Advanced mathematical methods / by Ostaszewski, Adam, author 656193

Query lower bounds for log-concave sampling by Chewi, Sinho, de Dios Pont, Jaume, Li, Jerry, Lu, Chen, Narayanan, Shyam

“…Our proofs rely upon (1) a multiscale construction inspired by work on the Kakeya conjecture in geometric measure theory, and (2) a novel reduction that demonstrates that block Krylov algorithms are optimal for this problem, as well as connections to lower bound techniques based on Wishart matrices developed in the matrix-vector query literature.…”
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Lifting Directional Fields to Minimal Sections by Palmer, David, Chern, Albert, Solomon, Justin

“…Directional fields, including unit vector, line, and cross fields, are essential tools in the geometry processing toolkit. …”
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Global optimization: a machine learning approach by Bertsimas, Dimitris, Margaritis, Georgios

“…We provide extensions to this approach, by (i) approximating the original problem using other MIO-representable ML models besides decision trees, such as gradient boosted trees, multi layer perceptrons and suport vector machines (ii) proposing adaptive sampling procedures for more accurate ML-based constraint approximations, (iii) utilizing robust optimization to account for the uncertainty of the sample-dependent training of the ML models, (iv) leveraging a family of relaxations to address the infeasibilities of the final MIO approximation. …”
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A sparse kernel algorithm for online time series data prediction by Fan, Haijin, Song, Qing

“…To make the kernel methods suitable for online learning, we propose a sparsification method based on the Hessian matrix of the system loss function to continuously examine the significance of the new training sample in order to select a sparse dictionary (support vector set). The Hessian matrix is equivalent to the correlation matrix of sample inputs in the kernel weight updating using the recursive least square (RLS) algorithm. …”
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Using AI / machine learning to solve real world problems by Lok, Ignatius Zhengrong

“…Different supervised machine learning models including Random Forests, Support Vector Machines, XGBoost, LGBM and Ensemble learning methods are then applied to predict the restaurant revenue, allowing a better decision to be made when opening new restaurants and to increase the effectiveness of investments in new restaurant sites.…”
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How vulnerable is innovation-based remote state estimation: fundamental limits under linear attacks by Liu, Hanxiao, Ni, Yuqing, Xie, Lihua, Johansson, Karl Henrik

“…The maximal performance degradations that an adversary can achieve with any linear first-order false-data injection attack under strict stealthiness for vector systems and ε-stealthiness for scalar systems are characterized. …”
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Deep learning for fabric defect detection by Nangia, Saniya

“…Their confidence scores are adjusted to reflect single or dual votes for predicted bounding boxes. Finally, a Support Vector Machine Regression meta-model is chosen to combine the predictions of both models, attaining a higher average precision and average recall than baseline models and other ensemble methods. …”
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Study of face detection and tracking by Khew, Zong Jie.

“…The methods that will be discussed are namely, automatic human face detection and recognition under non-uniform illumination face detection using discriminating feature analysis and Support Vector Machine (SVM), face tracking in Model-based Coding (MBC), multi-expert approach for face detection and multi-view face and eye detection using discriminant features. …”
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Ontology alignment for knowledge representation and integration : applications to biomedical text by Chua, Watson Wei Khong.

“…This technique selects only concept pairs with high similarities for comparison, based on the Vector Space Model.…”
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Emotional states classification from brain signals by Lee, Vinson Bing Jun.

“…We will observe the performances of the Kernel Extreme Learning Machine (ELM) compared to Support Vector Machine (SVM), and two other variants being – polynomial kernel with standard deviation, and polynomial kernel with maximum deviation. …”
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Monitoring the efficacy of magnetofection with Au-Fe3O4 nanoparticles by Sim, Stanley Siong Wei

“…However, there are not many efficient gene or drug delivery vectors around in the industry for such application. …”
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Animal flocking behaviours in game development using FAME by Choy, Jin Xiang

“…This library enables the user to easily create flocks, obstacles, and vector fields with configurable properties, thereby decreasing production time and cost. …”
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Machine learning attack on hardware implementation of one-way function by Lauw, Andri Renardi

“…It turns out that Support Vector Machine (SVM) is the most effective learning algorithm among all the six algorithms tested (Naïve Bayes, Decision Tree, Logistic Regression, Gradient Boosting, Neural Network, and SVM) to attack the PUF in terms of effectiveness and efficiency, which has prediction accuracy of 99% with relatively small amount of training data. …”
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Discrete wavelet transform coefficients for emotion recognition from EEG signals by Ser, Wee, Huang, Guang-Bin, Yohanes, Rendi E. J.

“…Two classifiers were used: Extreme Learning Machine (ELM) and Support Vector Machine (SVM). Experimental results confirmed that the proposed DWT coefficients method showed improvement of performance compared to previous methods.…”
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Efficient visual search for objects in videos by Sivic, J, Zisserman, A

“…These descriptors enable recognition to proceed successfully despite changes in viewpoint, illumination, and partial occlusion. Vector quantizing these region descriptors provides a visual analogy of a word, which we term a ldquovisual word.rdquo Efficient retrieval is then achieved by employing methods from statistical text retrieval, including inverted file systems, and text and document frequency weightings. …”

Presence of host-seeking Ixodes ricinus and their infection with Borrelia burgdorferi sensu lato in the Northern Apennines, Italy by Ragagli, C, Mannelli, A, Ambrogi, C, Bisanzio, D, Ceballos, LA, Grego, E, Martello, E, Selmi, M, Tomassone, L

“…Based upon the comparison with the results of previous studies at the same location, these research findings suggest the recent invasion of the study area by the tick vector and the agents of Lyme borreliosis.…”

Strong immune responses and robust protection following a novel protein in adjuvant tuberculosis vaccine candidate by Korompis, M, De Voss, CJ, Li, S, Richard, A, Almujri, SS, Ateere, A, Frank, G, Lemoine, C, McShane, H, Stylianou, E

“…Heterologous vaccination strategies were also explored by combining intranasal ChAdOx1.PPE15 viral vector, with intramuscular PPE15-LMQ resulting in improved protection compared to individual vaccines. …”

Narrowing the gap between machine learning scoring functions and free energy perturbation using augmented data by Valsson, Í, Warren, MT, Deane, CM, Magarkar, A, Morris, GM, Biggin, PC

“…Here, we address these issues by first introducing a novel attention-based graph neural network model called AEV-PLIG (atomic environment vector–protein ligand interaction graph). Second, we introduce a new and more realistic out-of-distribution test set called the OOD Test. …”

Population genetic evidence for species A, B, C and D of the Anopheles dirus complex in Thailand and enzyme electromorphs for their identification by Green, Christopher A., Munstermann, Leonard E., Tan, S. G., Panyim, Sakol, Baiman, Visut

“…An example is given of the use of enzyme electromorphs as a means of vector identification during a malaria entomological field study involving a mixture of An.dirus species A and D. …”