Results 81 to 90 of about 448,103 (274)

A Practical Incremental Learning Framework For Sparse Entity Extraction [PDF]

, 2018
This work addresses challenges arising from extracting entities from textual data, including the high cost of data annotation, model accuracy, selecting appropriate evaluation criteria, and the overall quality of annotation.
Al-Olimat, Hussein S., Gustafson, Steven, Mackay, Jason, Sheth, Amit, Thirunarayan, Krishnaprasad   +4 more
core   +2 more sources

Incremental Online Learning in High Dimensions [PDF]

Neural Computation, 2005
Locally weighted projection regression (LWPR) is a new algorithm for incremental nonlinear function approximation in high-dimensional spaces with redundant and irrelevant input dimensions. At its core, it employs nonparametric regression with locally linear models.
Vijayakumar, Sethu, D'Souza, Aaron, Schaal, Stefan   +2 more
openaire   +4 more sources

siRNA Delivery via Cross‐Linked Gelatin Microparticles Enables Targeted Modulation of Osteogenic‐Vascular Cross‐Talk: An Advanced Human 3D in Vitro Test System for Therapeutic siRNA

Advanced Healthcare Materials, EarlyView.
Osteogenic‐angiogenic cross‐talk is a vital prerequisite for vascularized bone regeneration. In this study, we investigated the effects of siRNA‐mediated silencing of two inhibitory proteins, Chordin and WWP‐1, via CaP‐NP‐loaded gelatin microparticles in osteogenically differentiated microtissues.
Franziska Mitrach, Jonas Kubat, Stefan Simm, Alexandra H. Springwald, Burak Demir, Anton Liebezeit, Michael C. Hacker, Michaela Schulz‐Siegmund   +7 more
wiley   +1 more source

Efficient Incremental Learning Using Dynamic Correction Vector

IEEE Access, 2020
One major challenge for modern artificial neural networks (ANNs) is that they typically does not handle incremental learning well. In other words, while learning the new features, the performances of existing features usually deteriorate. This phenomenon
Yun Xiang, Yongbiao Miao, Jingyin Chen, Qi Xuan   +3 more
doaj   +1 more source

Taming the Immiscibility of Gold, Iron, and Boron to Craft Chemodegradable Nanoparticles for Multimodal Imaging and Radiotherapy

Advanced Healthcare Materials, EarlyView.
Over half of cancer patients undergo radiotherapy. Laser ablation enabled the synthesis of immiscible Au‐Fe‐B nanoparticles designed as degradable bimodal radiosensitizers for X‐ray radiotherapy (XRT), boron neutron capture therapy (BNCT), and bimodal imaging for X‐ray computed tomography (CT) and magnetic resonance imaging (MRI). These nanosensitizers
Michael Bissoli, Clara M.G. de Faria, Veronica Torresan, Maria Assunta Lacavalla, Mattia Cattelan, Denis Badocco, Paolo Pastore, Pasquina Marzola, Laura Cansolino, Cinzia Ferrari, Ian Postuma, Riccardo Vago, Silva Bortolussi, Antonello E. Spinelli, Daniel Forrer, Vincenzo Amendola   +15 more
wiley   +1 more source

Incremental Prototype Tuning for Class Incremental Learning

, 2022
Class incremental learning(CIL) has attracted much attention, but most existing related works focus on fine-tuning the entire representation model, which inevitably results in much catastrophic forgetting. In the contrast, with a semantic-rich pre-trained representation model, parameter-additional-tuning (PAT) only changes very few parameters to learn ...
Deng, Jieren, Hu, Jianhua, Zhang, Haojian, Wang, Yunkuan   +3 more
openaire   +2 more sources

Ferroelectric Quantum Dots for Retinomorphic In‐Sensor Computing

Advanced Materials, EarlyView.
This work has provided a protocol for fabricating retinomorphic phototransistors by integrating ferroelectric ligands with quantum dots. The resulting device combines ferroelectricity, optical responsiveness, and low‐power operation to enable adaptive signal amplification and high recognition accuracy under low‐light conditions, while supporting ...
Tingyu Long, Huanyu Zhou, Jaewan Ko, Hongwei Tan, Jaemin Lim, Yanfei Zhao, Daehan Kang, Eojin Yoon, Gyeong‐Tak Go, Somin Kim, Seung‐Woo Lee, Chan‐Yul Park, Hyojun Choi, Hyeran Kim, Hyung Joong Yun, Sung Hyuk Park, Kwan Sik Park, Jeong Woo Park, Mungeun Kim, Yong Soo Cho, Ho Won Jang, Wenqiang Yang, Min Hyuk Park, Wan Ki Bae, Sebastiaan van Dijken, Joona Bang, Tae‐Woo Lee   +26 more
wiley   +1 more source

Robust and Adaptive Incremental Learning for Varying Feature Space

IEEE Access
Real-world multiple or streaming tabular datasets, such as electronic health records from various sources and internet-of-things data generated from different devices, typically exhibit varied feature spaces depending on the datasets. Batch-mode learning
Cheol Ho Kim, Jung-Hoon Lee, Hawon Shin, Ock Kee Baek   +3 more
doaj   +1 more source

Learning Automata Based Incremental Learning Method for Deep Neural Networks

IEEE Access, 2019
Deep learning methods have got fantastic performance on lots of large-scale datasets for machine learning tasks, such as visual recognition and neural language processing. Most of the progress on deep learning in recent years lied on supervised learning,
Haonan Guo, Shilin Wang, Jianxun Fan, Shenghong Li   +3 more
doaj   +1 more source

Transistor‐Level Activation Functions via Two‐Gate Designs: From Analog Sigmoid and Gaussian Control to Real‐Time Hardware Demonstrations

Advanced Materials, EarlyView.
Screen gate‐based transistors are presented, enabling tunable analog sigmoid and Gaussian activations. The SA‐transistor improves MRI classification accuracy, while the GA‐transistor supports precise Gaussian kernel tuning for forecasting. Both functions are implemented in a single device, offering compact, energy‐efficient analog AI processing ...
Junhyung Cho, Youngmin Han, Won Woo Lee, Youngwoo Yoo, Kannan Udaya Mohanan, Chang‐Hyun Kim, Junhwan Choi, Young‐Joon Kim, Wonjun Shin, Hocheon Yoo   +9 more
wiley   +1 more source