Efficient Graph Kernels by Randomization

No abstract is available for this paper.

• Publication year

  2012

• Venue

  ECML/PKDD

• Publication date

  2012-09-24

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1007/978-3-642-33460-3_30
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Weisfeiler-Lehman Graph Kernels

  2011influential reference
• Markov Logic Sets: Towards Lifted Information Retrieval Using PageRank and Label Propagation

  2011cited by this paper
• Efficient graphlet kernels for large graph comparison

  2009influential reference
• Counting Belief Propagation

  2009cited by this paper
• A Linear-Time Graph Kernel

  2009cited by this paper
• Lifted First-Order Belief Propagation

  2008cited by this paper
• Graph Kernels

  2008cited by this paper
• Graph kernels based on tree patterns for molecules

  2006cited by this paper
• Markov logic networks

  2006cited by this paper
• Shortest-path kernels on graphs

  2005cited by this paper
• Probability Product Kernels

  2004cited by this paper
• Cyclic pattern kernels for predictive graph mining

  2004cited by this paper
• Locality-sensitive hashing scheme based on p-stable distributions

  2004influential reference
• Learning with Local and Global Consistency

  2003cited by this paper
• Marginalized Kernels Between Labeled Graphs

  2003cited by this paper
• A Kullback-Leibler Divergence Based Kernel for SVM Classification in Multimedia Applications

  2003cited by this paper
• On Graph Kernels: Hardness Results and Efficient Alternatives

  2003cited by this paper
• Learning Theory and Kernel Machines

  2003cited by this paper
• Expressivity versus efficiency of graph kernels

  2003cited by this paper
• Information Diffusion Kernels

  2002cited by this paper
• Learning from labeled and unlabeled data with label propagation

  2002cited by this paper
• A New Discriminative Kernel from Probabilistic Models

  2001cited by this paper
• Generalized Belief Propagation

  2000cited by this paper
• Exploiting Generative Models in Discriminative Classifiers

  1998cited by this paper
• Vector quantization and signal compression

  1991cited by this paper
• Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence Multi-Evidence Lifted Message Passing, with Application to PageRank and the Kalman Filter

  year unknowncited by this paper

• A Graph Neural Network Model for Real-Time Gesture Recognition Based on sEMG Signals

  2024cites this paper
• A deep graph convolutional neural network architecture for graph classification

  2023cites this paper
• A Variational Graph Autoencoder for Manipulation Action Recognition and Prediction

  2021influential citation
• Subgraph feature extraction based on multi-view dictionary learning for graph classification

  2021cites this paper
• Neighborhood Preserving Kernels for Attributed Graphs

  2020cites this paper
• Learning Kernel-Based Embeddings in Graph Neural Networks

  2020cites this paper
• A framework for the definition of complex structured feature spaces

  2020cites this paper
• Probabilistic Learning on Graphs via Contextual Architectures

  2020cites this paper
• TUAL INFORMATION MAXIMIZATION

  2020cites this paper
• Tree++: Truncated Tree Based Graph Kernels

  2020cites this paper
• Classification on Large Networks: A Quantitative Bound via Motifs and Graphons (Research)

  2020cites this paper
• Multi-Multi-Instance Learning Networks

  2019cites this paper
• Learning metrics for persistence-based summaries and applications for graph classification

  2019cites this paper
• Automating facial emotion recognition

  2019cites this paper
• Graph Deep Learning: Methods and Applications

  2019cites this paper
• Universal Readout for Graph Convolutional Neural Networks

  2019cites this paper
• InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization

  2019cites this paper
• An Approach for Improving Automatic Mouth Emotion Recognition

  2019cites this paper
• Learning and Interpreting Multi-Multi-Instance Learning Networks

  2018cites this paper
• Graph Classification with 2 D Convolutional Neural Networks

  2018cites this paper
• An End-to-End Deep Learning Architecture for Graph Classification

  2018cites this paper
• Graph Capsule Convolutional Neural Networks

  2018cites this paper
• A Deep Hybrid Graph Kernel Through Deep Learning Networks

  2018cites this paper
• Nonparametric small random networks for graph-structured pattern recognition

  2018cites this paper
• Graph Classification with Geometric Scattering

  2018cites this paper
• Pre-training Graph Neural Networks with Kernels

  2018cites this paper
• On Filter Size in Graph Convolutional Networks

  2018cites this paper
• Geometric Scattering for Graph Data Analysis

  2018cites this paper
• Semantic and geometric reasoning for robotic grasping: a probabilistic logic approach

  2018cites this paper
• Machine Learning for Enzyme Promiscuity

  2018cites this paper
• Graph Classification with 2D Convolutional Neural Networks

  2017cites this paper
• EmEx, a Tool for Automated Emotive Face Recognition Using Convolutional Neural Networks

  2017cites this paper
• Edge distance graph kernel and its application to small molecule classification

  2017cites this paper
• kProbLog: an algebraic Prolog for machine learning

  2017influential citation
• Classification on Large Networks: A Quantitative Bound via Motifs and Graphons

  2017cites this paper
• A Fast Kernel for Attributed Graphs

  2016influential citation
• Protein Fold Classification Using Large Margin Combination of Distance Metrics

  2016cites this paper
• Representation Learning on Unstructured Data

  2016influential citation
• A transitive aligned Weisfeiler-Lehman subtree kernel

  2016cites this paper
• Leveraging novel information sources for protein structure prediction (Nutzung neuer Informationsquellen für die Proteinstrukturvorhersage)

  2016cites this paper
• The pyramid quantized Weisfeiler-Lehman graph representation

  2016cites this paper
• pyGPs: a Python library for Gaussian process regression and classification

  2015influential citation
• Transitive Assignment Kernels for Structural Classification

  2015cites this paper
• Ordered Decompositional DAG kernels enhancements

  2015cites this paper
• A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Division of Electronics and Informatics Graduate School of Science and Technology Gunma University February 2015

  2015cites this paper
• Automatic selection of compiler optimizations using program characterization and machine learning

  2015cites this paper
• Unfolding Kernel embeddings of graphs: Enhancing class separation through manifold learning

  2015cites this paper
• Graph Invariant Kernels

  2015influential citation
• A quantum Jensen-Shannon graph kernel for unattributed graphs

  2015cites this paper
• University of Birmingham Unfolding Kernel embeddings of graphs

  2015cites this paper
• Finding the best not the most: regularized loss minimization subgraph selection for graph classification

  2015cites this paper
• Latent Variable Analysis and Signal Separation

  2015cites this paper
• An Aligned Subtree Kernel for Weighted Graphs

  2015cites this paper
• kProbLog: An Algebraic Prolog for Kernel Programming

  2015influential citation
• Patchworking Multiple Pairwise Distances for Learning with Distance Matrices

  2015cites this paper
• Tree-Based Kernel for Graphs With Continuous Attributes

  2015cites this paper
• High-level Reasoning and Low-level Learning for Grasping: A Probabilistic Logic Pipeline

  2014cites this paper
• Propagation kernels: efficient graph kernels from propagated information

  2014cites this paper
• Explicit Versus Implicit Graph Feature Maps: A Computational Phase Transition for Walk Kernels

  2014cites this paper
• Mean Polynomial Kernel and Its Application to Vector Sequence Recognition

  2014cites this paper
• Graph Kernels for Object Category Prediction in Task-Dependent Robot Grasping

  2013influential citation
• Coinciding Walk Kernels

  2013cites this paper
• Coinciding Walk Kernels: Parallel Absorbing Random Walks for Learning with Graphs and Few Labels

  2013cites this paper
• Scalable kernels for graphs with continuous attributes

  2013cites this paper
• Propagation Kernels for Partially Labeled Graphs

  2012influential citation