3 citations · 3 across the 4 of their papers we have counts for
4 papers
Analyzing Physical Adversarial Example Threats to Machine Learning in Election Systems
Khaleque Md Aashiq Kamal, Surya Eada, Aayushi Verma +4
Developments in the machine learning voting domain have shown both promising results and risks. Trained models perform well on ballot classification tasks (> 99% accuracy) but are…
Busting the Paper Ballot: Voting Meets Adversarial Machine Learning
Kaleel Mahmood, Caleb Manicke, Ethan Rathbun +5
We show the security risk associated with using machine learning classifiers in United States election tabulators. The central classification task in election tabulation is decidin…
Syllabus: Portable Curricula for Reinforcement Learning Agents
Ryan Sullivan, Ryan Pégoud, Ameen Ur Rehman +5
Curriculum learning has been a quiet, yet crucial component of many high-profile successes of reinforcement learning. Despite this, it is still a niche topic that is not directly s…
Structural Analysis of Open Cluster Bochum 2
Harmeen Kaur, Saurabh Sharma, Alok Durgapal +5
We present the results from our deep optical photometric observations of Bochum 2 (Boc2) star cluster obtained using the m Devasthal Fast Optical Telescope along with archival…