67 citations · 350 across the 31 of their papers we have counts for
13 papers · 1 filter
Replacing Paths with Connection-Biased Attention for Knowledge Graph Completion
Sharmishtha Dutta, Alex Gittens, Mohammed J. Zaki +1
Knowledge graph (KG) completion aims to identify additional facts that can be inferred from the existing facts in the KG. Recent developments in this field have explored this task…
Exploiting Missing Data Remediation Strategies using Adversarial Missingness Attacks
Deniz Koyuncu, Alex Gittens, Bülent Yener +1
Adversarial Missingness (AM) attacks aim to manipulate model fitting by carefully engineering a missing data problem to achieve a specific malicious objective. AM attacks are signi…
Deception by Omission: Using Adversarial Missingness to Poison Causal Structure Learning
Deniz Koyuncu, Alex Gittens, Bülent Yener +1
Inference of causal structures from observational data is a key component of causal machine learning; in practice, this data may be incompletely observed. Prior work has demonstrat…
Reduced Label Complexity For Tight Regression
Alex Gittens, Malik Magdon-Ismail
Given data and labels the goal is find to minimize $\Vert{\rm X}\mathbf{w}-\mathbf{y}\V…
Simple Disentanglement of Style and Content in Visual Representations
Lilian Ngweta, Subha Maity, Alex Gittens +2
Learning visual representations with interpretable features, i.e., disentangled representations, remains a challenging problem. Existing methods demonstrate some success but are ha…
Output Randomization: A Novel Defense for both White-box and Black-box Adversarial Models
Daniel Park, Haidar Khan, Azer Khan +2
Adversarial examples pose a threat to deep neural network models in a variety of scenarios, from settings where the adversary has complete knowledge of the model in a "white box" s…