Summary of classification algorithms. حسب Stephen R. Piccolo (8367780)

Summary of feature-selection algorithms. حسب Stephen R. Piccolo (8367780)

Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start حسب Yifan Wang (380120)

"…CAMD often generates and evaluates molecular structures using genetic algorithms. However, genetic algorithms can suffer from slow convergence, and might yield suboptimal solutions. …"

Fine-Tuning a Genetic Algorithm for CAMD: A Screening-Guided Warm Start حسب Yifan Wang (380120)

"…CAMD often generates and evaluates molecular structures using genetic algorithms. However, genetic algorithms can suffer from slow convergence, and might yield suboptimal solutions. …"

Comparison based on hard instances from [79]. حسب Xiang Tian (4369285)

Hierarchical Optimization on large models. حسب Nisha Ann Viswan (20371285)

"…With this the entire optimization is complete. B: Barchart of costs for the four different models, comparing the initial cost with the final cost obtained using three different algorithms from the scipy.minimize library. …"

Diversity and specificity of lipid patterns in basal soil food web resources حسب Jakob Kühn (7288466)

"…In marine environments, multivariate optimization models (Quantitative Fatty Acid Signature Analysis) and Bayesian approaches (source-tracking algorithm) were established to predict the proportion of predator diets using lipids as tracers. …"

Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML حسب Ayush Garg (21090944)

"…The important findings of our studies are as follows: (i) there is no effect of threshold optimization on ranking metrics such as AUC and AUPR, but AUC and AUPR get affected by class-weighting and SMOTTomek; (ii) for ML methods RF and SVM, significant percentage improvement up to 375, 33.33, and 450 over all the data sets can be achieved, respectively, for F1 score, MCC, and balanced accuracy, which are suitable for performance evaluation of imbalanced data sets; (iii) for AutoML libraries AutoGluon-Tabular and H2O AutoML, significant percentage improvement up to 383.33, 37.25, and 533.33 over all the data sets can be achieved, respectively, for F1 score, MCC, and balanced accuracy; (iv) the general pattern of percentage improvement in balanced accuracy is that the percentage improvement increases when the class ratio is systematically decreased from 0.5 to 0.1; in the case of F1 score and MCC, maximum improvement is achieved at the class ratio of 0.3; (v) for both ML and AutoML with balancing, it is observed that any individual class-balancing technique does not outperform all other methods on a significantly higher number of data sets based on F1 score; (vi) the three external balancing techniques combined outperformed the internal balancing methods of the ML and AutoML; (vii) AutoML tools perform as good as the ML models and in some cases perform even better for handling imbalanced classification when applied with imbalance handling techniques. …"

Cell-free DNA coverage and fragmentomic profiles produced under various sequencing protocols حسب Antoine Passemiers (17302912)

Table_1_Data-based modeling for hypoglycemia prediction: Importance, trends, and implications for clinical practice.docx حسب Liyin Zhang (6371999)

"…Data-driven models based on various techniques such as neural networks, autoregressive, ensemble learning, supervised learning, and mathematical formulas have also revealed suggestive features in cases of hypoglycemia prediction.</p>Conclusion<p>In this study, we looked deep into the currently established hypoglycemia prediction models and identified hypoglycemia risk factors from various perspectives, which may provide readers with a better understanding of future trends in this topic.…"

Data Sheet 1_A novel method for power transformer fault diagnosis considering imbalanced data samples.docx حسب Jun Chen (4238)

"…Hyperparameter tuning is achieved through the Bayesian optimization algorithm to identify the model parameter set that maximizes test set accuracy.…"

DataSheet1_Towards Computational Modeling of Human Goal Recognition.pdf حسب Shify Treger (11973125)

"…However, recent experiments by Berkovitz (Berkovitz, The effect of spatial cognition and context on robot movement legibility in human-robot collaboration, 2018) show that in many cases, humans seem to have reached quick (correct) decisions when observing motions which were far from rational (optimal), while optimal motions were slower to be recognized. …"

DataSheet1_Towards Computational Modeling of Human Goal Recognition.pdf حسب Shify Treger (11973125)

"…However, recent experiments by Berkovitz (Berkovitz, The effect of spatial cognition and context on robot movement legibility in human-robot collaboration, 2018) show that in many cases, humans seem to have reached quick (correct) decisions when observing motions which were far from rational (optimal), while optimal motions were slower to be recognized. …"

Supporting data for "clinical-oriented surgical planning based on finite element method and automate-generated surgical templates assisting the spinal surgery" حسب Tianchi Wu (11062323)

"…Remaining algorithm needed was reimplemented from open-source libraries.…"

Collaborative Research: SI2-SSI: ELSI-Infrastructure for Scalable Electronic Structure Theory حسب Volker Blum (3683170)

"…The ELectronic Structure Infrastructure (ELSI) project provides an open-source software interface to facilitate the implementation and optimal use of high-performance solver libraries covering cubic scaling eigensolvers, linear scaling density-matrix-based algorithms, and other reduced scaling methods in between. …"

Collaborative Research: SI2-SSI: ELSI - Infrastructure for Scalable Electronic Structure Theory حسب Volker Blum (3683170)

"…The ELectronic Structure Infrastructure (ELSI) project provides an open-source software interface to facilitate the implementation and optimal use of high-performance solver libraries covering cubic scaling eigensolvers, linear scaling density-matrix-based algorithms, and other reduced scaling methods in between. …"

Data_Sheet_1_Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning and HPC Workloads.PDF حسب Evangelos Georganas (12429885)

"…DL workloads leverage either highly-optimized, yet platform-specific and inflexible kernels from DL libraries, or in the case of novel operators, reference implementations are built via DL framework primitives with underwhelming performance. …"