Search Results

Graph Agreement Models for Semi-Supervised Learning

tensorflow/neural-structured-learning NeurIPS 2019

To address this, we propose Graph Agreement Models (GAM), which introduces an auxiliary model that predicts the probability of two nodes sharing the same label as a learned function of their features.

Classification General Classification +2

CARLS: Cross-platform Asynchronous Representation Learning System

tensorflow/neural-structured-learning 26 May 2021

In this work, we propose CARLS, a novel framework for augmenting the capacity of existing deep learning frameworks by enabling multiple components -- model trainers, knowledge makers and knowledge banks -- to concertedly work together in an asynchronous fashion across hardware platforms.

Representation Learning

Explaining and Harnessing Adversarial Examples

tensorflow/neural-structured-learning 20 Dec 2014

Several machine learning models, including neural networks, consistently misclassify adversarial examples---inputs formed by applying small but intentionally worst-case perturbations to examples from the dataset, such that the perturbed input results in the model outputting an incorrect answer with high confidence.

Image Classification

Graph-RISE: Graph-Regularized Image Semantic Embedding

tensorflow/neural-structured-learning 14 Feb 2019

Learning image representations to capture fine-grained semantics has been a challenging and important task enabling many applications such as image search and clustering.

Clustering General Classification +4

Low-Dimensional Hyperbolic Knowledge Graph Embeddings

tensorflow/neural-structured-learning ACL 2020

However, existing hyperbolic embedding methods do not account for the rich logical patterns in KGs.

Knowledge Graph Embeddings

Cannot find the paper you are looking for? You can Submit a new open access paper.