14 citations · 23 across the 6 of their papers we have counts for
7 papers
Feedback Control for Multi-Objective Graph Self-Supervision
Karish Grover, Theodore Vasiloudis, Han Xie +3
Can multi-task self-supervised learning on graphs be coordinated without the usual tug-of-war between objectives? Graph self-supervised learning (SSL) offers a growing toolbox of p…
Dynamic Mixture-of-Experts for Incremental Graph Learning
Lecheng Kong, Theodore Vasiloudis, Seongjun Yun +2
Graph incremental learning is a learning paradigm that aims to adapt trained models to continuously incremented graphs and data over time without the need for retraining on the ful…
GraphStorm: all-in-one graph machine learning framework for industry applications
Da Zheng, Xiang Song, Qi Zhu +13
Graph machine learning (GML) is effective in many business applications. However, making GML easy to use and applicable to industry applications with massive datasets remain challe…
TEM: High Utility Metric Differential Privacy on Text
Ricardo Silva Carvalho, Theodore Vasiloudis, Oluwaseyi Feyisetan
Ensuring the privacy of users whose data are used to train Natural Language Processing (NLP) models is necessary to build and maintain customer trust. Differential Privacy (DP) has…
BRR: Preserving Privacy of Text Data Efficiently on Device
Ricardo Silva Carvalho, Theodore Vasiloudis, Oluwaseyi Feyisetan
With the use of personal devices connected to the Internet for tasks such as searches and shopping becoming ubiquitous, ensuring the privacy of the users of such services has becom…
Block-distributed Gradient Boosted Trees
Theodore Vasiloudis, Hyunsu Cho, Henrik Boström
The Gradient Boosted Tree (GBT) algorithm is one of the most popular machine learning algorithms used in production, for tasks that include Click-Through Rate (CTR) prediction and…
Predicting Session Length in Media Streaming
Theodore Vasiloudis, Hossein Vahabi, Ross Kravitz +1
Session length is a very important aspect in determining a user's satisfaction with a media streaming service. Being able to predict how long a session will last can be of great us…