27 citations · 59 across the 6 of their papers we have counts for
12 papers
Deep Learning Models for Predicting Wildfires from Historical Remote-Sensing Data
Fantine Huot, R. Lily Hu, Matthias Ihme +6
Identifying regions that have high likelihood for wildfires is a key component of land and forestry management and disaster preparedness. We create a data set by aggregating nearly…
Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval
Tao Wu, Ellie Ka-In Chio, Heng-Tze Cheng +15
Many recent advances in neural information retrieval models, which predict top-K items given a query, learn directly from a large training set of (query, item) pairs. However, they…
Neural Collaborative Filtering vs. Matrix Factorization Revisited
Steffen Rendle, Walid Krichene, Li Zhang +1
Embedding based models have been the state of the art in collaborative filtering for over a decade. Traditionally, the dot product or higher order equivalents have been used to com…
Superbloom: Bloom filter meets Transformer
John Anderson, Qingqing Huang, Walid Krichene +2
We extend the idea of word pieces in natural language models to machine learning tasks on opaque ids. This is achieved by applying hash functions to map each id to multiple hash to…
Sensitivity Analysis in the Dupire Local Volatility Model with Tensorflow
Francois Belletti, Davis King, James Lottes +2
In a recent paper, we have demonstrated how the affinity between TPUs and multi-dimensional financial simulation resulted in fast Monte Carlo simulations that could be setup in a f…
Large-Scale Discrete Fourier Transform on TPUs
Tianjian Lu, Yi-Fan Chen, Blake Hechtman +2
In this work, we present two parallel algorithms for the large-scale discrete Fourier transform (DFT) on Tensor Processing Unit (TPU) clusters. The two parallel algorithms are asso…