# Knowledge-augmented Column Networks: Guiding Deep Learning with Advice

## TL;DR

This paper introduces Knowledge-augmented Column Networks, a deep learning framework that incorporates human advice to improve learning from sparse and noisy data in structured domains.

## Contribution

It presents a novel relational deep learning model that effectively integrates human knowledge to enhance learning under data sparsity and noise.

## Key findings

- Improved model performance with sparse data
- Enhanced robustness to noise
- Effective use of human advice in deep learning

## Abstract

Recently, deep models have had considerable success in several tasks, especially with low-level representations. However, effective learning from sparse noisy samples is a major challenge in most deep models, especially in domains with structured representations. Inspired by the proven success of human guided machine learning, we propose Knowledge-augmented Column Networks, a relational deep learning framework that leverages human advice/knowledge to learn better models in presence of sparsity and systematic noise.