82 citations · 112 across the 6 of their papers we have counts for
6 papers
A Comparison of Decision Forest Inference Platforms from A Database Perspective
Hong Guan, Mahidhar Reddy Dwarampudi, Venkatesh Gunda +3
Decision forest, including RandomForest, XGBoost, and LightGBM, is one of the most popular machine learning techniques used in many industrial scenarios, such as credit card fraud…
Learning from Training Dynamics: Identifying Mislabeled Data Beyond Manually Designed Features
Qingrui Jia, Xuhong Li, Lei Yu +5
While mislabeled or ambiguously-labeled samples in the training set could negatively affect the performance of deep models, diagnosing the dataset and identifying mislabeled sample…
Backpropagation through Time and Space: Learning Numerical Methods with Multi-Agent Reinforcement Learning
Elliot Way, Dheeraj S. K. Kapilavai, Yiwei Fu +1
We introduce Backpropagation Through Time and Space (BPTTS), a method for training a recurrent spatio-temporal neural network, that is used in a homogeneous multi-agent reinforceme…
Effects of Differential Privacy and Data Skewness on Membership Inference Vulnerability
Stacey Truex, Ling Liu, Mehmet Emre Gursoy +2
Membership inference attacks seek to infer the membership of individual training instances of a privately trained model. This paper presents a membership privacy analysis and evalu…
Towards Demystifying Membership Inference Attacks
Stacey Truex, Ling Liu, Mehmet Emre Gursoy +2
Membership inference attacks seek to infer membership of individual training instances of a model to which an adversary has black-box access through a machine learning-as-a-service…
Adversarial Examples in Deep Learning: Characterization and Divergence
Wenqi Wei, Ling Liu, Margaret Loper +4
The burgeoning success of deep learning has raised the security and privacy concerns as more and more tasks are accompanied with sensitive data. Adversarial attacks in deep learnin…