منابع مشابه
Three More Learning Points
Kathryn Maitland, Charles Newton, Kevin Marsh, Mike Levin The study by Planche et al. [1] provides important new information addressing intracellular volume depletion in children with severe childhood malaria, but does not address the question of whether intravascular volume depletion (hypovolemic shock) is present. Using sophisticated methodology to determine total body water and extracellular...
متن کاملSelecting Landmark Points for Sparse Manifold Learning
There has been a surge of interest in learning non-linear manifold models to approximate high-dimensional data. Both for computational complexity reasons and for generalization capability, sparsity is a desired feature in such models. This usually means dimensionality reduction, which naturally implies estimating the intrinsic dimension, but it can also mean selecting a subset of the data to us...
متن کاملPoor starting points in machine learning
Poor (even random) starting points for learning/training/optimization are common in machine learning. In many settings, the method of Robbins and Monro (online stochastic gradient descent) is known to be optimal for good starting points, but may not be optimal for poor starting points — indeed, for poor starting points Nesterov acceleration can help during the initial iterations, even though Ne...
متن کاملLearning grasping points with shape context
This paper presents work on vision based robotic grasping. The proposed method adopts a learning framework where prototypical grasping points are learnt from several examples and then used on novel objects. For representation purposes, we apply the concept of shape context and for learning we use a supervised learning approach in which the classifier is trained with labelled synthetic images. W...
متن کاملAttainability of boundary points under reinforcement learning
This paper investigates the properties of the most common form of reinforcement learning (the “basic model” of Erev and Roth, American Economic Review, 88, 848-881, 1998). Stochastic approximation theory has been used to analyse the local stability of fixed points under this learning process. However, as we show, when such points are on the boundary of the state space, for example, pure strateg...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Swiss Medical Forum ‒ Schweizerisches Medizin-Forum
سال: 2001
ISSN: 1424-4020,1424-3784
DOI: 10.4414/smf.2001.04120