Region selection by active learning algorithms. by Samuel A. Danziger (260043)

Certainty-based Active Learning algorithm in a pool-based scenario. by Wenjing Han (3120129)

“…<p>Certainty-based Active Learning algorithm in a pool-based scenario.</p>…”

Certainty-based Active Learning algorithm in a stream-based scenario. by Wenjing Han (3120129)

“…<p>Certainty-based Active Learning algorithm in a stream-based scenario.</p>…”

muTOX-AL-main.zip by Huiyan Xu (19231228)

Subjects:

Supporting data for "Structural Identification and Model Updating Based on Active Learning Kriging Approach and Bayesian Inference" by Ye Yuan (9071153)

Subjects:

Data Sheet 1_A combined model of shoot phosphorus uptake based on sparse data and active learning algorithm.pdf by Tianli Wang (1438498)

Supplementary Material by Srihari Kastuar (19351834)

“…The Supplementary Material contains detailed about the active learning algorithm, including model and feature selection. …”

Performance comparison with PC and GIES on DREAM4 data sets. by Hyunghoon Cho (633643)

“…<p>We evaluated the final prediction accuracy of our active learning algorithm in identifying edges in the undirected skeleton of the ground truth network. …”

Reconstructing Causal Biological Networks through Active Learning by Hyunghoon Cho (633643)

“…In this work, we present an efficient, information-theoretic active learning algorithm for Gaussian Bayesian networks (GBNs), which serve as important models for gene regulatory networks. …”

The utility of machine learning and text mining to expedite systematic reviews in injury recovery research by Melita Giummarra (4580353)

“…Abstrackr is one such tool, hosted at Brown University, USA, that is a free web-based platform that uses an active learning algorithm to generate predictions of relevance from the words in citation titles, abstracts and keywords (using unigrams and bigrams). …”

Dimensional Control over Metal Halide Perovskite Crystallization Guided by Active Learning by Zhi Li (72309)

“…To efficiently acquire the data needed to construct a machine learning (ML) model of the reaction conditions where the 1D and 2D phases are formed, data acquisition was guided by a diverse-mini-batch-sampling active learning algorithm, using prediction confidence as a stopping criterion. …”

Dimensional Control over Metal Halide Perovskite Crystallization Guided by Active Learning by Zhi Li (72309)

“…To efficiently acquire the data needed to construct a machine learning (ML) model of the reaction conditions where the 1D and 2D phases are formed, data acquisition was guided by a diverse-mini-batch-sampling active learning algorithm, using prediction confidence as a stopping criterion. …”

Dimensional Control over Metal Halide Perovskite Crystallization Guided by Active Learning by Zhi Li (72309)

“…To efficiently acquire the data needed to construct a machine learning (ML) model of the reaction conditions where the 1D and 2D phases are formed, data acquisition was guided by a diverse-mini-batch-sampling active learning algorithm, using prediction confidence as a stopping criterion. …”

Data Sheet 2_Active learning with human heuristics: an algorithm robust to labeling bias.pdf by Sriram Ravichandran (14456604)

“…How does modeling the oracle as a human heuristic affect the performance of active learning algorithms? If there is a drop in performance, can one design active learning algorithms robust to labeling bias? …”

Data Sheet 1_Active learning with human heuristics: an algorithm robust to labeling bias.zip by Sriram Ravichandran (14456604)

“…How does modeling the oracle as a human heuristic affect the performance of active learning algorithms? If there is a drop in performance, can one design active learning algorithms robust to labeling bias? …”

Dedupe’s active learning process. by Sarah Tahamont (11407773)

“…When a pool of ground-truth information is unavailable, researchers can use “active learning” algorithms for linking, which ask the user to provide ground-truth information for select candidate pairs. …”

Performance for different sample sizes. by Sarah Tahamont (11407773)

“…When a pool of ground-truth information is unavailable, researchers can use “active learning” algorithms for linking, which ask the user to provide ground-truth information for select candidate pairs. …”

Polyanion sodium cathode materials dataset by Martin Hoffmann Petersen (13626778)

“…<p dir="ltr">We have created a polyanion sodium cathode materials dataset that includes optimizations of structures to the lowest energy, ab initio molecular dynamics simulations trajectories sampled at 1000K, and structures generated from ML-driven molecular dynamics simulation at 1000K using active learning algorithms. The dataset consists of structures sampled from four sodium ion polyanionic cathode materials NaTMPO₄(olivine) ,NaTMPO₄(maricite), Na₂TMSiO₄ and Na_2.56TM_1.72(SO₄)₃ , along with various structures incorporating doping of transition metal ions (TM). …”