• SCS

  • Referenced in 53 articles [sw16632]
  • Homogeneous Self-Dual Embedding. We introduce a first order method for solving very large cone ... alternating directions method of multipliers, to solve the homogeneous self-dual embedding, an equivalent feasibility ... several favorable properties. Compared to interior-point methods, first-order methods scale to very large...
  • Chombo

  • Referenced in 69 articles [sw04316]
  • tools for implementing finite difference methods for the solution of partial differential equations on block ... with both embedded boundaries and mapped grids, and Chombo also supports particle methods. Most parallel...
  • FaceNet

  • Referenced in 30 articles [sw21626]
  • standard techniques with FaceNet embeddings as feature vectors. Our method uses a deep convolutional network ... trained to directly optimize the embedding itself, rather than an intermediate bottleneck layer ... generated using a novel online triplet mining method. The benefit of our approach is much ... also introduce the concept of harmonic embeddings, and a harmonic triplet loss, which describe different...
  • PTE

  • Referenced in 7 articles [sw37756]
  • scale Heterogeneous Text Networks. Unsupervised text embedding methods, such as Skip-gram and Paragraph Vector ... architectures such as convolutional neural networks, these methods usually yield inferior results when applied ... possible reason is that these text embedding methods learn the representation of text ... learning method for text data, which we call the extit{predictive text embedding} (PTE). Predictive...
  • TR-BDF2

  • Referenced in 33 articles [sw03446]
  • This method can be viewed as an embedded diagonally implicit Runge-Kutta pair of orders ... examples show the effectiveness of the refined method...
  • Graphs

  • Referenced in 109 articles [sw12277]
  • names): algorithm engineers construct fast route planning methods; database and information systems researchers investigate materialization ... networking and distributed computing and for metric embeddings in geometry as well. In this survey ... size and the query time. We survey methods for general graphs as well as specialized...
  • AnnexML

  • Referenced in 5 articles [sw30153]
  • Multi-label Classification. Extreme multi-label classification methods have been widely used in Web-scale ... paper, we present a novel graph embedding method called ”AnnexML”. At the training step, AnnexML ... search method that efficiently explores the learned k-nearest neighbor graph in the embedding space ... state-of-the-art embedding-based method...
  • mdp

  • Referenced in 11 articles [sw14129]
  • Slow Feature Analysis), manifold learning methods ([Hessian] Locally Linear Embedding), several classifiers, probabilistic methods (Factor...
  • DynGEM

  • Referenced in 4 articles [sw40461]
  • DynGEM: Deep Embedding Method for Dynamic Graphs. Embedding large graphs in low dimensional spaces ... node classification. Existing methods focus on computing the embedding for static graphs. However, many graphs ... better running time than using static embedding methods on each snapshot of a dynamic graph...
  • SBERT

  • Referenced in 6 articles [sw36204]
  • other state-of-the-art sentence embeddings methods...
  • ECOS

  • Referenced in 58 articles [sw12123]
  • used to solve optimization problems on any embedded system for which a C-compiler ... implemented solution algorithm is an interior-point method that is an efficient standard algorithm...
  • GAP

  • Referenced in 19 articles [sw26294]
  • algorithms and clustering methods with validation indices are implemented for extracting embedded information ... more powerful and effective than conventional graphical methods when dimension reduction techniques fail or when...
  • MADNESS

  • Referenced in 7 articles [sw06887]
  • PDEs in irregular geometries with multiresolution methods. I: Embedded Dirichlet boundary conditions In this work...
  • PyTorch-BigGraph

  • Referenced in 4 articles [sw34086]
  • Large-scale Graph Embedding System. Graph embedding methods produce unsupervised node features from graphs that ... edges, which exceeds the capability of existing embedding systems. We present PyTorch-BigGraph...
  • HyPy

  • Referenced in 2 articles [sw40557]
  • significant interest in scalable hyperbolic-space embedding methods. These embeddings enable constant-time approximation ... large-scale graphs. Whereas previous methods compute the embedding by using the derivative-free Nelder ... optimization. We compare our hyperbolic embedding method implementation in Python (called Hypy) against the best ... show the scalability of our method by embedding a graph with 1.8 billion edges...
  • OSQP

  • Referenced in 27 articles [sw26960]
  • quadratic programs based on the alternating direction method of multipliers, employing a novel operator splitting ... embedded systems. In addition, our technique is the first operator splitting method for quadratic programs...
  • MEBDF

  • Referenced in 85 articles [sw00567]
  • described. The algorithm is constructed by embedding a standard sparse linear algebraic equation solver into ... more space dimensions, using the method of lines. A code based on this algorithm...
  • CogDL

  • Referenced in 2 articles [sw37740]
  • divided into two major parts, graph embedding methods and graph neural networks. Most ... graph embedding methods learn node-level or graph-level representations in an unsupervised...
  • hydra+

  • Referenced in 2 articles [sw40553]
  • Hydra: a method for strain-minimizing hyperbolic embedding of network- and distance-based data ... distance recovery and approximation), a new method for embedding network- or distance-based data into ... hydra is competitive with existing hyperbolic embedding methods, but achieved at substantially shorter computation time ... hydra+, typically outperforms existing methods in both computation time and embedding quality...
  • MIRACL

  • Referenced in 30 articles [sw06009]
  • software library for implementing number-theoretic based methods of cryptography. While there are many libraries ... MIRACL does more by securing embedded-devices and mobile smart devices like no other ... your answer. MIRACL is particularly adept at methods based on Elliptic Curves...