Tzu-Kuo Huang

According to our database, Tzu-Kuo Huang authored at least 23 papers between 2004 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

SmartChoices: Augmenting Software with Learned Implementations.

Daniel Golovin, Gábor Bartók, Eric Chen, Emily Donahue, Tzu-Kuo Huang, Efi Kokiopoulou, Ruoyan Qin, Nikhil Sarda, Justin Sybrandt, Vincent Tjeng

CoRR, 2023

2020

Predicting Motion of Vulnerable Road Users using High-Definition Maps and Efficient ConvNets.

Fang-Chieh Chou, Tsung-Han Lin, Henggang Cui, Vladan Radosavljevic, Thi Nguyen, Tzu-Kuo Huang, Matthew Niedoba, Jeff Schneider, Nemanja Djuric

Proceedings of the IEEE Intelligent Vehicles Symposium, 2020

Long-term Prediction of Vehicle Behavior using Short-term Uncertainty-aware Trajectories and High-definition Maps.

Sai Yalamanchi, Tzu-Kuo Huang, Galen Clark Haynes, Nemanja Djuric

Proceedings of the 23rd IEEE International Conference on Intelligent Transportation Systems, 2020

2019

Active Learning for Cost-Sensitive Classification.

Akshay Krishnamurthy, Alekh Agarwal, Tzu-Kuo Huang, Hal Daumé III, John Langford

J. Mach. Learn. Res., 2019

Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networks.

Henggang Cui, Vladan Radosavljevic, Fang-Chieh Chou, Tsung-Han Lin, Thi Nguyen, Tzu-Kuo Huang, Jeff Schneider, Nemanja Djuric

Proceedings of the International Conference on Robotics and Automation, 2019

2018

Enhancing Selectivity in Big Data.

Mathias Lécuyer, Riley Spahn, Roxana Geambasu, Tzu-Kuo Huang, Siddhartha Sen

IEEE Secur. Priv., 2018

2017

Pyramid: Enhancing Selectivity in Big Data Protection with Count Featurization.

Mathias Lécuyer, Riley Spahn, Roxana Geambasu, Tzu-Kuo Huang, Siddhartha Sen

Proceedings of the 2017 IEEE Symposium on Security and Privacy, 2017

2016

Active Learning with Oracle Epiphany.

Tzu-Kuo Huang, Lihong Li, Ara Vartanian, Saleema Amershi, Xiaojin Zhu

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Active Search and Bandits on Graphs using Sigma-Optimality.

Yifei Ma, Tzu-Kuo Huang, Jeff G. Schneider

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Efficient and Parsimonious Agnostic Active Learning.

Tzu-Kuo Huang, Alekh Agarwal, Daniel J. Hsu, John Langford, Robert E. Schapire

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

Active Transfer Learning under Model Shift.

Xuezhi Wang, Tzu-Kuo Huang, Jeff G. Schneider

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Exploiting Non-Sequence Data in Dynamic Model Learning.

Tzu-Kuo Huang

PhD thesis, 2013

Learning Hidden Markov Models from Non-sequence Data via Tensor Decomposition.

Tzu-Kuo Huang, Jeff G. Schneider

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Spectral Learning of Hidden Markov Models from Dynamic and Static Data.

Tzu-Kuo Huang, Jeff G. Schneider

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

Learning Bi-clustered Vector Autoregressive Models.

Tzu-Kuo Huang, Jeff G. Schneider

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2012

2011

Learning Auto-regressive Models from Sequence and Non-sequence Data.

Tzu-Kuo Huang, Jeff G. Schneider

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010

Learning Nonlinear Dynamic Models from Non-sequenced Data.

Tzu-Kuo Huang, Le Song, Jeff G. Schneider

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Temporal Collaborative Filtering with Bayesian Probabilistic Tensor Factorization.

Liang Xiong, Xi Chen, Tzu-Kuo Huang, Jeff G. Schneider, Jaime G. Carbonell

Proceedings of the SIAM International Conference on Data Mining, 2010

2009

Learning linear dynamical systems without sequence information.

Tzu-Kuo Huang, Jeff G. Schneider

Proceedings of the 26th Annual International Conference on Machine Learning, 2009

2006

Generalized Bradley-Terry Models and Multi-Class Probability Estimates.

Tzu-Kuo Huang, Ruby C. Weng, Chih-Jen Lin

J. Mach. Learn. Res., 2006

Ranking individuals by group comparisons.

Tzu-Kuo Huang, Chih-Jen Lin, Ruby C. Weng

Proceedings of the Machine Learning, 2006

2004

A Generalized Bradley-Terry Model: From Group Competition to Individual Skill.

Tzu-Kuo Huang, Chih-Jen Lin, Ruby C. Weng

Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Sequence Recognition with Scanning N-Tuple Ensembles.

Simon M. Lucas, Tzu-Kuo Huang

Proceedings of the 17th International Conference on Pattern Recognition, 2004