135 citations · 232 across the 11 of their papers we have counts for
11 papers
Probabilistic Semantic Retrieval for Surveillance Videos with Activity Graphs
Yuting Chen, Joseph Wang, Yannan Bai +2
We present a novel framework for finding complex activities matching user-described queries in cluttered surveillance videos. The wide diversity of queries coupled with unavailabil…
Field of Groves: An Energy-Efficient Random Forest
Zafar Takhirov, Joseph Wang, Marcia S. Louis +2
Machine Learning (ML) algorithms, like Convolutional Neural Networks (CNN), Support Vector Machines (SVM), etc. have become widespread and can achieve high statistical performance.…
Adaptive Neural Networks for Efficient Inference
Tolga Bolukbasi, Joseph Wang, Ofer Dekel +1
We present an approach to adaptively utilize deep neural networks in order to reduce the evaluation time on new examples without loss of accuracy. Rather than attempting to redesig…
Pruning Random Forests for Prediction on a Budget
Feng Nan, Joseph Wang, Venkatesh Saligrama
We propose to prune a random forest (RF) for resource-constrained prediction. We first construct a RF and then prune it to optimize expected feature cost & accuracy. We pose prunin…
Resource Constrained Structured Prediction
Tolga Bolukbasi, Kai-Wei Chang, Joseph Wang +1
We study the problem of structured prediction under test-time budget constraints. We propose a novel approach applicable to a wide range of structured prediction problems in comput…
Optimally Pruning Decision Tree Ensembles With Feature Cost
Feng Nan, Joseph Wang, Venkatesh Saligrama
We consider the problem of learning decision rules for prediction with feature budget constraint. In particular, we are interested in pruning an ensemble of decision trees to reduc…