… model to work well involves research into the architecture and a long period of tuning. We
present a single model that … In particular, this single model is trained concurrently on ImageNet, …

… to the new class, transferring from only one model does not exploit fully previous experience.
At the same time, using acritically all the prior knowledge induces partial negative transfer …

Curation of large, diverse MRI datasets via multi-institutional collaborations can help improve
learning of generalizable synthesis models that reliably translate source- onto target-…

… ), we aim to suggest a model that is simple while explaining all observed phenomena. So
what are the components that underlie all learning phenomena? In the ULM there are three: …

… a graphical illustration of the generative model. We will call this model the Theme Model 1. …
Before we show how we could proceed to learn the model parameters, let us first look at how …

… than learn them, the model group subjects should have a decided advantage. Experiment 2
tested this implication by using two groups as before, in which one learned the device model …

… As no a priori knowledge of the target distribution is available, the key question is how to
guide the model learning to capture information which is discriminative for the specific task but …

… We know that if one of us has a problem everyone is going to be there to deal with whatever
needs to be dealt with. It's your friends at school who you're going to depend on most. …

… It is proposed that if people assess that they already know an item they will choose not to
study it. The second substage involves order determination of those items that will be studied. …

… All of these factors were shown to individually influence learning outcomes, but no single
factor was capable of adequately explaining visitor learning outcomes across all visitors. The …