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Stochastic Gradient Descent (SGD) is the method of choice for large scale problems, most notably in deep learning. Recent studies target improving convergence and speed of the SGD algorithm. In this paper, we equip the SGD algorithm and its advanced versions with an intriguing feature, namely handling constrained problems. Constraints such as orthogonality are pervasive in learning theory. Nevertheless...
Motivated by the prospects of quantum computation, the design of quantum circuits received significant attention in the recent past. Due to the complex representation of the underlying quantum mechanical phenomena, a two-stage design flow was established in which the desired functionality is first realized in terms of a reversible circuit and, afterwards, mapped into an equivalent quantum circuit...
SDN aims to facilitate the management of increasingly complex, dynamic network environments and optimize the use of the resources available therein with minimal operator intervention. To this end, SDN controllers maintain a global view of the network topology and its state. However, the extraction of information about network flows and other network metrics remains a non-trivial challenge. Network...
In Systems-on-Chip (SoCs) based on Networks-on-Chip (NoCs), the timing requirements of target applications can be met by using virtual channels and traffic differentiation mechanisms to prioritize the most urgent communication streams. However, the use of virtual channels in NoCs results in silicon and power overheads as they are usually implemented by means of additional buffers and multiplexers...
We describe and evaluate the development of mission planners in intralogistics for a commercial unmanned aerial vehicle equipped with a robotic gripper in an industrial environment, which consists of an input warehouse, production lines, and a product depot. In this particular study, the planner produces the needed commands for carrying out a given mission, which includes the delivery of inputs picked...
Given the soaring amount of data being generated daily, graph mining tasks are becoming increasingly challenging, leading to tremendous demand for summarization techniques. Feature selection is a representative approach that simplifies a dataset by choosing features that are relevant to a specific task, such as classification, prediction, and anomaly detection. Although it can be viewed as a way to...
Orthogonal frequency division multiple (OFDM) has been introduced into long term evolution (LTE) because of its high spectral efficiency and robust anti-multipath fading ability. However, a major drawback of OFDM signals is high fluctuations of signal envelope. Peak-to-average power ratio (PAPR) is a well-known measure for the envelope fluctuations. Recently, another metric named cubic metric (CM)...
Monte Carlo Tree Search (MCTS) is frequently used for online planning and decision making in large space problems, where the move maximizing a reward score is chosen as the optimal solution. As many problems have more than one objective, this paper presents a multi-objective version of MCTS. The algorithm employs a non-linear scalarization function, the Chebyshev metric based function, as a basis...
The solution of difficult problems can be realized in shorter time with heuristic algorithms. There are many heuristic algorithms. In this study, artificial bee colony (ABC), biogeography based optimization (BBO), cuckoo bird search algorithm (CSO), differential evolution (DE), imperialist competitive algorithm (ICA) and particle swarm algorithm (PSO) have been chosen due to reasons such as the widespread...
Segment Routing (SR) can be used as a traffic engineering strategy to counteract increasing loads on networks like Internet Service Provider (ISP) backbones. Many SR approaches, however, optimize traffic flows that were measured in the past. This paper introduces a new tunnel training architecture. It aims to show that the results of these strategies can still be beneficial for routing new traffic...
We give a nearly linear-time randomized approximation scheme for the Held-Karp bound [22] for Metric-TSP. Formally, given an undirected edge-weighted graph G = (V,E) on m edges and ε 0, the algorithm outputs in O(m log^4 n/ε^2) time, with high probability, a (1 + ε)-approximation to the Held-Karp bound on the Metric-TSP instance induced by the shortest path metric...
In this study, crabs mating optimization (CRAB) algorithm that is one of the heuristic algorithms, has been developed and a monogamous crab mating optimization (MCO) algorithm has been proposed. In development, the main goal is to develop an algorithm that runs faster than the CRAB algorithm, to ensure obtaining good results like the CRAB algorithm. The developed MCO algorithm is compared with the...
Datacenters provide flexibility and high performance for users and cost efficiency for operators. However, the high computational demands of big data and analytics technologies such as MapReduce, a dominant programming model and framework for big data analytics, mean that even small changes in the efficiency of execution in the data center can have a large effect on user cost and operational cost...
One popular approach for blind deconvolution is to formulate a maximum a posteriori (MAP) problem with sparsity priors on the gradients of the latent image, and then alternatingly estimate the blur kernel and the latent image. While several successful MAP based methods have been proposed, there has been much controversy and confusion about their convergence, because sparsity priors have been shown...
In this paper, we propose a computational strategy to enhance the performance of Image Quality Metrics (IQM) by using content specific features of an image. We do this by creating Visual Error Importance (VEI) map that is applied to the error maps computed by the IQM. A global optimization can be used to compute the VEI map that is optimal for any given IQM. We demonstrate this concept by categorizing...
It is necessary to optimize the energy-efficient (EE) performance for millimeter-wave (mmWave) wireless systems, since the power consumption problem becomes increasingly crucial at high frequency bands. In hybrid precoding mmWave systems, the EE-oriented optimized elements include the analog and digital precoders at the transmitter, the analog and digital combiners at the receiver, as well as the...
In the Team Orienteering Problem (TOP) a set of locations is given, each with a score. The objective is to determine a fixed number of routes (teams), limited in length, that visit some locations and maximize the sum of the collected scores. For the first time we introduce bi-objective TOP which has a second objective, to balance all team's scores for the purpose of obtaining fair teams. So the second...
Video scene detection, the task of temporally dividing a video into its semantic sections, is an important process for effective analysis of heterogeneous video content. With the increased amount of video available for consumption, video scene detection becomes more and more important by providing means for effective video summarization, search and retrieval, browsing, and video understanding. We...
Coordinated multipoint transmission (CoMP) and soft frequency reuse (SFR) are two popular techniques used to control the deleterious effects caused by inter-cell interference in current 4G and envisaged 5G cellular networks. The performance of the combination of CoMP and SFR has been shown to be strongly influenced by the specific choice of the parameters governing the action of both mechanisms. Unfortunately,...
The bit mapping pattern has a crucial effect on the error performance of a bit-interleaved polar-coded modulation (BIPCM) system. In this paper, we have shown that a large proportion of the mapping patterns are producing the same error performances and are hence redundant as far as mapping optimization is concerned. An effective method is then proposed to eliminate the redundant mapping patterns and...
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