Search Results - computer learning AND pattern recognition::automated problems solving~

A Bi-Projection Neural Network for Solving Constrained Quadratic Optimization Problems by Xia, Youshen, Wang, Jun

“…In this paper, a bi-projection neural network for solving a class of constrained quadratic optimization problems is proposed…”
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A Recurrent Neural Network for Solving Bilevel Linear Programming Problem by He, Xing, Li, Chuandong, Huang, Tingwen, Li, Chaojie, Huang, Junjian

“…) modeled by means of a differential inclusion is proposed for solving the bilevel linear programming problem (BLPP…”
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Five points to check when comparing visual perception in humans and machines by Funke, Christina M., Borowski, Judy, Stosio, Karolina, Brendel, Wieland, Wallis, Thomas S. A., Bethge, Matthias

“…With the rise of machines to human-level performance in complex recognition tasks, a growing amount of work is directed toward comparing information processing in humans and machines…”
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Comparing machines and humans on a visual categorization test by Fleuret, François, Li, Ting, Dubout, Charles, Wampler, Emma K, Yantis, Steven, Geman, Donald

“…Automated scene interpretation has benefited from advances in machine learning, and restricted tasks, such as face detection, have been solved with sufficient accuracy for restricted settings…”
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Does a language model “understand” high school math? A survey of deep learning based word problem solvers by Sundaram, Sowmya S., Gurajada, Sairam, Padmanabhan, Deepak, Abraham, Savitha Sam, Fisichella, Marco

“…From the latter half of the last decade, there has been a growing interest in developing algorithms for automatically solving mathematical word problems (MWP…”
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Task-Driven Dictionary Learning by Mairal, J., Bach, F., Ponce, J.

“… In this context, learning the dictionary amounts to solving a large-scale matrix factorization problem, which can be done efficiently with classical optimization tools…”
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KGE-UNIT: toward the unification of molecular interactions prediction based on knowledge graph and multi-task learning on drug discovery by Zhang, Chengcheng, Zang, Tianyi, Zhao, Tianyi

“…) and multi-task learning, for simultaneous prediction of drug–target interactions (DTIs) and drug–drug interactions (DDIs) and enhancing the performance of each task, even when data availability is limited…”
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Solving Nonlinear Equality Constrained Multiobjective Optimization Problems Using Neural Networks by Mestari, Mohammed, Benzirar, Mohammed, Saber, Nadia, Khouil, Meryem

“…This paper develops a neural network architecture and a new processing method for solving in real time, the nonlinear equality constrained multiobjective optimization problem (NECMOP…”
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Location-Aware and Regularization-Adaptive Correlation Filters for Robust Visual Tracking by Liu, Risheng, Chen, Qianru, Yao, Yuansheng, Fan, Xin, Luo, Zhongxuan

“…Correlation filter (CF) has recently been widely used for visual tracking. The estimation of the search window and the filter-learning strategies is the key component of the CF trackers…”
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An Interactive Approach to Solving Correspondence Problems by Jegelka, Stefanie, Kapoor, Ashish, Horvitz, Eric

“…Finding correspondences among objects in different images is a critical problem in computer vision…”
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Learning Graph Matching by Caetano, T.S., McAuley, J.J., Li Cheng, Le, Q.V., Smola, A.J.

“…As a fundamental problem in pattern recognition, graph matching has applications in a variety of fields, from computer vision to computational biology…”
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Solving Pseudomonotone Variational Inequalities and Pseudoconvex Optimization Problems Using the Projection Neural Network by Hu, Xiaolin, Wang, Jun

“…In recent years, a recurrent neural network called projection neural network was proposed for solving monotone variational inequalities and related convex optimization problems…”
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Training a support vector machine in the primal by Chapelle, Olivier

“…Most literature on support vector machines (SVMs) concentrates on the dual optimization problem…”
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Distributed Medical Image Analysis and Diagnosis through Crowd-Sourced Games: A Malaria Case Study by Mavandadi, Sam, Dimitrov, Stoyan, Feng, Steve, Yu, Frank, Sikora, Uzair, Yaglidere, Oguzhan, Padmanabhan, Swati, Nielsen, Karin, Ozcan, Aydogan

“…In this work we investigate whether the innate visual recognition and learning capabilities of untrained humans can be used in conducting reliable microscopic analysis of biomedical samples toward diagnosis…”
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Discrete-Time Neural Network for Fast Solving Large Linear L1 Estimation Problems and Its Application to Image Restoration by Xia, Youshen, Sun, Changyin, Zheng, Wei Xing

“…There is growing interest in solving linear L1 estimation problems for sparsity of the solution and robustness against non-Gaussian noise…”
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A Novel Recurrent Neural Network for Solving Nonlinear Optimization Problems With Inequality Constraints by Xia, Youshen, Feng, Gang, Wang, Jun

“…This paper presents a novel recurrent neural network for solving nonlinear optimization problems with inequality constraints…”
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Multiple Kernel Learning for Visual Object Recognition: A Review by Bucak, Serhat S., Rong Jin, Jain, Anil K.

“… We review the state-of-the-art for MKL, including different formulations and algorithms for solving the related optimization problems, with the focus on their applications to object recognition…”
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A new touchscreen test of pattern separation: effect of hippocampal lesions by McTighe, Stephanie M, Mar, Adam C, Romberg, Carola, Bussey, Timothy J, Saksida, Lisa M

“… In this study, we develop and test a new automated touchscreen-based method for studying pattern separation in rodents…”
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A Minimum Resource Neural Network Framework for Solving Multiconstraint Shortest Path Problems by Zhang, Junying, Zhao, Xiaoxue, He, Xiaotao

“…) framework is proposed for solving a wide range of single-source shortest path (SP) problems for various graph types…”
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Solving the Assignment Problem Using Continuous-Time and Discrete-Time Improved Dual Networks by Hu, Xiaolin, Wang, Jun

“…) for solving the assignment problem. Compared with most assignment networks in the literature, the two versions of IDNNs are advantageous in circuit implementation due to their simple structures…”
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