8.8k citations · 9.9k across the 52 of their papers we have counts for
7 papers · 1 filter
Births are difficult to predict even with rich survey and full-population register data
Elizaveta Sivak, Emily M. Cantrell, Thomas Emery +109
Major life events have proven difficult to predict. Does this reflect limits of theory, data, and algorithms, or the large role of chance? We examine one outcome - having a child w…
Provable Fairness for Neural Network Models using Formal Verification
Giorgian Borca-Tasciuc, Xingzhi Guo, Stanley Bak +1
Machine learning models are increasingly deployed for critical decision-making tasks, making it important to verify that they do not contain gender or racial biases picked up from…
Online AUC Optimization for Sparse High-Dimensional Datasets
Baojian Zhou, Yiming Ying, Steven Skiena
The Area Under the ROC Curve (AUC) is a widely used performance measure for imbalanced classification arising from many application domains where high-dimensional sparse data is ab…
Syntax-Directed Variational Autoencoder for Structured Data
Hanjun Dai, Yingtao Tian, Bo Dai +2
Deep generative models have been enjoying success in modeling continuous data. However it remains challenging to capture the representations for discrete structures with formal gra…
Exploring the power of GPU's for training Polyglot language models
Vivek Kulkarni, Rami Al-Rfou', Bryan Perozzi +1
One of the major research trends currently is the evolution of heterogeneous parallel computing. GP-GPU computing is being widely used and several applications have been designed t…
Inducing Language Networks from Continuous Space Word Representations
Bryan Perozzi, Rami Al-Rfou, Vivek Kulkarni +1
Recent advancements in unsupervised feature learning have developed powerful latent representations of words. However, it is still not clear what makes one representation better th…