Abstract Ultrasonic tomography, which is widely used in the study of fracturing process rocks, often exhibits low resolution due to insufficient ray coverage, particularly while evaluating three-dimensional (3D) fractures. To resolve this issue, we adopted sparseness regularisation tomography reconstruct ultrasonic velocity rocks. Both numerical and laboratory experiments demonstrate that with ...

Natural images follow statistics inherited by the structure of our physical (visual) environment. In particular, a prominent facet of this structure is that images can be described by a relatively sparse number of features. To investigate the role of this sparseness in the efficiency of the neural code, we designed a new class of random textured stimuli with a controlled sparseness value inspir...

The goal of supervised learning is to infer a functional mapping based on a set of training examples. To achieve good generalization, it is necessary to control the “complexity” of the learned function. In Bayesian approaches, this is done by adopting a prior for the parameters of the function being learned. We propose a Bayesian approach to supervised learning, which leads to sparse solutions;...

It is well known that direct training of deep neural networks will generally lead to poor results. A major progress in recent years is the invention of various pretraining methods to initialize network parameters and it was shown that such methods lead to good prediction performance. However, the reason for the success of pretraining has not been fully understood, although it was argued that re...

Support vector machines (SVMs) construct decision functions that are linear combinations of kernel evaluations on the training set. The samples with non-vanishing coefficients are called support vectors. In this work we establish lower (asymptotical) bounds on the number of support vectors. On our way we prove several results which are of great importance for the understanding of SVMs. In parti...

Most brain-imaging studies of language comprehension focus on activity following meaningful stimuli. Testing adult human participants with high-density EEG, we show that, already before the presentation of a critical word, context-induced semantic predictions are reflected by a neurophysiological index, which we therefore call the semantic readiness potential (SRP). The SRP precedes critical wo...