Search Results - learning with errors (problem OR (problems OR problemys))

PROBLEMY Z NAUCZANIEM FLEKSJI RZECZOWNIKA UCZNIÓW BIAŁORUSKO- I ROSYJSKOJĘZYCZNYCH NA POZIOMIE A by Czerwińska-Trzaskoma, Anna

“…Difficulties in learning Polish as a foreign language by people from the East fall within the scope of interest of glottodidacticians…”
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PROBLEMY FONETYCZNE SŁOWEŃCÓW UCZĄCYCH SIĘ JĘZYKA POLSKIEGO by Wtorkowska, Maria

“…The article shows certain phonetic difficulties encountered by Slovene students during the initial stages of learning Polish…”
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Problemy przyrodniczej edukacji holistycznej w świetle idei zrównoważonego rozwoju by Sandner, Jan

“… to learning about the environment, the primary concept of the author is the attempt to undertake a holistic approach to the problem of natural science education…”
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METHODS OF INTELLIGENT DATA ANALYSIS USING NEURAL NETWORKS IN DIAGNOSIS by Lyfar, Volodymyr, Lyfar, Olena, Zynchenko, Volodymyr

“…The considered methods make it possible to develop the structure of diagnostic systems based on neural networks and implement decision support systems in classification diagnostic problems…”
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IMPROVING PARAMETERS OF V-SUPPORT VECTOR REGRESSION WITH FEATURE SELECTION IN PARALLEL BY USING QUASI-OPPOSITIONAL AND HARRIS HAWKS OPTIMIZATION ALGORITHM by Ismael, Omar Mohammed, Qasim, Omar Saber, Algamal, Zakariya Yahya

“…Numerous real-world problems have been addressed using support vector regression, particularly v-support vector regression (v-SVR…”
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Learning from Errors by Metcalfe, Janet

“…Although error avoidance during learning appears to be the rule in American classrooms, laboratory studies suggest that it may be a counterproductive strategy, at least for neurologically typical students…”
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Generalization of machine learning for problem reduction: a case study on travelling salesman problems by Sun, Yuan, Ernst, Andreas, Li, Xiaodong, Weiner, Jake

“… In this paper, we examine the generalization capability of a machine learning model for problem reduction on the classic travelling salesman problems (TSP…”
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Praktyczna składnia języka polskiego do celów akademickich z uwzględnieniem potrzeb użytkowników z pierwszym językiem ukraińskim by Krawczuk, Ałła

“… The study discusses common errors in case government, sentence structure, and agreement in Polish academic texts written by Ukrainian students…”
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Rapid trial-and-error learning with simulation supports flexible tool use and physical reasoning by Allen, Kelsey R, Smith, Kevin A, Tenenbaum, Joshua B

“… But human beings remain distinctive in their capacity for flexible, creative tool use-using objects in new ways to act on the world, achieve a goal, or solve a problem…”
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Noise resilient quantum learning: Adaptive policy guided error mitigation in quantum reinforcement learning for the traveling salesman problem by Majid, Bisma, Sofi, Shabir Ahmed, Jabeen, Zamrooda

“…Quantum Reinforcement Learning (QRL) has emerged as a promising paradigm for solving combinatorial optimization problems by leveraging quantum parallelism and interference to enhance learning efficiency…”
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Prediction Policy Problems by Kleinberg, Jon, Ludwig, Jens, Mullainathan, Sendhil, Obermeyer, Ziad

“… these “prediction policy problems” requires more than simple regression techniques, since these are tuned to generating unbiased estimates of coefficients rather than minimizing prediction error…”
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Post-Quantum Key Exchange for the TLS Protocol from the Ring Learning with Errors Problem by Bos, Joppe W., Costello, Craig, Naehrig, Michael, Stebila, Douglas

“…) protocol that provide key exchange based on the ring learning with errors (R-LWE) problem, we accompany these cipher suites with a rigorous proof of security…”
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Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems by Cao, Lianghao, O'Leary-Roseberry, Thomas, Jha, Prashant K., Oden, J. Tinsley, Ghattas, Omar

“…We explore using neural operators, or neural network representations of nonlinear maps between function spaces, to accelerate infinite-dimensional Bayesian inverse problems (BIPs…”
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Effects of self-explaining feedback on learning from problem-solving errors by Zhang, Qian, Fiorella, Logan

“…•Modifying the layout of the feedback did not affect learning. We tested two potential ways to help students learn from feedback on their problem-solving errors in physics…”
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Solving a Higgs optimization problem with quantum annealing for machine learning by Mott, Alex, Job, Joshua, Vlimant, Jean-Roch, Lidar, Daniel, Spiropulu, Maria

“… Here, Alex Mott and colleagues implement a 'signal versus background' machine learning optimization problem that can be used in the search for Higgs bosons at the Large Hadron Collider at CERN and at future colliders…”
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Deep Learning for Integrated Origin-Destination Estimation and Traffic Sensor Location Problems by Owais, Mahmoud

“… This article provides a resilient deep learning (DL) architecture combined with a global sensitivity analysis tool to solve O-D estimation and sensor location problems simultaneously…”
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Learning about structural errors in models of complex dynamical systems by Wu, Jin-Long, Levine, Matthew E., Schneider, Tapio, Stuart, Andrew

“… Building on such closure models and correcting them through learning the structural errors can be an effective way of fusing data with domain knowledge…”
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Mitigating the Multicollinearity Problem and Its Machine Learning Approach: A Review by Chan, Jireh Yi-Le, Leow, Steven Mun Hong, Bea, Khean Thye, Cheng, Wai Khuen, Phoong, Seuk Wai, Hong, Zeng-Wei, Chen, Yen-Lin

“… Although this presents opportunities to better model the relationship between predictors and the response variables, this also causes serious problems during data analysis, one of which is the multicollinearity problem…”
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Solving Inverse Problems With Deep Neural Networks - Robustness Included? by Genzel, Martin, Macdonald, Jan, Marz, Maximilian

“…In the past five years, deep learning methods have become state-of-the-art in solving various inverse problems…”
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Using meta‐learning to predict performance metrics in machine learning problems by Carneiro, Davide, Guimarães, Miguel, Carvalho, Mariana, Novais, Paulo

“…Machine learning has been facing significant challenges over the last years, much of which stem from the new characteristics of machine learning problems, such as learning from streaming data…”
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