Learning From Disagreement in the U.S. Treasury Bond Market
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DOI: 10.1111/jofi.12971
Abstract: This paper studies an arbitrage-free dynamic term structure model of a Bayesian learner who presumes that dispersion of beliefs is priced in Treasury markets and that measured dispersion has forecasting power for future Treasury yields.… read more here.
Keywords: treasury; market; disagreement treasury; learning rule ... See more keywords
Learning rule sets from survival data
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DOI: 10.1186/s12859-017-1693-x
Abstract: BackgroundSurvival analysis is an important element of reasoning from data. Applied in a number of fields, it has become particularly useful in medicine to estimate the survival rate of patients on the basis of their… read more here.
Keywords: rule sets; analysis; survival data; learning rule ... See more keywords
Optimizing BCPNN Learning Rule for Memory Access
Sign Up to like & getrecommendations! Published in 2020 at "Frontiers in Neuroscience"
DOI: 10.3389/fnins.2020.00878
Abstract: Simulation of large scale biologically plausible spiking neural networks, e.g., Bayesian Confidence Propagation Neural Network (BCPNN), usually requires high-performance supercomputers with dedicated accelerators, such as GPUs, FPGAs, or even Application-Specific Integrated Circuits (ASICs). Almost all… read more here.
Keywords: memory access; learning rule; optimization; access ... See more keywords
Voltage-dependent synaptic plasticity: Unsupervised probabilistic Hebbian plasticity rule based on neurons membrane potential
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Neuroscience"
DOI: 10.3389/fnins.2022.983950
Abstract: This study proposes voltage-dependent-synaptic plasticity (VDSP), a novel brain-inspired unsupervised local learning rule for the online implementation of Hebb’s plasticity mechanism on neuromorphic hardware. The proposed VDSP learning rule updates the synaptic conductance on the… read more here.
Keywords: rule; learning rule; plasticity; voltage dependent ... See more keywords
Infants’ Learning of Rule-Based Visual Sequences Predicts Language Outcome at 2 Years
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DOI: 10.3389/fpsyg.2020.00281
Abstract: The ability to learn and generalize abstract rules from sensory input – i.e., Rule Learning (RL) – is seen as pivotal to language development, and specifically to the acquisition of the grammatical structure of language.… read more here.
Keywords: infants learning; rule based; learning rule; outcome years ... See more keywords