过去一年中添加的文章,按日期排序

[图书][B] Recent Trends in Image Processing and Pattern Recognition: 6th International Conference, RTIP2R 2023, Derby, UK, December 7-8, 2023, Revised Selected …

KC Santosh, A Makkar, M Conway, AK Singh… - 2024 - books.google.com
92 天前 - automatic spiral analysis for the objective assessment of motor symptoms in PD.
This study used machine learning … train machine learning classifiers, including Support Vector …

[图书][B] Intelligent Information Processing 12

Z Shi, J Torresen, S Yang - 2024 - books.google.com
92 天前 - … task scheduling, distributed machine learning, and seamless … powerful way for
automated algorithm/solver design. This … provide an adaptive ensemble approach that combines …

Learning the Market: Sentiment-Based Ensemble Trading Agents

A Ye, J Xu, Y Wang, Y Yu, D Yan, R Chen… - arXiv preprint arXiv …, 2024 - arxiv.org
156 天前 - … and deep-reinforcement learning ensemble algorithms for stock trading, and design
a strategy … In particular, the exploration of using deep reinforcement learning to automate

Automated Stock Trading using Reinforcement Learning

IV Devi, B Natarajan, S Prabu, RA Praba… - 2023 International …, 2023 - ieeexplore.ieee.org
226 天前 - … to execute stock market trades automatically. This research work proposes …
ensemble approach that leverages deep reinforcement learning to discover a stock trading strategy

[PDF][PDF] Exploiting Data Science for Measuring the Performance of Technology Stocks

T Sher, A Rehman, D Kim, I Ihsan - Computers, Materials and …, 2023 - cdn.techscience.cn
280 天前 - … , tree-based models, the ARIMA (Auto Regressive Integrated … utilized LSTM and
machine learning ensembles (tree-… comprehensive machine learning (ML) and deep learning (…

Gray-box Adversarial Attack of Deep Reinforcement Learning-based Trading Agents*

F Ataiefard, H Hemmati - … Conference on Machine Learning and …, 2023 - ieeexplore.ieee.org
285 天前 - … Most recent applications of deep reinforcement learning approaches in trading benefit
… 3 automated trading RL agents using our adversary approach: Baseline agent, ensemble