no code implementations • 18 Sep 2023 • Siva Likitha Valluru, Biplav Srivastava, Sai Teja Paladi, Siwen Yan, Sriraam Natarajan
Building teams and promoting collaboration are two very common business activities.
no code implementations • 10 Sep 2023 • Siwen Yan, Phillip Odom, Sriraam Natarajan
We consider the problem of identifying authorship by posing it as a knowledge graph construction and refinement.
1 code implementation • 14 Oct 2022 • Tiantian Chen, Siwen Yan, Jianxiong Guo, Weili Wu
Aiming at selecting a small subset of nodes with maximum influence on networks, the Influence Maximization (IM) problem has been extensively studied.
no code implementations • 16 Jun 2022 • Siwen Yan, Sriraam Natarajan, Saket Joshi, Roni Khardon, Prasad Tadepalli
Ensemble models (bagging and gradient-boosting) of relational decision trees have proved to be one of the most effective learning methods in the area of probabilistic logic models (PLMs).
no code implementations • 19 Mar 2021 • Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan
Predicting and discovering drug-drug interactions (DDIs) using machine learning has been studied extensively.
no code implementations • 13 Feb 2021 • Devendra Singh Dhami, Siwen Yan, Sriraam Natarajan
We consider the problem of learning distance-based Graph Convolutional Networks (GCNs) for relational data.
no code implementations • NeurIPS Workshop ICBINB 2020 • Siwen Yan, Devendra Singh Dhami, Sriraam Natarajan
Reducing bias while learning and inference is an important requirement to achieve generalizable and better performing models.
no code implementations • 2 Jan 2020 • Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, Sriraam Natarajan
We consider the problem of structure learning for Gaifman models and learn relational features that can be used to derive feature representations from a knowledge base.
no code implementations • 14 Nov 2019 • Devendra Singh Dhami, Siwen Yan, Gautam Kunapuli, David Page, Sriraam Natarajan
Predicting and discovering drug-drug interactions (DDIs) is an important problem and has been studied extensively both from medical and machine learning point of view.