Liu Yang

According to our database, Liu Yang authored at least 30 papers between 2006 and 2023.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2023

Bandit Learnability can be Undecidable.

Steve Hanneke, Liu Yang

Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2021

Toward a General Theory of Online Selective Sampling: Trading Off Mistakes and Queries.

Steve Hanneke, Liu Yang

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2019

Statistical Learning under Nonstationary Mixing Processes.

Steve Hanneke, Liu Yang

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Bounds on the minimax rate for estimating a prior over a VC class from independent learning tasks.

Liu Yang, Steve Hanneke, Jaime G. Carbonell

Theor. Comput. Sci., 2018

Testing piecewise functions.

Steve Hanneke, Liu Yang

Theor. Comput. Sci., 2018

2017

Learning with Changing Features.

Amit Dhurandhar, Steve Hanneke, Liu Yang

CoRR, 2017

2015

Minimax analysis of active learning.

Steve Hanneke, Liu Yang

J. Mach. Learn. Res., 2015

Statistical Learning under Nonstationary Mixing Processes.

Steve Hanneke, Tommi S. Jaakkola, Liu Yang

CoRR, 2015

Online Allocation and Pricing with Economies of Scale.

Avrim Blum, Yishay Mansour, Liu Yang

Proceedings of the Web and Internet Economics - 11th International Conference, 2015

Learning with a Drifting Target Concept.

Steve Hanneke, Varun Kanade, Liu Yang

Proceedings of the Algorithmic Learning Theory - 26th International Conference, 2015

2013

A theory of transfer learning with applications to active learning.

Liu Yang, Steve Hanneke, Jaime G. Carbonell

Mach. Learn., 2013

Buy-in-Bulk Active Learning.

Liu Yang, Jaime G. Carbonell

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

Learnability of DNF with representation-specific queries.

Liu Yang, Avrim Blum, Jaime G. Carbonell

Proceedings of the Innovations in Theoretical Computer Science, 2013

Activized Learning with Uniform Classification Noise.

Liu Yang, Steve Hanneke

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

2012

Surrogate Losses in Passive and Active Learning

Steve Hanneke, Liu Yang

CoRR, 2012

Active Property Testing.

Maria-Florina Balcan, Eric Blais, Avrim Blum, Liu Yang

Proceedings of the 53rd Annual IEEE Symposium on Foundations of Computer Science, 2012

2011

Identifiability of Priors from Bounded Sample Sizes with Applications to Transfer Learning.

Liu Yang, Steve Hanneke, Jaime G. Carbonell

Proceedings of the COLT 2011, 2011

The Sample Complexity of Self-Verifying Bayesian Active Learning.

Liu Yang, Steve Hanneke, Jaime G. Carbonell

Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Active Testing

Maria-Florina Balcan, Eric Blais, Avrim Blum, Liu Yang

CoRR, 2011

2010

A Boosting Framework for Visuality-Preserving Distance Metric Learning and Its Application to Medical Image Retrieval.

Liu Yang, Rong Jin, Lily B. Mummert, Rahul Sukthankar, Adam Goode, Bin Zheng, Steven C. H. Hoi, Mahadev Satyanarayanan

IEEE Trans. Pattern Anal. Mach. Intell., 2010

Negative Results for Active Learning with Convex Losses.

Steve Hanneke, Liu Yang

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

Bayesian Active Learning Using Arbitrary Binary Valued Queries.

Liu Yang, Steve Hanneke, Jaime G. Carbonell

Proceedings of the Algorithmic Learning Theory, 21st International Conference, 2010

2009

Online learning by ellipsoid method.

Liu Yang, Rong Jin, Jieping Ye

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

2008

Semi-supervised Learning with Weakly-Related Unlabeled Data: Towards Better Text Categorization.

Liu Yang, Rong Jin, Rahul Sukthankar

Proceedings of the Advances in Neural Information Processing Systems 21, 2008

Unifying discriminative visual codebook generation with classifier training for object category recognition.

Liu Yang, Rong Jin, Rahul Sukthankar, Frédéric Jurie

Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008

2007

Bayesian Active Distance Metric Learning.

Liu Yang, Rong Jin, Rahul Sukthankar

Proceedings of the UAI 2007, 2007

Learning distance metrics for interactive search-assisted diagnosis of mammograms.

Liu Yang, Rong Jin, Rahul Sukthankar, Bin Zheng, Lily B. Mummert, Mahadev Satyanarayanan, Mei Chen, Drazen Jukic

Proceedings of the Medical Imaging 2007: Computer-Aided Diagnosis, San Diego, 2007

Discriminative Cluster Refinement: Improving Object Category Recognition Given Limited Training Data.

Liu Yang, Rong Jin, Caroline Pantofaru, Rahul Sukthankar

Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2007), 2007

2006

An Efficient Algorithm for Local Distance Metric Learning.

Liu Yang, Rong Jin, Rahul Sukthankar, Yi Liu

Proceedings of the Proceedings, 2006

Semi-supervised Multi-label Learning by Constrained Non-negative Matrix Factorization.

Yi Liu, Rong Jin, Liu Yang

Proceedings of the Proceedings, 2006