Deep networks are able to learn good representations of unlabelled data via a greedy layer-wise approach to training. One challenge arises in choosing the layer types to use, whether it is an autoencoder, restricted boltzmann machine, with and without sparsity regularization. The layer choice directly affects the type of representations learned. In this paper, we examine sparse autoencoders and...

In this paper we propose a new routing paradigm, called pseudogeometric routing. In pseudo-geometric routing, each node u of a network of computing elements is assigned a pseudo coordinate composed of the graph (hop) distances from u to a set of designated nodes (the anchors) in the network. On theses pseudo coordinates we employ greedy geometric routing. Almost as a side effect, pseudo-geometr...

Abstract The Fixed Set Search (FSS) is a novel metaheuristic that adds learning mechanism to the Greedy Randomized Adaptive Procedure (GRASP). In recent publications, its efficiency has been shown on different types of combinatorial optimization problems like routing, machine scheduling and covering. this paper FSS adapted multi-objective for finding Pareto Front approximations. This adaptation...

Because of fast convergence in finite number of steps and low computational complexity, signal recovery from compressed measurements using greedy algorithms have generated a large amount of interest in recent years. Among these greedy algorithms OMP is well studied and recently its generalization, gOMP, have also drawn attention. On the other hand OLS and its generalization mOLS have been studi...

The connected vertex cover (CVC) problem is a variant of the vertex cover problem, 1 which has many important applications, such as wireless network design, routing and wavelength 2 assignment problem, etc. A good algorithm for the problem can help us improve engineering 3 efficiency, cost savings and resources in industrial applications. In this work, we present an efficient 4 algorithm GRASP-...

We study the convergence time of Nash dynamics in two classes of congestion games – constant player congestion games and bounded jump congestion games. It was shown by Ackermann and Skopalik [2] that even 3-player congestion games are PLS-complete. We design an FPTAS for congestion games with constant number of players. In particular, for any > 0, we establish a stronger result, namely, any seq...

On [24] some consequences of the Restricted Isometry Property (RIP) of matrices have been applied to develop a greedy algorithm called “ROMP” (Regularized Orthogonal Matching Pursuit) to recover sparse signals and to approximate non-sparse ones. These consequences were subsequently applied to other greedy and thresholding algorithms like “SThresh”, “CoSaMP”, “StOMP” and “SWCGP”. In this paper, ...

Balancing the load in content addressing schemes for route-restricted networks represents a challenge with a wide range of applications. Solutions based on greedy embeddings maintain minimal state information and enable efficient routing, but any such solutions currently result in either imbalanced content addressing, overloading individual nodes, or are unable to efficiently account for networ...

We describe the Fast Greedy Sparse Subspace Clustering (FGSSC) algorithm providing an efficient method for clustering data belonging to a few low-dimensional linear or affine subspaces. The main difference of our algorithm from predecessors is its ability to work with noisy data having a high rate of erasures (missed entries with the known coordinates) and errors (corrupted entries with unknown...

Microarray data usually contain a large number of genes, but a small number of samples. Feature subset selection for microarray data aims at reducing the number of genes so that useful information can be extracted from the samples. Reducing the dimension of data sets further helps in improving the computational efficiency of the learning model. In this paper, we propose a modified algorithm bas...