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2020 – today
- 2024
[c16]Lee Cohen, Yishay Mansour, Shay Moran, Han Shao:
Learnability Gaps of Strategic Classification. COLT 2024: 1223-1259- [c15]Lee Cohen, Han Shao:
Incentivized Collaboration in Active Learning. FORC 2024: 2:1-2:20 - [i15]Lee Cohen, Yishay Mansour, Shay Moran, Han Shao:
Learnability Gaps of Strategic Classification. CoRR abs/2402.19303 (2024) - [i14]Han Shao:
Trustworthy Machine Learning under Social and Adversarial Data Sources. CoRR abs/2408.01596 (2024) - 2023
- [j6]Han Shao
, Libo Huang, Dominik L. Michels:
A Current Loop Model for the Fast Simulation of Ferrofluids. IEEE Trans. Vis. Comput. Graph. 29(12): 5394-5405 (2023) - [c14]Tarun Narayan, Mary-Kate Reidy, Sarah Heelan, Alan O'Riordan, Han Shao:
Real-Time Electrochemical Sensor for Phosphate Sensing in Water. SENSORS 2023: 1-4 - [c13]Han Shao, Lee Cohen, Avrim Blum, Yishay Mansour, Aadirupa Saha, Matthew R. Walter:
Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback. NeurIPS 2023 - [c12]Han Shao, Avrim Blum, Omar Montasser:
Strategic Classification under Unknown Personalized Manipulation. NeurIPS 2023 - [i13]Han Shao, Lee Cohen, Avrim Blum, Yishay Mansour, Aadirupa Saha, Matthew R. Walter:
Eliciting User Preferences for Personalized Multi-Objective Decision Making through Comparative Feedback. CoRR abs/2302.03805 (2023) - [i12]Han Shao, Avrim Blum, Omar Montasser:
Strategic Classification under Unknown Personalized Manipulation. CoRR abs/2305.16501 (2023) - [i11]Lee Cohen, Han Shao:
Incentivized Collaboration in Active Learning. CoRR abs/2311.00260 (2023) - [i10]Natalie Collina, Aaron Roth, Han Shao:
Efficient Prior-Free Mechanisms for No-Regret Agents. CoRR abs/2311.07754 (2023) - [i9]Minbiao Han, Kumar Kshitij Patel, Han Shao, Lingxiao Wang:
On the Effect of Defections in Federated Learning and How to Prevent Them. CoRR abs/2311.16459 (2023) - 2022
- [j5]Yange Sun, Han Shao, Bencai Zhang:
Ensemble based on accuracy and diversity weighting for evolving data streams. Int. Arab J. Inf. Technol. 19(1): 90-96 (2022) - [j4]Han Shao, Libo Huang, Dominik L. Michels:
A fast unsmoothed aggregation algebraic multigrid framework for the large-scale simulation of incompressible flow. ACM Trans. Graph. 41(4): 49:1-49:18 (2022) - [c11]Han Shao, Xiang Li, Guodi Wang:
Are You Tired? I am: Trying to Understand Privacy Fatigue of Social Media Users. CHI Extended Abstracts 2022: 378:1-378:7 - [c10]Han Shao, Zhencai Chen:
Application of Artificial Intelligence in Drug Detoxification. ISAIMS 2022: 547-550 - [c9]Han Shao, Omar Montasser, Avrim Blum:
A Theory of PAC Learnability under Transformation Invariances. NeurIPS 2022 - [i8]Han Shao, Omar Montasser, Avrim Blum:
A Theory of PAC Learnability under Transformation Invariances. CoRR abs/2202.07552 (2022) - 2021
- [j3]Yange Sun, Meng Li, Lei Li, Han Shao, Yi Sun:
Cost-Sensitive Classification for Evolving Data Streams with Concept Drift and Class Imbalance. Comput. Intell. Neurosci. 2021: 8813806:1-8813806:9 (2021) - [j2]Robert Daly, Tarun Narayan, Han Shao, Alan O'Riordan, Pierre Lovera:
Platinum-Based Interdigitated Micro-Electrode Arrays for Reagent-Free Detection of Copper. Sensors 21(10): 3544 (2021) - [c8]Han Shao:
Do I Prefer It?: The Role of Cultural Heuristics in Chinese Citizens' Attitudes to COVID-19 Rumors. CHI Extended Abstracts 2021: 414:1-414:6 - [c7]Avrim Blum, Steve Hanneke, Jian Qian, Han Shao:
Robust learning under clean-label attack. COLT 2021: 591-634 - [c6]Avrim Blum, Nika Haghtalab, Richard Lanas Phillips, Han Shao:
One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning. ICML 2021: 1005-1014 - [c5]Han Shao, Tassilo Kugelstadt, Torsten Hädrich, Wojtek Palubicki, Jan Bender, Sören Pirk, Dominik L. Michels:
Accurately Solving Rod Dynamics with Graph Learning. NeurIPS 2021: 4829-4842 - [i7]Avrim Blum, Steve Hanneke, Jian Qian, Han Shao:
Robust learning under clean-label attack. CoRR abs/2103.00671 (2021) - [i6]Avrim Blum, Nika Haghtalab, Richard Lanas Phillips, Han Shao:
One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning. CoRR abs/2103.03228 (2021) - 2020
- [c4]Rémy Degenne, Han Shao, Wouter M. Koolen:
Structure Adaptive Algorithms for Stochastic Bandits. ICML 2020: 2443-2452 - [c3]Avrim Blum, Han Shao:
Online Learning with Primary and Secondary Losses. NeurIPS 2020 - [i5]Han Shao, Tassilo Kugelstadt, Wojciech Palubicki, Jan Bender, Sören Pirk, Dominik L. Michels:
Accurately Solving Physical Systems with Graph Learning. CoRR abs/2006.03897 (2020) - [i4]Rémy Degenne, Han Shao, Wouter M. Koolen:
Structure Adaptive Algorithms for Stochastic Bandits. CoRR abs/2007.00969 (2020) - [i3]Xuedong Shang, Han Shao, Jian Qian:
Stochastic Bandits with Vector Losses: Minimizing 𝓁∞-Norm of Relative Losses. CoRR abs/2010.08061 (2020) - [i2]Avrim Blum, Han Shao:
Online Learning with Primary and Secondary Losses. CoRR abs/2010.14670 (2020)
2010 – 2019
- 2019
- [j1]Yange Sun, Han Shao, Shasha Wang:
Efficient Ensemble Classification for Multi-Label Data Streams with Concept Drift. Inf. 10(5): 158 (2019) - 2018
- [c2]Han Shao, Xiaotian Yu, Irwin King, Michael R. Lyu:
Almost Optimal Algorithms for Linear Stochastic Bandits with Heavy-Tailed Payoffs. NeurIPS 2018: 8430-8439 - [c1]Xiaotian Yu, Han Shao, Michael R. Lyu, Irwin King:
Pure Exploration of Multi-Armed Bandits with Heavy-Tailed Payoffs. UAI 2018: 937-946 - [i1]Han Shao, Xiaotian Yu, Irwin King, Michael R. Lyu:
Almost Optimal Algorithms for Linear Stochastic Bandits with Heavy-Tailed Payoffs. CoRR abs/1810.10895 (2018)
Coauthor Index
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last updated on 2024-10-07 22:12 CEST by the dblp team
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