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Online learning: A comprehensive survey
Online learning represents a family of machine learning methods, where a learner attempts
to tackle some predictive (or any type of decision-making) task by learning from a sequence …
to tackle some predictive (or any type of decision-making) task by learning from a sequence …
Online portfolio selection: A survey
Online portfolio selection is a fundamental problem in computational finance, which has
been extensively studied across several research communities, including finance, statistics …
been extensively studied across several research communities, including finance, statistics …
A deep reinforcement learning framework for the financial portfolio management problem
Financial portfolio management is the process of constant redistribution of a fund into
different financial products. This paper presents a financial-model-free Reinforcement …
different financial products. This paper presents a financial-model-free Reinforcement …
Reinforcement learning for quantitative trading
Quantitative trading (QT), which refers to the usage of mathematical models and data-driven
techniques in analyzing the financial market, has been a popular topic in both academia and …
techniques in analyzing the financial market, has been a popular topic in both academia and …
Alphastock: A buying-winners-and-selling-losers investment strategy using interpretable deep reinforcement attention networks
Recent years have witnessed the successful marriage of finance innovations and AI
techniques in various finance applications including quantitative trading (QT). Despite great …
techniques in various finance applications including quantitative trading (QT). Despite great …
Cost-sensitive portfolio selection via deep reinforcement learning
Portfolio Selection is an important real-world financial task and has attracted extensive
attention in artificial intelligence communities. This task, however, has two main difficulties:(i) …
attention in artificial intelligence communities. This task, however, has two main difficulties:(i) …
[HTML][HTML] An asset subset-constrained minimax optimization framework for online portfolio selection
Effective online portfolio selection necessitates seamless integration of three key properties:
diversity, sparsity, and risk control. However, existing algorithms often prioritize one property …
diversity, sparsity, and risk control. However, existing algorithms often prioritize one property …
[HTML][HTML] Moving average reversion strategy for on-line portfolio selection
On-line portfolio selection, a fundamental problem in computational finance, has attracted
increasing interest from artificial intelligence and machine learning communities in recent …
increasing interest from artificial intelligence and machine learning communities in recent …
Online portfolio management via deep reinforcement learning with high-frequency data
J Li, Y Zhang, X Yang, L Chen - Information Processing & Management, 2023 - Elsevier
Recently, models that based on Transformer (Vaswani et al., 2017) have yielded superior
results in many sequence modeling tasks. The ability of Transformer to capture long-range …
results in many sequence modeling tasks. The ability of Transformer to capture long-range …
Application of deep q-network in portfolio management
Machine Learning algorithms and Neural Networks are widely applied to many different
areas such as stock market prediction, facial recognition and automatic machine translation …
areas such as stock market prediction, facial recognition and automatic machine translation …