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ORCIDLiu Yang 0001
Person information
- affiliation: Yale University, New Haven, CT, USA
- affiliation (former): IBM T.J. Watson Research Center, Yorktown Heights, USA
- affiliation (former): Carnegie Mellon University, Machine Learning Department, Pittsburgh, PA, USA
- affiliation (former): Michigan State University, East Lansing, MI, USA
Other persons with the same name
- Liu Yang — disambiguation page
- Liu Yang 0002
![[0000-0001-9915-6432]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-9915-6432")
— Guangzhou University, School of Computer Science and Education Software, China (and 1 more) - Liu Yang 0003 — Chongqing University of Posts and Telecommunications, School of Communication and Information Engineering, China
- Liu Yang 0004 — Army Engineering University of PLA, College of Communication Engineering, Nanjing, China
- Liu Yang 0005 — University of Massachusetts Amherst, College of Information and Computer Sciences, MA, USA
- Liu Yang 0006 — Beijing Jiaotong University, State Key Laboratory of Rail Traffic Control and Safety, China
- Liu Yang 0007 — Beijing Institute of Technology, School of Automation, China
- Liu Yang 0008 — Hong Kong University of Science and Technology, Department of Computer Science and Engineering, Hong Kong
Other persons with a similar name
- Alex X. Liu (aka: Xiang-Yang Alex Liu) — Michigan State University, East Lansing, Department of Computer Science and Engineering (and 1 more)
- San Yang Liu (aka: San-Yang Liu, San-yang Liu, Sanyang Liu) — disambiguation page
- Xiao-Yang Liu
- Yang Liu — disambiguation page
- Yang Liu 0003 — Nanyang Technological University, School of Computer Engineering, Singapore (and 1 more)
- Yang Liu 0004 — Amazon Alexa AI, Sunnyvale, CA, USA (and 3 more)
- Yang Liu 0005 — Tsinghua University, Department of Computer Science and Technology, China (and 1 more)
- Yang Liu 0018 — University of California, Santa Cruz, CA, USA (and 2 more)
- Yang Liu 0040 — Zhejiang Normal University, College of Mathematics, Physics and Information Engineering, Jinhua, China (and 1 more)
- Yang Liu 0165 — Tsinghua University, Institute for AI Industry Research, Beijing, China (and 2 more)
- show all similar names
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2020 – today
- 2023
[c22]Steve Hanneke, Liu Yang:
Bandit Learnability can be Undecidable. COLT 2023: 5813-5849- 2021
- [c21]Steve Hanneke, Liu Yang:
Toward a General Theory of Online Selective Sampling: Trading Off Mistakes and Queries. AISTATS 2021: 3997-4005
2010 – 2019
- 2019
- [c20]Steve Hanneke, Liu Yang:
Statistical Learning under Nonstationary Mixing Processes. AISTATS 2019: 1678-1686 - 2018
- [j5]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: 124-140 (2018) - [j4]Steve Hanneke, Liu Yang:
Testing piecewise functions. Theor. Comput. Sci. 745: 23-35 (2018) - 2017
- [i9]Amit Dhurandhar, Steve Hanneke, Liu Yang:
Learning with Changing Features. CoRR abs/1705.00219 (2017) - [i8]Steve Hanneke, Liu Yang:
Testing Piecewise Functions. CoRR abs/1706.07669 (2017) - 2015
- [j3]Steve Hanneke, Liu Yang:
Minimax analysis of active learning. J. Mach. Learn. Res. 16: 3487-3602 (2015) - [c19]Steve Hanneke, Varun Kanade, Liu Yang:
Learning with a Drifting Target Concept. ALT 2015: 149-164 - [c18]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: 270-284 - [c17]Avrim Blum, Yishay Mansour, Liu Yang:
Online Allocation and Pricing with Economies of Scale. WINE 2015: 159-172 - [i7]Steve Hanneke, Varun Kanade, Liu Yang:
Learning with a Drifting Target Concept. CoRR abs/1505.05215 (2015) - [i6]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 abs/1505.05231 (2015) - [i5]Steve Hanneke, Tommi S. Jaakkola, Liu Yang:
Statistical Learning under Nonstationary Mixing Processes. CoRR abs/1512.08064 (2015) - 2014
- [i4]Steve Hanneke, Liu Yang:
Minimax Analysis of Active Learning. CoRR abs/1410.0996 (2014) - 2013
- [j2]Liu Yang, Steve Hanneke, Jaime G. Carbonell:
A theory of transfer learning with applications to active learning. Mach. Learn. 90(2): 161-189 (2013) - [c16]Liu Yang, Steve Hanneke:
Activized Learning with Uniform Classification Noise. ICML (2) 2013: 370-378 - [c15]Liu Yang, Avrim Blum, Jaime G. Carbonell:
Learnability of DNF with representation-specific queries. ITCS 2013: 37-46 - [c14]Liu Yang, Jaime G. Carbonell:
Buy-in-Bulk Active Learning. NIPS 2013: 2229-2237 - 2012
- [c13]Maria-Florina Balcan, Eric Blais, Avrim Blum, Liu Yang:
Active Property Testing. FOCS 2012: 21-30 - [i3]Liu Yang, Rong Jin, Rahul Sukthankar:
Bayesian Active Distance Metric Learning. CoRR abs/1206.5283 (2012) - [i2]Steve Hanneke, Liu Yang:
Surrogate Losses in Passive and Active Learning. CoRR abs/1207.3772 (2012) - 2011
- [c12]Liu Yang, Steve Hanneke, Jaime G. Carbonell:
Identifiability of Priors from Bounded Sample Sizes with Applications to Transfer Learning. COLT 2011: 789-806 - [c11]Liu Yang, Steve Hanneke, Jaime G. Carbonell:
The Sample Complexity of Self-Verifying Bayesian Active Learning. AISTATS 2011: 816-822 - [i1]Maria-Florina Balcan, Eric Blais, Avrim Blum, Liu Yang:
Active Testing. CoRR abs/1111.0897 (2011) - 2010
- [j1]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): 30-44 (2010) - [c10]Liu Yang, Steve Hanneke, Jaime G. Carbonell:
Bayesian Active Learning Using Arbitrary Binary Valued Queries. ALT 2010: 50-58 - [c9]Steve Hanneke, Liu Yang:
Negative Results for Active Learning with Convex Losses. AISTATS 2010: 321-325
2000 – 2009
- 2009
- [c8]Liu Yang, Rong Jin, Jieping Ye:
Online learning by ellipsoid method. ICML 2009: 1153-1160 - 2008
- [c7]Liu Yang, Rong Jin, Rahul Sukthankar, Frédéric Jurie:
Unifying discriminative visual codebook generation with classifier training for object category recognition. CVPR 2008 - [c6]Liu Yang, Rong Jin, Rahul Sukthankar:
Semi-supervised Learning with Weakly-Related Unlabeled Data: Towards Better Text Categorization. NIPS 2008: 1857-1864 - 2007
- [c5]Liu Yang, Rong Jin, Caroline Pantofaru, Rahul Sukthankar:
Discriminative Cluster Refinement: Improving Object Category Recognition Given Limited Training Data. CVPR 2007 - [c4]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. Computer-Aided Diagnosis 2007: 65141H - [c3]Liu Yang, Rong Jin, Rahul Sukthankar:
Bayesian Active Distance Metric Learning. UAI 2007: 442-449 - 2006
- [c2]Yi Liu, Rong Jin, Liu Yang:
Semi-supervised Multi-label Learning by Constrained Non-negative Matrix Factorization. AAAI 2006: 421-426 - [c1]Liu Yang, Rong Jin, Rahul Sukthankar, Yi Liu:
An Efficient Algorithm for Local Distance Metric Learning. AAAI 2006: 543-548
Coauthor Index
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