42 citations · 91 across the 6 of their papers we have counts for
6 papers
Long-term Prediction of Vehicle Behavior using Short-term Uncertainty-aware Trajectories and High-definition Maps
Sai Yalamanchi, Tzu-Kuo Huang, Galen Clark Haynes +1
Motion prediction of surrounding vehicles is one of the most important tasks handled by a self-driving vehicle, and represents a critical step in the autonomous system necessary to…
Predicting Motion of Vulnerable Road Users using High-Definition Maps and Efficient ConvNets
Fang-Chieh Chou, Tsung-Han Lin, Henggang Cui +6
Following detection and tracking of traffic actors, prediction of their future motion is the next critical component of a self-driving vehicle (SDV) technology, allowing the SDV to…
Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networks
Henggang Cui, Vladan Radosavljevic, Fang-Chieh Chou +5
Autonomous driving presents one of the largest problems that the robotics and artificial intelligence communities are facing at the moment, both in terms of difficulty and potentia…
Pyramid: Enhancing Selectivity in Big Data Protection with Count Featurization
Mathias Lecuyer, Riley Spahn, Roxana Geambasu +2
Protecting vast quantities of data poses a daunting challenge for the growing number of organizations that collect, stockpile, and monetize it. The ability to distinguish data that…
Active Learning for Cost-Sensitive Classification
Akshay Krishnamurthy, Alekh Agarwal, Tzu-Kuo Huang +2
We design an active learning algorithm for cost-sensitive multiclass classification: problems where different errors have different costs. Our algorithm, COAL, makes predictions by…
Efficient and Parsimonious Agnostic Active Learning
Tzu-Kuo Huang, Alekh Agarwal, Daniel J. Hsu +2
We develop a new active learning algorithm for the streaming setting satisfying three important properties: 1) It provably works for any classifier representation and classificatio…