Results 51 to 60 of about 1,734,839 (338)
Learning with three factors: modulating Hebbian plasticity with errors
Current Opinion in Neurobiology, 2017 Synaptic plasticity is a central theme in neuroscience. A framework of three-factor learning rules provides a powerful abstraction, helping to navigate through the abundance of models of synaptic plasticity. It is well-known that the dopamine modulation of learning is related to reward, but theoretical models predict other functional roles of the ...
Łukasz Kuśmierz +2 more
openaire +2 more sources
Deep supervised learning using local errors [PDF]
, 2017 Error backpropagation is a highly effective mechanism for learning high-quality hierarchical features in deep networks. Updating the features or weights in one layer, however, requires waiting for the propagation of error signals from higher layers ...
Cauwenberghs, Gert +2 more
core +2 more sources
Molecular Oncology, EarlyView.Clinical trials on PARP inhibitors in urothelial carcinoma (UC) showed limited efficacy and a lack of predictive biomarkers. We propose SLFN5, SLFN11, and OAS1 as UC‐specific response predictors. We suggest Talazoparib as the better PARP inhibitor for UC than Olaparib.
Jutta Schmitz +15 more
wiley +1 more source
NEWMAN ERROR ANALYSIS (NEA): DETECTION OF STUDENT LEARNING BARRIERS IN PPKM IN MATHEMATICS SUBJECTS
Aksioma: Jurnal Program Studi Pendidikan Matematika, 2021 The research aims to analyze students' mistakes in solving straight-line equations and then find the learning barriers experienced during distance learning conducted in the 8th grade of a superior private junior high school in Surakarta City.
Sutama Sutama, Yuni Putri Indriyani
doaj +1 more source
Exploiting `Subjective' Annotations [PDF]
, 2008 Many interesting phenomena in conversation can only be annotated as a subjective task, requiring interpretative judgements from annotators. This leads to data which is annotated with lower levels of agreement not only due to errors in the annotation, but
Akker, Rieks op den, Reidsma, Dennis
core +2 more sources
Molecular Oncology, EarlyView.To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley +1 more source
Inner product encryption from ring learning with errors
Cybersecurity, 2020 The functional encryption scheme designed using the lattice can realize fine-grained encryption and it can resist quantum attacks. Unfortunately, the sizes of the keys and ciphertexts in cryptographic applications based on learning with errors are large,
Shisen Fang, Shaojun Yang, Yuexin Zhang
doaj +1 more source
Molecular Oncology, EarlyView.Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova +25 more
wiley +1 more source
Uncertainty-guided learning with scaled prediction errors in the basal ganglia.
PLoS Computational Biology, 2022 To accurately predict rewards associated with states or actions, the variability of observations has to be taken into account. In particular, when the observations are noisy, the individual rewards should have less influence on tracking of average reward,
Moritz Möller +2 more
doaj +1 more source
Meshed Up: Learnt Error Correction in 3D Reconstructions
, 2018 Dense reconstructions often contain errors that prior work has so far minimised using high quality sensors and regularising the output. Nevertheless, errors still persist.
Bewley, Alex +3 more
core +1 more source