Liu Yang

Publication Activity (10 Years)

Years Active: 2006-2023
Publications (10 Years): 7

Top Topics

Linear Separability

Pac Learnability

Top Venues

Theor. Comput. Sci.

Publications

Steve Hanneke, Liu Yang
Bandit Learnability can be Undecidable. COLT (2023)
Steve Hanneke, Liu Yang
Toward a General Theory of Online Selective Sampling: Trading Off Mistakes and Queries. AISTATS (2021)
Steve Hanneke, Liu Yang
Statistical Learning under Nonstationary Mixing Processes. AISTATS (2019)
Liu Yang, Steve Hanneke, Jaime G. Carbonell
Bounds on the minimax rate for estimating a prior over a VC class from independent learning tasks. Theor. Comput. Sci. 716 (2018)
Steve Hanneke, Liu Yang
Testing piecewise functions. Theor. Comput. Sci. 745 (2018)
Amit Dhurandhar, Steve Hanneke, Liu Yang
Learning with Changing Features. CoRR (2017)
Steve Hanneke, Liu Yang
Testing Piecewise Functions. CoRR (2017)
Steve Hanneke, Tommi S. Jaakkola, Liu Yang
Statistical Learning under Nonstationary Mixing Processes. CoRR (2015)
Steve Hanneke, Varun Kanade, Liu Yang
Learning with a Drifting Target Concept. CoRR (2015)
Avrim Blum, Yishay Mansour, Liu Yang
Online Allocation and Pricing with Economies of Scale. WINE (2015)
Steve Hanneke, Varun Kanade, Liu Yang
Learning with a Drifting Target Concept. ALT (2015)
Liu Yang, Steve Hanneke, Jaime G. Carbonell
Bounds on the Minimax Rate for Estimating a Prior over a VC Class from Independent Learning Tasks. CoRR (2015)
Steve Hanneke, Liu Yang
Minimax analysis of active learning. J. Mach. Learn. Res. 16 (2015)
Liu Yang, Steve Hanneke, Jaime G. Carbonell
Bounds on the Minimax Rate for Estimating a Prior over a VC Class from Independent Learning Tasks. ALT (2015)
Steve Hanneke, Liu Yang
Minimax Analysis of Active Learning. CoRR (2014)
Liu Yang, Jaime G. Carbonell
Buy-in-Bulk Active Learning. NIPS (2013)
Liu Yang, Steve Hanneke
Activized Learning with Uniform Classification Noise. ICML (2) (2013)
Liu Yang, Steve Hanneke, Jaime G. Carbonell
A theory of transfer learning with applications to active learning. Mach. Learn. 90 (2) (2013)
Liu Yang, Avrim Blum, Jaime G. Carbonell
Learnability of DNF with representation-specific queries. ITCS (2013)
Liu Yang, Rong Jin, Rahul Sukthankar
Bayesian Active Distance Metric Learning CoRR (2012)
Maria-Florina Balcan, Eric Blais, Avrim Blum, Liu Yang
Active Property Testing. FOCS (2012)
Steve Hanneke, Liu Yang
Surrogate Losses in Passive and Active Learning CoRR (2012)
Liu Yang, Steve Hanneke, Jaime G. Carbonell
The Sample Complexity of Self-Verifying Bayesian Active Learning. AISTATS (2011)
Liu Yang, Steve Hanneke, Jaime G. Carbonell
Identifiability of Priors from Bounded Sample Sizes with Applications to Transfer Learning. COLT (2011)
Maria-Florina Balcan, Eric Blais, Avrim Blum, Liu Yang
Active Testing CoRR (2011)
Steve Hanneke, Liu Yang
Negative Results for Active Learning with Convex Losses. AISTATS (2010)
Liu Yang, Rong Jin, Lily B. Mummert, Rahul Sukthankar, Adam Goode, Bin Zheng, Steven C. H. Hoi, Mahadev Satyanarayanan
A Boosting Framework for Visuality-Preserving Distance Metric Learning and Its Application to Medical Image Retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 32 (1) (2010)
Liu Yang, Steve Hanneke, Jaime G. Carbonell
Bayesian Active Learning Using Arbitrary Binary Valued Queries. ALT (2010)
Liu Yang, Rong Jin, Jieping Ye
Online learning by ellipsoid method. ICML (2009)
Liu Yang, Rong Jin, Rahul Sukthankar, Frédéric Jurie
Unifying discriminative visual codebook generation with classifier training for object category recognition. CVPR (2008)
Liu Yang, Rong Jin, Rahul Sukthankar
Semi-supervised Learning with Weakly-Related Unlabeled Data: Towards Better Text Categorization. NIPS (2008)
Liu Yang, Rong Jin, Rahul Sukthankar, Bin Zheng, Lily B. Mummert, Mahadev Satyanarayanan, Mei Chen, Drazen Jukic
Learning distance metrics for interactive search-assisted diagnosis of mammograms. Medical Imaging: Computer-Aided Diagnosis (2007)
Liu Yang, Rong Jin, Rahul Sukthankar
Bayesian Active Distance Metric Learning. UAI (2007)
Liu Yang, Rong Jin, Caroline Pantofaru, Rahul Sukthankar
Discriminative Cluster Refinement: Improving Object Category Recognition Given Limited Training Data. CVPR (2007)
Liu Yang, Rong Jin, Rahul Sukthankar, Yi Liu
An Efficient Algorithm for Local Distance Metric Learning. AAAI (2006)
Yi Liu, Rong Jin, Liu Yang
Semi-supervised Multi-label Learning by Constrained Non-negative Matrix Factorization. AAAI (2006)