منابع مشابه
Geometrical Perspective on Learning Behavior
We construct a geometrical perspective to justify the slow learning period and fast learning period during training. We plot the error surfaces and the solution space on the input space for a single neuron with two inputs. We study various training paths on this space when we run the back-propagation (BP) learning algorithm [1]. We display the relation between the learning curve and the trainin...
متن کاملA Geometrical Perspective on the Insulin Evolution
We study the molecular evolution of insulin from metric geometry point of view. In mathematics, and in particular in geometry, distances and metrics between objects are of fundamental importance. Using a weaker notion than the classical distance, namely the weighted quasi-metrics, one can study the geometry of biological sequences (DNA, mRNA, or proteins) space. We analyze from geometrical poin...
متن کاملA Geometrical Perspective for the Bargaining Problem
A new treatment to determine the Pareto-optimal outcome for a non-zero-sum game is presented. An equilibrium point for any game is defined here as a set of strategy choices for the players, such that no change in the choice of any single player will increase the overall payoff of all the players. Determining equilibrium for multi-player games is a complex problem. An intuitive conceptual tool f...
متن کاملFeed-forward neural networks: a geometrical perspective
The convex hull of any subset o f vertices of an n-dimensional hypercube contains no other vertex of the hypercube. This result permits the application of some theorems of n-dimensional geometry lo digital reed-forward neural networks. Also. the construction Of the convex hull is proposed as an alternative to more traditional learning algorithms. Some preliminary simulation results are reponed.
متن کاملEfficiency and Robustness in a Geometrical Perspective
A geometrical setting is constructed, based on Hilbert space, in which the asymptotic properties of estimators can be studied. Estimators are defined in the context of parametrised models, which are treated as submanifolds of an underlying Hilbert manifold, on which a parameter-defining mapping is defined as a submersion on to a finite-dimensional parameter space. Robustness of an estimator is ...
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: The Mathematical Intelligencer
سال: 2014
ISSN: 0343-6993,1866-7414
DOI: 10.1007/s00283-014-9464-2