• ToulBar2

  • Referenced in 22 articles [sw07289]
  • software for Graphical Models such as Cost Function Networks, Markov Random Fields, Weighted Constraint Satisfaction...
  • NETGEN

  • Referenced in 147 articles [sw09229]
  • capacitated and uncapacitated transportation and minimum cost flow network problems, and assignment problems. In addition ... generating structurally different classes of network problems the code permits the user to vary structural ... paper contains the solution time and objective function value of 40 assignment, transportation, and network...
  • D-ADMM

  • Referenced in 16 articles [sw28440]
  • ADMM), for solving separable optimization problems in networks of interconnected nodes or agents ... optimization problem there is a private cost function and a private constraint set at each ... minimize the sum of all the cost functions, constraining the solution ... ADMM is proven to converge when the network is bipartite or when all the functions...
  • GREAT

  • Referenced in 1 article [sw18878]
  • find regions of topological or functional similarities between networks. In computational biology ... between nodes in different networks (via a node cost function) and then aim to find ... networks) with respect to “node conservation”, typically the total node cost function over all aligned ... optimally edges between networks first in order to improve node cost function needed to then...
  • AutoKeras

  • Referenced in 3 articles [sw33648]
  • suffer from expensive computational cost. Network morphism, which keeps the functionality of a neural network...
  • Lasagne

  • Referenced in 6 articles [sw20936]
  • such as Convolutional Neural Networks (CNNs), recurrent networks including Long Short-Term Memory (LSTM ... momentum, RMSprop and ADAM. Freely definable cost function and no need to derive gradients...
  • MONC

  • Referenced in 7 articles [sw00589]
  • computations for Monte Carlo methods within a network of personal computers using the program system ... modification of a congruent pseudorandom number generator; functional capabilities of the MONC; demands ... execute using the MONC; an estimate of costs of distributed computations using the MONC. Advantages...
  • LinkBoost

  • Referenced in 1 article [sw29981]
  • communities in a network. Specifically, a variable-cost loss function is defined to address ... function. As a result, any link prediction method designed to optimize the loss function would ... function and present an approach to scale-up the algorithm by decomposing the network into...
  • iCDI-PseFpt

  • Referenced in 15 articles [sw30067]
  • with PseAAC and molecular fingerprints. Many crucial functions in life, such as heartbeat, sensory transduction ... study of ion channel-drug interaction networks is an important topic for drug development. However ... both time-consuming and costly to determine whether a drug and a protein ion channel...
  • WaveGlow

  • Referenced in 1 article [sw35020]
  • only a single network, trained using only a single cost function: maximizing the likelihood...
  • automl

  • Referenced in 2 articles [sw32865]
  • networks either with gradient descent or metaheuristic, using automatic hyper parameters tuning and custom cost ... function. A mix inspired by the common tricks on Deep Learning and Particle Swarm Optimization...
  • PANET

  • Referenced in 1 article [sw25676]
  • networks. Despite such a useful function, limitations on the network size that can be analyzed ... exist due to high computational costs. In addition, the plugin cannot verify an intrinsic property ... function to simulate the observation on a large number of random networks. To overcome these...
  • MERLIN

  • Referenced in 14 articles [sw04248]
  • training of neural networks. Minimizing a multidimensional function faces a lot of difficulties. There ... derivatives using differencing, that in turn costs in computing time as well as in accuracy...
  • FINN-R

  • Referenced in 1 article [sw25906]
  • inference engines on FPGAs. Given a neural network description, the tool optimizes for given platforms ... precision. We introduce formalizations of resource cost functions and performance predictions, and elaborate ... evaluate a selection of reduced precision neural networks ranging from CIFAR-10 classifiers to YOLO...
  • CAPP

  • Referenced in 9 articles [sw03233]
  • reasons for this effect are: Costs are declining, which encourages partnerships between CAD and CAPP ... from one point to another on the network; and relational databases (RDBs) and associated structured ... planning. An alternative way of accomplishing this function was needed and Computer Aided Process Planning ... planning applicationMetCAPP software looks for the least costly plan capable of producing the design...
  • DeepMovie

  • Referenced in 1 article [sw15171]
  • another image. First, they use convolutional neural network features to build a statistical model ... incorporate optical flow explicitly into the cost function...
  • Sancus

  • Referenced in 3 articles [sw24321]
  • propose Sancus, a security architecture for networked embedded devices. Sancus supports extensibility in the form ... only the hardware. Moreover, the hardware cost of Sancus is low. We describe the design ... memory access control and cryptographic functionality required to run Sancus. We also develop...
  • Monkeys

  • Referenced in 1 article [sw01277]
  • Monkeys -- A software architecture for viRoom -- low-cost multicamera system This paper presents a software ... different number of FireWire digital cameras and networked computers. Minimal hardware requirement is the main ... which makes it flexible and transportable. The functionality of the system is demonstrated...
  • WNetKAT

  • Referenced in 1 article [sw25228]
  • demonstrate several relevant applications for WNetKAT, including cost and capacity-aware reachability, as well ... generalize to more complex (and stateful) network functions and service chains. For example, WNetKAT allows...
  • GEDEVO

  • Referenced in 2 articles [sw08298]
  • infer the biological function of proteins and genes. However, the corresponding network alignment problem ... comparison dedicated to real-world size biological networks. Underlying our approach is the so-called ... minimal number of (or more general: minimal costs for) edge insertions and deletions. We present...