1.6k citations · 5.9k across the 67 of their papers we have counts for
10 papers · 1 filter
Bloom Origami Assays: Practical Group Testing
Louis Abraham, Gary Becigneul, Benjamin Coleman +3
We study the problem usually referred to as group testing in the context of COVID-19. Given n samples collected from patients, how should we select and test mixtures of samples to…
An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph
Jiarui Jin, Jiarui Qin, Yuchen Fang +5
There is an influx of heterogeneous information network (HIN) based recommender systems in recent years since HIN is capable of characterizing complex graphs and contains rich sema…
DDPG++: Striving for Simplicity in Continuous-control Off-Policy Reinforcement Learning
Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola
This paper prescribes a suite of techniques for off-policy Reinforcement Learning (RL) that simplify the training process and reduce the sample complexity. First, we show that simp…
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation
Rasool Fakoor, Jonas Mueller, Nick Erickson +2
Automated machine learning (AutoML) can produce complex model ensembles by stacking, bagging, and boosting many individual models like trees, deep networks, and nearest neighbor es…
Tiering as a Stochastic Submodular Optimization Problem
Hyokun Yun, Michael Froh, Roshan Makhijani +3
Tiering is an essential technique for building large-scale information retrieval systems. While the selection of documents for high priority tiers critically impacts the efficiency…
Improving Semantic Segmentation via Self-Training
Yi Zhu, Zhongyue Zhang, Chongruo Wu +6
Deep learning usually achieves the best results with complete supervision. In the case of semantic segmentation, this means that large amounts of pixelwise annotations are required…