Domain-adaptive active learning for cost-effective virtual metrology modeling

2022 ◽  
Vol 135 ◽  
pp. 103572
Author(s):  
Jaewoong Shim ◽  
Seokho Kang
Keyword(s):  
Active Learning ◽  
Cost Effective ◽  
Virtual Metrology

Joint Semi-supervised and Active Learning for Segmentation of Gigapixel Pathology Images with Cost-Effective Labeling

2021 ◽  
Author(s):  
Zhengfeng Lai ◽  
Chao Wang ◽  
Luca Cerny Oliveira ◽  
Brittany N. Dugger ◽  
Sen-Ching Cheung ◽  
...  
Keyword(s):  
Active Learning ◽  
Cost Effective

scholarly journals LEXSSA KIT IMPROVE READING SKILLS FOR STUDENT WITH DISABILITIES

2021 ◽  
Vol 3 (8) ◽  
pp. 149-166
Author(s):  
Norleena Gutasan ◽  
Rojiah Saiwah Karim ◽  
Zoriffah Mohd Kudin ◽  
Nor Jannah Hassan
Keyword(s):  
Learning Disabilities ◽  
Active Learning ◽  
Reading Skills ◽  
Cost Effective ◽  
Survey Method ◽  
Slow Learner ◽  
Students With Learning Disabilities ◽  
Learning Aids ◽  
Students With Autism ◽  
Adaptation Processes

The LEXSSA Kit (More Effective Xtra Fun Suitable for Student Levels) is produced for Students with Learning Disabilities. The aim of this research is to help students with Learning Disabilities such as students with Autism, Dyslexia, Slow Learner, Down Syndrome, and Attention Deficit Hyperactive Disorder (ADHD) improve their reading skills. This study was conducted to observe the perception of Students with Learning Disabilities of using LEXSSA Kit as learning aids that can encourage active learning and improve the mastery of reading. The design of this research has used a survey method and presented in the form of descriptive statistics (frequency and percentage). Meanwhile, the LEXSSA Kit was produced through four adaptation processes using the PDCA Model and was implemented for Students with Learning Disabilities in the district of Tuaran, Kudat, and Kota Belud. Preliminary findings found that Students with Learning Disabilities unable to read simple syllables, words, phrases, and sentences without the help of a teacher. The result of the intervention using the LEXSSA Kit shows that Students with Learning Disabilities can read simple syllables and words independently. The finding of the assessment phase shows that 95 percent of Students with Learning Disabilities can read syllables and words using the LEXSSA Kit. The implication of this study proves that the LEXSSA Kit can help improve Students with Learning Disabilities' reading skills. It is easy to use, interactive, fun, engaging, encourages active learning among Students with Learning Disabilities, and cost-effective for teachers to use.

scholarly journals Employment of Active Learning at HEIs in Bangladesh to Improve Education Quality

2016 ◽  
Vol 9 (10) ◽  
pp. 47 ◽  
Author(s):  
Faieza Chowdhury
Keyword(s):  
Active Learning ◽  
Learning Strategies ◽  
Resource Constraints ◽  
Implementation Process ◽  
Cost Effective ◽  
Education Quality ◽  
Quality Of Education ◽  
Multiple Sources ◽  
Active Learning Strategies

<p class="apa">In recent years, education quality and quality assessment have received a great deal of attention at Higher Education Institutions (HEIs) in Bangladesh. Most of the HEIs in Bangladesh face severe resource constraints and find it difficult to improve education quality by improving inputs, such as better infrastructure and modernized classroom facilities. Thus, in response to the present government’s demand to improve the quality of education at HEIs in Bangladesh, it is imperative to formulate plans that are more cost-effective. According to some previous studies, the quality of education depends largely on the teaching-learning process. These studies affirm that, with limited resources at hand, the employment of active learning in the classroom is one of the most effective ways to improve education quality. To conduct this qualitative research, we utilized multiple sources of data, including semi-structured and in-depth interviews, descriptive observations and self-administered questionnaires. This paper aims to explore three related issues: What are the various active learning strategies that can be employed by the instructors at HEIs in Bangladesh? What are the potential factors that can hinder the implementation process? Finally, what recommendations can be provided on how to successfully implement active learning strategies in the classroom? The findings suggest that a lack of teacher training and student prior experience in an active learning environment, large class sizes, excessive curriculum loads and students’ academic backgrounds are some common factors that can hinder the implementation of active learning in Bangladesh. The findings of this study can be instrumental for HEIs in Bangladesh as they aspire to improve their education quality.</p>

Cost Effective Multi-label Active Learning via Querying Subexamples

2018 ◽  
Author(s):  
Xia Chen ◽  
Guoxian Yu ◽  
Carlotta Domeniconi ◽  
Jun Wang ◽  
Zhao Li ◽  
...  
Keyword(s):  
Active Learning ◽  
Cost Effective

scholarly journals CMAL: Cost-effective Multi-label Active Learning by Querying Subexamples

2020 ◽  
pp. 1-1
Author(s):  
Guoxian Yu ◽  
Xia Chen ◽  
Carlotta Domeniconi ◽  
Jun Wang ◽  
Zhao Li ◽  
...  
Keyword(s):  
Active Learning ◽  
Cost Effective

Cost-Effective Vehicle Type Recognition in Surveillance Images With Deep Active Learning and Web Data

2020 ◽  
Vol 21 (1) ◽  
pp. 79-86 ◽  
Author(s):  
Yue Huang ◽  
Zhenwei Liu ◽  
Minghui Jiang ◽  
Xian Yu ◽  
Xinghao Ding
Keyword(s):  
Active Learning ◽  
Cost Effective ◽  
Web Data ◽  
Vehicle Type

scholarly journals Active learning with point supervision for cost-effective panicle detection in cereal crops

Plant Methods ◽  
2020 ◽  
Vol 16 (1) ◽  
Author(s):  
Akshay L. Chandra ◽  
Sai Vikas Desai ◽  
Vineeth N. Balasubramanian ◽  
Seishi Ninomiya ◽  
Wei Guo
Keyword(s):  
Active Learning ◽  
Cost Effective ◽  
Cereal Crops

scholarly journals Actively Searching: Inverse Design of Novel Molecules with Simultaneously Optimized Properties

2021 ◽  
Author(s):  
Nicolae C. Iovanac ◽  
Robert MacKnight ◽  
Brett Savoie
Keyword(s):  
Active Learning ◽  
Quantum Chemistry ◽  
Chemical Space ◽  
Cost Effective ◽  
Generative Models ◽  
Learning Approach ◽  
The Novel ◽  
Practical Applications ◽  
Chemical Models ◽  
And Shifts

<p>Combining quantum chemistry characterizations with generative machine learning models has the potential to accelerate molecular searches in chemical space. In this paradigm, quantum chemistry acts as a relatively cost-effective oracle for evaluating the properties of particular molecules while generative models provide a means of sampling chemical space based on learned structure-function relationships. For practical applications, multiple potentially orthogonal properties must be optimized in tandem during a discovery workflow. This carries additional difficulties associated with specificity of the targets and the ability for the model to reconcile all properties simultaneously. Here we demonstrate an active learning approach to improve the performance of multi-target generative chemical models. We first demonstrate the effectiveness of a set of baseline models trained on single property prediction tasks in generating novel compounds with various property targets, including both interpolative and extrapolative generation scenarios. For property ranges where accurate targeting proves difficult, the novel compounds suggested by the model are characterized using quantum chemistry to obtain the true values, and these new molecules closest to expressing the desired properties are fed back into the generative model for additional training. This gradually improves the generative models’ understanding of unknown areas of chemical space and shifts the distribution of generated compounds towards the targeted values. We then demonstrate the effectiveness of this active learning approach in generating compounds with multiple chemical constraints, including vertical ionization potential, electron affinity, and dipole moment targets, and validate the results at the B97X-D3/def2-TZVP level. This method requires no modifications to extant generative approaches, but rather utilizes their inherent generative and predictive aspects for self-refinement, and can be applied to situations where any number of properties with varying degrees of correlation must be optimized simultaneously.</p>

scholarly journals Cost-Effective Active Learning from Diverse Labelers

2017 ◽  
Author(s):  
Sheng-Jun Huang ◽  
Jia-Lve Chen ◽  
Xin Mu ◽  
Zhi-Hua Zhou
Keyword(s):  
Cost Effectiveness ◽  
Active Learning ◽  
Low Cost ◽  
Selection Criterion ◽  
Ground Truth ◽  
Cost Effective ◽  
Classification Model ◽  
Data Sets ◽  
Active Selection ◽  
The Cost

In traditional active learning, there is only one labeler that always returns the ground truth of queried labels. However, in many applications, multiple labelers are available to offer diverse qualities of labeling with different costs. In this paper, we perform active selection on both instances and labelers, aiming to improve the classification model most with the lowest cost. While the cost of a labeler is proportional to its overall labeling quality, we also observe that different labelers usually have diverse expertise, and thus it is likely that labelers with a low overall quality can provide accurate labels on some specific instances. Based on this fact, we propose a novel active selection criterion to evaluate the cost-effectiveness of instance-labeler pairs, which ensures that the selected instance is helpful for improving the classification model, and meanwhile the selected labeler can provide an accurate label for the instance with a relative low cost. Experiments on both UCI and real crowdsourcing data sets demonstrate the superiority of our proposed approach on selecting cost-effective queries.

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