219 citations · 287 across the 20 of their papers we have counts for
8 papers · 1 filter
Multi-Agent Algorithmic Recourse
Andrew O'Brien, Edward Kim
The recent adoption of machine learning as a tool in real world decision making has spurred interest in understanding how these decisions are being made. Counterfactual Explanation…
ATRAS: Adversarially Trained Robust Architecture Search
Yigit Alparslan, Edward Kim
In this paper, we explore the effect of architecture completeness on adversarial robustness. We train models with different architectures on CIFAR-10 and MNIST dataset. For each mo…
Extreme Volatility Prediction in Stock Market: When GameStop meets Long Short-Term Memory Networks
Yigit Alparslan, Edward Kim
The beginning of 2021 saw a surge in volatility for certain stocks such as GameStop company stock (Ticker GME under NYSE). GameStop stock increased around 10 fold from its decade-l…
Evaluating Online and Offline Accuracy Traversal Algorithms for k-Complete Neural Network Architectures
Yigit Alparslan, Ethan Jacob Moyer, Edward Kim
Architecture sizes for neural networks have been studied widely and several search methods have been offered to find the best architecture size in the shortest amount of time possi…
Towards Searching Efficient and Accurate Neural Network Architectures in Binary Classification Problems
Yigit Alparslan, Ethan Jacob Moyer, Isamu Mclean Isozaki +4
In recent years, deep neural networks have had great success in machine learning and pattern recognition. Architecture size for a neural network contributes significantly to the su…
The Interpretable Dictionary in Sparse Coding
Edward Kim, Connor Onweller, Andrew O'Brien +1
Artificial neural networks (ANNs), specifically deep learning networks, have often been labeled as black boxes due to the fact that the internal representation of the data is not e…
Unsupervised Star Galaxy Classification with Cascade Variational Auto-Encoder
Hao Sun, Jiadong Guo, Edward J. Kim +1
The increasing amount of data in astronomy provides great challenges for machine learning research. Previously, supervised learning methods achieved satisfactory recognition accura…
Classifiers Based on Deep Sparse Coding Architectures are Robust to Deep Learning Transferable Examples
Jacob M. Springer, Charles S. Strauss, Austin M. Thresher +2
Although deep learning has shown great success in recent years, researchers have discovered a critical flaw where small, imperceptible changes in the input to the system can drasti…