Fish classification and deep learning by Zhang, Dawei

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Transfer learning on UR robots by Yu, Xiwei

“…As neural networks and deep learning develop, researchers are continually exploring the capabilities and potential of using data-driven methods to control robots. …”
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Descriptor learning for efficient retrieval by Philbin, J, Isard, M, Sivic, J, Zisserman, A

“…Scalable, stochastic gradient methods are used for the optimization.</p> <br> <p>For the case of particular object retrieval, we demonstrate impressive gains in performance on a ground truth dataset: our learnt 32-D descriptor without spatial re-ranking outperforms a baseline method using 128-D SIFT descriptors with spatial re-ranking.…”

Online learning for search and classification by Nguyen, Thanh Tam

“…(i) Feature selection: we have investigated a number of newly supervised term weighting methods to improve the performance of text classification; (ii) Online classification: we have proposed several online learning algorithms that can be used for topic classification; (iii) Two-view online learning: we have proposed a two-view online learning algorithm, which can work on two-view datasets; (iv) Online learning-to-rank: for search engine, we have proposed an online learning-to-rank algorithm, which was to learn a scoring function to re-rank the search result.…”
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Optimization strategies for federated learning by Zhang, Tinghao

“…We achieve this through a deep reinforcement learning-based scheduling strategy and an optimized bandwidth allocation method, enabling FL to achieve target accuracy with reduced system costs. …”
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Reinforcement learning for robot assembly by Vuong Quoc Nghia

“…Finally, this thesis examines methods to narrow the reality gap - the fundamental problem in sim-to-real reinforcement learning. …”
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Vision language representation learning by Yang, Xiaofeng

“…Despite its significance, learning effective vision language representation remains challenging due to several reasons. …”
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Unsupervised generative variational continual learning by Liu, Guimeng

“…Recent research in continual learning generally incorporates two of these methods to obtain better performance. …”
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iTD3-CLN: learn to navigate in dynamic scene through Deep Reinforcement Learning by Jiang, Haoge, Esfahani, Mahdi Abolfazli, Wu, Keyu, Wan, Kong-wah, Heng, Kuan-kian, Wang, Han, Jiang, Xudong

“…In contrast to the conventional methods such as the DWA, our approach is found superior in the following ways: no need for prior knowledge of the environment and metric map, lower reliance on an accurate sensor, learning emergent behavior in dynamic scene that is intuitive, and more remarkably, able to transfer to the real robot without further fine-tuning. …”
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MAS.714J / STS.445J Technologies for Creative Learning, Fall 2004 by Resnick, Mitchel

Subjects: “…learning…”
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Refining learning models in grammatical inference by Wang, Xiangrui

“…We introduce the use of recurrent neural networks (RNNs) and present a pruning learning method to avoid the exponential space costs. …”
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16.901 Computational Methods in Aerospace Engineering, Spring 2003 by Darmofal, David L.

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15.053 Optimization Methods in Management Science, Spring 2007 by Mamani, Hamed, Orlin, James, Metzger, Michael, Narayanaswamy, Murali

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16.901 Computational Methods in Aerospace Engineering, Spring 2005 by Darmofal, David

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Explore anomaly detection and localization methods for medical imaging data by Yu, Tianze

“…Motivated by this, we introduce Contrastive Learning guided GAN (CLGAN), which leverages unlabeled mixed data and contrastive learning to guide the generation process. …”
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Handbook of Research on Deep Learning Techniques for Cloud-Based Industrial IoT / by Swarnalatha, P. (Purushotham), 1977-, editor 656271, Prabu, S., 1981-, editor 656272, IGI Global (Online service) 631983

“…"Deep Learning Techniques for Cloud-Based Industrial IoT aims to demonstrate how computer scientists and engineers of today might employ artificial intelligence in practical applications with the emerging cloud and IoT technologies. …”
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Data-driven methods to predict the stability metrics of catalytic nanoparticles by Prabhu, Asmee M., Choksi, Tej S.

“…In this review we discuss the recent advances in data-driven methods to predict stability metrics of nanoparticles.…”
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Incremental learning technologies for semantic segmentation by Yang, Yizhuo

“…In addition, other incremental learning technologies - knowledge distillation, replay and parameter freezing are also applied to the proposed method to further assist the model in overcoming catastrophic forgetting. …”
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ACDC: online unsupervised cross-domain adaptation by de Carvalho, Marcus, Pratama, Mahardhika, Zhang, Jie, Yee, Edward Yapp Kien

“…Our experimental results under the prequential test-then-train protocol indicate an improvement in target accuracy over the baseline methods, achieving more than a 10% increase in some cases.…”
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Anomaly detection in multivariate time series using ensemble method by Liu, Yanling

“…To improve the above-mentioned anomaly detection limitation of matrix profile, we propose and demonstrate two methods, the matrix profile with autoencoder method and the boosting method. …”
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