2 citations · 2 across the 3 of their papers we have counts for
5 papers
Large Scale Neural Architecture Search with Polyharmonic Splines
Ulrich Finkler, Michele Merler, Rameswar Panda +8
Neural Architecture Search (NAS) is a powerful tool to automatically design deep neural networks for many tasks, including image classification. Due to the significant computationa…
Ideas for Improving the Field of Machine Learning: Summarizing Discussion from the NeurIPS 2019 Retrospectives Workshop
Shagun Sodhani, Mayoore S. Jaiswal, Lauren Baker +5
This report documents ideas for improving the field of machine learning, which arose from discussions at the ML Retrospectives workshop at NeurIPS 2019. The goal of the report is t…
NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search
Rameswar Panda, Michele Merler, Mayoore Jaiswal +8
Neural Architecture Search (NAS) is an open and challenging problem in machine learning. While NAS offers great promise, the prohibitive computational demand of most of the existin…
MUTE: Data-Similarity Driven Multi-hot Target Encoding for Neural Network Design
Mayoore S. Jaiswal, Bumsoo Kang, Jinho Lee +1
Target encoding is an effective technique to deliver better performance for conventional machine learning methods, and recently, for deep neural networks as well. However, the exis…
Assessing Shape Bias Property of Convolutional Neural Networks
Hossein Hosseini, Baicen Xiao, Mayoore Jaiswal +1
It is known that humans display "shape bias" when classifying new items, i.e., they prefer to categorize objects based on their shape rather than color. Convolutional Neural Networ…