Table_1_A scheduling route planning algorithm based on the dynamic genetic algorithm with ant colony binary iterative optimization for unmanned aerial vehicle spraying in multiple... by Yangyang Liu (807797)

Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data by Fei Xue (24567)

“…Specifically, the proposed method obtains the optimal DTR via integrating estimations of decision rules at multiple stages into a single multicategory classification algorithm without imposing additional constraints, which is also more computationally efficient and robust. …”

Analysis and design of algorithms for the manufacturing process of integrated circuits by Sonia Fleytas (16856403)

“…The (approximate) solution proposals of state-of-the-art methods include rule-based approaches, genetic algorithms, and reinforcement learning. …”

Contextual Dynamic Pricing with Strategic Buyers by Pangpang Liu (18886419)

“…The seller does not observe the buyer’s true feature, but a manipulated feature according to buyers’ strategic behavior. …”

Predictive Analysis of Mushroom Toxicity Based Exclusively on Their Natural Habitat. by Enrico Bertozzi (22461709)

“…<br>The consistency of the results across different kernels demonstrates that the information contained in the habitat, by itself, leads to a very simple optimal decision rule (mostly the prediction of the most frequent class per habitat), which cannot be improved solely by model adjustments. …”

Supplementary Material 8 by Nishitha R Kumar (19750617)

“…</li><li><b>Naïve bayes (NB): </b> A probabilistic classifier based on Bayes' theorem, suitable for predicting resistance phenotypes based on genomic features.</li><li><b>Linear discriminant Analysis (LDA) is a statistica</b>l approach that maximizes class separability. …”

Objective performance of fully-automated SLAVV software. by Samuel A. Mihelic (11539996)

Adaptive Inference for Change Points in High-Dimensional Data by Yangfan Zhang (6451946)

“…On the estimation front, we obtain the convergence rate of the maximizer of our test statistic standardized by sample size when there is one change-point in mean and <i>q</i> = 2, and propose to combine our tests with a wild binary segmentation algorithm to estimate the change-point number and locations when there are multiple change-points. …”