Name
Title | ||
|---|---|---|
Human-Guided Learning of Column Networks: Knowledge Injection for Relational Deep Learning |
Abstract | ||
|---|---|---|
Recently, deep models have been successfully adopted in several applications, especially where low-level representations are needed. However, sparse, noisy samples and structured domains (with multiple objects and interactions) are some of the open challenges in most deep models. Column Networks, a deep architecture, can succinctly capture domain structure and interactions, but may still be prone to sub-optimal learning from sparse and noisy samples. Inspired by the success of human-knowledge guided learning in AI, especially in data-scarce domains, we propose Knowledge-augmented Column Networks that leverage human advice/knowledge for better learning with noisy/sparse samples. Our experiments demonstrate that our approach leads to either superior overall performance or faster convergence (i.e., both effective and efficient). |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3430984.3431018 | CODS-COMAD 2021: PROCEEDINGS OF THE 3RD ACM INDIA JOINT INTERNATIONAL CONFERENCE ON DATA SCIENCE & MANAGEMENT OF DATA (8TH ACM IKDD CODS & 26TH COMAD) |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mayukh Das | 1 | 9 | 5.03 |
| Devendra Singh Dhami | 2 | 0 | 4.06 |
| Yang Yu | 3 | 0 | 0.34 |
| Gautam Kunapuli | 4 | 0 | 0.34 |
| Sriraam Natarajan | 5 | 0 | 0.68 |