458 citations · 979 across the 26 of their papers we have counts for
9 papers · 1 filter
Reaching Data Confidentiality and Model Accountability on the CalTrain
Zhongshu Gu, Hani Jamjoom, Dong Su +5
Distributed collaborative learning (DCL) paradigms enable building joint machine learning models from distrusting multi-party participants. Data confidentiality is guaranteed by re…
Scalable Graph Learning for Anti-Money Laundering: A First Look
Mark Weber, Jie Chen, Toyotaro Suzumura +6
Organized crime inflicts human suffering on a genocidal scale: the Mexican drug cartels have murdered 150,000 people since 2006, upwards of 700,000 people per year are "exported" i…
Online Planner Selection with Graph Neural Networks and Adaptive Scheduling
Tengfei Ma, Patrick Ferber, Siyu Huo +2
Automated planning is one of the foundational areas of AI. Since no single planner can work well for all tasks and domains, portfolio-based techniques have become increasingly popu…
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Tengfei Ma, Jie Chen, Cao Xiao
Deep generative models have achieved remarkable success in various data domains, including images, time series, and natural languages. There remain, however, substantial challenges…
AWE: Asymmetric Word Embedding for Textual Entailment
Tengfei Ma, Chiamin Wu, Cao Xiao +1
Textual entailment is a fundamental task in natural language processing. It refers to the directional relation between text fragments such that the "premise" can infer "hypothesis"…
RDPD: Rich Data Helps Poor Data via Imitation
Shenda Hong, Cao Xiao, Trong Nghia Hoang +3
In many situations, we need to build and deploy separate models in related environments with different data qualities. For example, an environment with strong observation equipment…