Chicheng Zhang

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John LangfordMicrosoft Research New YorkVerified email at hunch.net
Kamalika ChaudhuriProfessor of Computer Science, UCSD. Research Scientist, Meta AIVerified email at ucsd.edu
Alekh AgarwalGoogleVerified email at google.com
Akshay KrishnamurthyUniversity of Massachusetts AmherstVerified email at cs.umass.edu
Jordan T. AshMicrosoft Research NYCVerified email at princeton.edu
Zhi WangPhD Student, University of California San DiegoVerified email at ucsd.edu
Aleksandrs SlivkinsSenior Principal Researcher, Microsoft Research NYCVerified email at microsoft.com
Songbai YanUniversity of California San DiegoVerified email at eng.ucsd.edu
Jie ShenAssistant Professor, Stevens Institute of TechnologyVerified email at stevens.edu
Kwang-Sung JunThe University of ArizonaVerified email at cs.arizona.edu
Francesco OrabonaAssociate Professor, KAUSTVerified email at orabona.com
pranjal awasthiGoogleVerified email at rutgers.edu
Tengyu MAStanford UniversityVerified email at stanford.edu
Haipeng LuoAssociate Professor, University of Southern CaliforniaVerified email at usc.edu
Yining ChenOpenAIVerified email at openai.com
Sahand NegahbanAssociate Professor, Yale UniversityVerified email at yale.edu
Hal Daumé IIIAssociate Professor of Computer Science, University of MarylandVerified email at umiacs.umd.edu
Maryam MajzoubiGoogle, PhD New York University 2021Verified email at google.com
Balazs SzorenyiSr Research Scientist at Yahoo ResearchVerified email at yahooinc.com
Devanathan ThiruvenkatachariYahoo Research / VerizonmediaVerified email at verizonmedia.com

Chicheng Zhang

University of Arizona

Verified email at cs.arizona.edu - Homepage

Interactive machine learning learning theory


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Deep batch active learning by diverse, uncertain gradient lower bounds JT Ash, C Zhang, A Krishnamurthy, J Langford, A Agarwal arXiv preprint arXiv:1906.03671, 2019	578	2019
Active learning from weak and strong labelers C Zhang, K Chaudhuri Advances in Neural Information Processing Systems 28, 2015	103	2015
Beyond disagreement-based agnostic active learning C Zhang, K Chaudhuri Advances in Neural Information Processing Systems 27, 2014	98	2014
Contextual bandits with continuous actions: Smoothing, zooming, and adapting A Krishnamurthy, J Langford, A Slivkins, C Zhang The Journal of Machine Learning Research 21 (1), 5402-5446, 2020	67	2020
Revisiting perceptron: Efficient and label-optimal learning of halfspaces S Yan, C Zhang Advances in Neural Information Processing Systems 30, 2017	53	2017
Efficient active learning of sparse halfspaces C Zhang Conference on Learning Theory, 1856-1880, 2018	38	2018
Efficient active learning of sparse halfspaces with arbitrary bounded noise C Zhang, J Shen, P Awasthi Advances in Neural Information Processing Systems 33, 7184-7197, 2020	34	2020
Search improves label for active learning A Beygelzimer, DJ Hsu, J Langford, C Zhang Advances in neural information processing systems 29, 2016	30	2016
Warm-starting contextual bandits: Robustly combining supervised and bandit feedback C Zhang, A Agarwal, H Daumé III, J Langford, SN Negahban arXiv preprint arXiv:1901.00301, 2019	27	2019
Efficient contextual bandits with continuous actions M Majzoubi, C Zhang, R Chari, A Krishnamurthy, J Langford, A Slivkins Advances in Neural Information Processing Systems 33, 349-360, 2020	26	2020
Improved algorithms for efficient active learning halfspaces with massart and tsybakov noise C Zhang, Y Li Conference on Learning Theory, 4526-4527, 2021	21	2021
Efficient Online Bandit Multiclass Learning with Regret A Beygelzimer, F Orabona, C Zhang International Conference on Machine Learning, 488-497, 2017	20	2017
The extended littlestone’s dimension for learning with mistakes and abstentions C Zhang, K Chaudhuri Conference on Learning Theory, 1584-1616, 2016	20	2016
Multitask bandit learning through heterogeneous feedback aggregation Z Wang, C Zhang, MK Singh, L Riek, K Chaudhuri International Conference on Artificial Intelligence and Statistics, 1531-1539, 2021	17*	2021
Active online learning with hidden shifting domains Y Chen, H Luo, T Ma, C Zhang International Conference on Artificial Intelligence and Statistics, 2053-2061, 2021	14*	2021
Crush optimism with pessimism: Structured bandits beyond asymptotic optimality KS Jun, C Zhang Advances in Neural Information Processing Systems 33, 6366-6376, 2020	14	2020
Provably efficient multi-task reinforcement learning with model transfer C Zhang, Z Wang Advances in Neural Information Processing Systems 34, 19771-19783, 2021	13	2021
Attribute-efficient learning of halfspaces with malicious noise: Near-optimal label complexity and noise tolerance J Shen, C Zhang Algorithmic Learning Theory, 1072-1113, 2021	11	2021
Active fairness auditing T Yan, C Zhang International Conference on Machine Learning, 24929-24962, 2022	10	2022
Bandit multiclass linear classification: Efficient algorithms for the separable case A Beygelzimer, D Pal, B Szorenyi, D Thiruvenkatachari, CY Wei, C Zhang International Conference on Machine Learning, 624-633, 2019	10	2019

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