is a deep neural network. This is because deep neural network optimized with stochastic gradient descent
Externí odkaz:
http://arxiv.org/abs/2109.00983
Knowledge Distillation refers to a class of methods that transfers the knowledge from a teacher network to a student network. In this paper, we propose Sparse Representation Matching (SRM), a method to transfer intermediate knowledge obtained from on
Externí odkaz:
http://arxiv.org/abs/2103.17012
Recently, the Multilinear Compressive Learning (MCL) framework was proposed to efficiently optimize the sensing and learning steps when working with multidimensional signals, i.e. tensors. In Compressive Learning in general, and in MCL in particular,
Externí odkaz:
http://arxiv.org/abs/2009.10456