2 citations · 2 across the 1 of their papers we have counts for
5 papers
MosAIc: Finding Artistic Connections across Culture with Conditional Image Retrieval
Mark Hamilton, Stephanie Fu, Mindren Lu +9
We introduce MosAIc, an interactive web app that allows users to find pairs of semantically related artworks that span different cultures, media, and millennia. To create this appl…
It Is Likely That Your Loss Should be a Likelihood
Mark Hamilton, Evan Shelhamer, William T. Freeman
Many common loss functions such as mean-squared-error, cross-entropy, and reconstruction loss are unnecessarily rigid. Under a probabilistic interpretation, these common losses cor…
Semi-Supervised Translation with MMD Networks
Mark Hamilton
This work aims to improve semi-supervised learning in a neural network architecture by introducing a hybrid supervised and unsupervised cost function. The unsupervised component is…
MMLSpark: Unifying Machine Learning Ecosystems at Massive Scales
Mark Hamilton, Sudarshan Raghunathan, Ilya Matiach +13
We introduce Microsoft Machine Learning for Apache Spark (MMLSpark), an ecosystem of enhancements that expand the Apache Spark distributed computing library to tackle problems in D…
Flexible and Scalable Deep Learning with MMLSpark
Mark Hamilton, Sudarshan Raghunathan, Akshaya Annavajhala +11
In this work we detail a novel open source library, called MMLSpark, that combines the flexible deep learning library Cognitive Toolkit, with the distributed computing framework Ap…