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ORCIDGoran Radanovic
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- affiliation: Max Planck Institute for Software Systems, Saarbrücken, Germany
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2020 – today
- 2025
[c37]Vasilis Pollatos, Debmalya Mandal, Goran Radanovic:
On Corruption-Robustness in Performative Reinforcement Learning. AAAI 2025: 19939-19947- [c36]Jonathan Nöther, Adish Singla, Goran Radanovic:
Text-Diffusion Red-Teaming of Large Language Models: Unveiling Harmful Behaviors with Proximity Constraints. AAAI 2025: 27547-27555 - [i34]Jonathan Nöther, Adish Singla, Goran Radanovic:
Text-Diffusion Red-Teaming of Large Language Models: Unveiling Harmful Behaviors with Proximity Constraints. CoRR abs/2501.08246 (2025) - [i33]Debmalya Mandal, Paulius Sasnauskas, Goran Radanovic:
Distributionally Robust Reinforcement Learning with Human Feedback. CoRR abs/2503.00539 (2025) - [i32]Andi Nika, Jonathan Nöther, Debmalya Mandal, Parameswaran Kamalaruban, Adish Singla, Goran Radanovic:
Policy Teaching via Data Poisoning in Learning from Human Preferences. CoRR abs/2503.10228 (2025) - 2024
- [c35]Andi Nika, Debmalya Mandal, Adish Singla, Goran Radanovic:
Corruption-Robust Offline Two-Player Zero-Sum Markov Games. AISTATS 2024: 1243-1251 - [c34]Aleksa Sukovic, Goran Radanovic:
Reward Design for Justifiable Sequential Decision-Making. ICLR 2024 - [c33]Andi Nika, Debmalya Mandal, Parameswaran Kamalaruban, Georgios Tzannetos, Goran Radanovic, Adish Singla:
Reward Model Learning vs. Direct Policy Optimization: A Comparative Analysis of Learning from Human Preferences. ICML 2024 - [c32]Stelios Triantafyllou, Aleksa Sukovic, Debmalya Mandal, Goran Radanovic:
Agent-Specific Effects: A Causal Effect Propagation Analysis in Multi-Agent MDPs. ICML 2024 - [c31]Mridul Mahajan, Georgios Tzannetos, Goran Radanovic, Adish Singla:
Learning Embeddings for Sequential Tasks Using Population of Agents. IJCAI 2024: 4733-4741 - [c30]Ben Rank, Stelios Triantafyllou, Debmalya Mandal, Goran Radanovic:
Performative Reinforcement Learning in Gradually Shifting Environments. UAI 2024: 3041-3075 - [i31]Debmalya Mandal, Andi Nika, Parameswaran Kamalaruban, Adish Singla, Goran Radanovic:
Corruption Robust Offline Reinforcement Learning with Human Feedback. CoRR abs/2402.06734 (2024) - [i30]Ben Rank, Stelios Triantafyllou, Debmalya Mandal, Goran Radanovic:
Performative Reinforcement Learning in Gradually Shifting Environments. CoRR abs/2402.09838 (2024) - [i29]Aleksa Sukovic, Goran Radanovic:
Reward Design for Justifiable Sequential Decision-Making. CoRR abs/2402.15826 (2024) - [i28]Andi Nika, Debmalya Mandal, Parameswaran Kamalaruban, Georgios Tzannetos, Goran Radanovic, Adish Singla:
Reward Model Learning vs. Direct Policy Optimization: A Comparative Analysis of Learning from Human Preferences. CoRR abs/2403.01857 (2024) - [i27]Andi Nika, Debmalya Mandal, Adish Singla, Goran Radanovic:
Corruption-Robust Offline Two-Player Zero-Sum Markov Games. CoRR abs/2403.07933 (2024) - [i26]Stelios Triantafyllou, Aleksa Sukovic, Yasaman Zolfimoselo, Goran Radanovic:
Counterfactual Effect Decomposition in Multi-Agent Sequential Decision Making. CoRR abs/2410.12539 (2024) - [i25]Debmalya Mandal, Goran Radanovic:
Performative Reinforcement Learning with Linear Markov Decision Process. CoRR abs/2411.05234 (2024) - 2023
- [j6]Kiarash Banihashem, Adish Singla, Goran Radanovic:
Defense Against Reward Poisoning Attacks in Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c29]Debmalya Mandal, Goran Radanovic, Jiarui Gan, Adish Singla, Rupak Majumdar:
Online Reinforcement Learning with Uncertain Episode Lengths. AAAI 2023: 9064-9071 - [c28]Jiarui Gan, Annika Hennes, Rupak Majumdar, Debmalya Mandal, Goran Radanovic:
Markov Decision Processes with Time-Varying Geometric Discounting. AAAI 2023: 11980-11988 - [c27]Andi Nika, Adish Singla, Goran Radanovic:
Online Defense Strategies for Reinforcement Learning Against Adaptive Reward Poisoning. AISTATS 2023: 335-358 - [c26]Stelios Triantafyllou, Goran Radanovic:
Towards Computationally Efficient Responsibility Attribution in Decentralized Partially Observable MDPs. AAMAS 2023: 131-139 - [c25]Mohammad Mohammadi, Jonathan Nöther, Debmalya Mandal, Adish Singla, Goran Radanovic:
Implicit Poisoning Attacks in Two-Agent Reinforcement Learning: Adversarial Policies for Training-Time Attacks. AAMAS 2023: 1835-1844 - [c24]Debmalya Mandal, Stelios Triantafyllou, Goran Radanovic:
Performative Reinforcement Learning. ICML 2023: 23642-23680 - [i24]Debmalya Mandal, Goran Radanovic, Jiarui Gan, Adish Singla, Rupak Majumdar:
Online Reinforcement Learning with Uncertain Episode Lengths. CoRR abs/2302.03608 (2023) - [i23]Stelios Triantafyllou, Goran Radanovic:
Towards Computationally Efficient Responsibility Attribution in Decentralized Partially Observable MDPs. CoRR abs/2302.12676 (2023) - [i22]Mohammad Mohammadi, Jonathan Nöther, Debmalya Mandal, Adish Singla, Goran Radanovic:
Implicit Poisoning Attacks in Two-Agent Reinforcement Learning: Adversarial Policies for Training-Time Attacks. CoRR abs/2302.13851 (2023) - [i21]Mridul Mahajan, Georgios Tzannetos, Goran Radanovic, Adish Singla:
Learning Embeddings for Sequential Tasks Using Population of Agents. CoRR abs/2306.03311 (2023) - [i20]Jiarui Gan, Rupak Majumdar, Debmalya Mandal, Goran Radanovic:
Sequential Principal-Agent Problems with Communication: Efficient Computation and Learning. CoRR abs/2306.03832 (2023) - [i19]Jiarui Gan, Annika Hennes, Rupak Majumdar, Debmalya Mandal, Goran Radanovic:
Markov Decision Processes with Time-Varying Geometric Discounting. CoRR abs/2307.10491 (2023) - [i18]Stelios Triantafyllou, Aleksa Sukovic, Debmalya Mandal, Goran Radanovic:
Agent-Specific Effects. CoRR abs/2310.11334 (2023) - 2022
- [c23]Jiarui Gan, Rupak Majumdar, Goran Radanovic, Adish Singla:
Bayesian Persuasion in Sequential Decision-Making. AAAI 2022: 5025-5033 - [c22]Kiarash Banihashem, Adish Singla, Jiarui Gan, Goran Radanovic:
Admissible Policy Teaching through Reward Design. AAAI 2022: 6037-6045 - [c21]Stelios Triantafyllou, Adish Singla, Goran Radanovic:
Actual Causality and Responsibility Attribution in Decentralized Partially Observable Markov Decision Processes. AIES 2022: 739-752 - [c20]Jiarui Gan, Rupak Majumdar, Goran Radanovic, Adish Singla:
Sequential Decision Making With Information Asymmetry (Invited Talk). CONCUR 2022: 4:1-4:18 - [c19]Jiarui Gan, Rupak Majumdar, Adish Singla, Goran Radanovic:
Envy-free Policy Teaching to Multiple Agents. NeurIPS 2022 - [i17]Kiarash Banihashem, Adish Singla, Jiarui Gan, Goran Radanovic:
Admissible Policy Teaching through Reward Design. CoRR abs/2201.02185 (2022) - [i16]Stelios Triantafyllou, Adish Singla, Goran Radanovic:
Actual Causality and Responsibility Attribution in Decentralized Partially Observable Markov Decision Processes. CoRR abs/2204.00302 (2022) - [i15]Debmalya Mandal, Stelios Triantafyllou, Goran Radanovic:
Performative Reinforcement Learning. CoRR abs/2207.00046 (2022) - 2021
- [j5]Abraham Bernstein, Claes H. de Vreese, Natali Helberger
, Wolfgang Schulz, Katharina Anna Zweig, Christian Baden, Michael A. Beam, Marc P. Hauer, Lucien Heitz, Pascal Jürgens, Christian Katzenbach, Benjamin Kille, Beate Klimkiewicz, Wiebke Loosen, Judith Möller, Goran Radanovic, Guy Shani, Nava Tintarev, Suzanne Tolmeijer, Wouter van Atteveldt, Sanne Vrijenhoek, Theresa Zueger:
Diversity in News Recommendation (Dagstuhl Perspectives Workshop 19482). Dagstuhl Manifestos 9(1): 43-61 (2021) - [j4]Amin Rakhsha, Goran Radanovic, Rati Devidze, Xiaojin Zhu, Adish Singla:
Policy Teaching in Reinforcement Learning via Environment Poisoning Attacks. J. Mach. Learn. Res. 22: 210:1-210:45 (2021) - [c18]Paul Tylkin, Goran Radanovic, David C. Parkes:
Learning Robust Helpful Behaviors in Two-Player Cooperative Atari Environments. AAMAS 2021: 1686-1688 - [c17]Stelios Triantafyllou, Adish Singla, Goran Radanovic:
On Blame Attribution for Accountable Multi-Agent Sequential Decision Making. NeurIPS 2021: 15774-15786 - [c16]Rati Devidze, Goran Radanovic, Parameswaran Kamalaruban, Adish Singla:
Explicable Reward Design for Reinforcement Learning Agents. NeurIPS 2021: 20118-20131 - [i14]Kiarash Banihashem, Adish Singla, Goran Radanovic:
Defense Against Reward Poisoning Attacks in Reinforcement Learning. CoRR abs/2102.05776 (2021) - [i13]Jiarui Gan, Rupak Majumdar, Goran Radanovic, Adish Singla:
Bayesian Persuasion in Sequential Decision-Making. CoRR abs/2106.05137 (2021) - [i12]Adish Singla, Anna N. Rafferty, Goran Radanovic, Neil T. Heffernan:
Reinforcement Learning for Education: Opportunities and Challenges. CoRR abs/2107.08828 (2021) - [i11]Stelios Triantafyllou, Adish Singla, Goran Radanovic:
On Blame Attribution for Accountable Multi-Agent Sequential Decision Making. CoRR abs/2107.11927 (2021) - 2020
- [j3]Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu:
How do fairness definitions fare? Testing public attitudes towards three algorithmic definitions of fairness in loan allocations. Artif. Intell. 283: 103238 (2020) - [c15]Debmalya Mandal, Goran Radanovic, David C. Parkes:
The Effectiveness of Peer Prediction in Long-Term Forecasting. AAAI 2020: 2160-2167 - [c14]Amin Rakhsha, Goran Radanovic, Rati Devidze, Xiaojin Zhu, Adish Singla:
Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement Learning. ICML 2020: 7974-7984 - [i10]Amin Rakhsha, Goran Radanovic, Rati Devidze, Xiaojin Zhu, Adish Singla:
Policy Teaching via Environment Poisoning: Training-time Adversarial Attacks against Reinforcement Learning. CoRR abs/2003.12909 (2020) - [i9]Abraham Bernstein, Claes H. de Vreese, Natali Helberger, Wolfgang Schulz, Katharina Anna Zweig, Christian Baden, Michael A. Beam, Marc P. Hauer, Lucien Heitz, Pascal Jürgens, Christian Katzenbach, Benjamin Kille, Beate Klimkiewicz, Wiebke Loosen, Judith Möller, Goran Radanovic, Guy Shani, Nava Tintarev, Suzanne Tolmeijer, Wouter van Atteveldt, Sanne Vrijenhoek, Theresa Zueger:
Diversity in News Recommendations. CoRR abs/2005.09495 (2020) - [i8]Amin Rakhsha, Goran Radanovic, Rati Devidze, Xiaojin Zhu, Adish Singla:
Policy Teaching in Reinforcement Learning via Environment Poisoning Attacks. CoRR abs/2011.10824 (2020)
2010 – 2019
- 2019
- [c13]Christos Dimitrakakis, Yang Liu, David C. Parkes, Goran Radanovic:
Bayesian Fairness. AAAI 2019: 509-516 - [c12]Nripsuta Ani Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu:
How Do Fairness Definitions Fare?: Examining Public Attitudes Towards Algorithmic Definitions of Fairness. AIES 2019: 99-106 - [c11]Goran Radanovic, Rati Devidze, David C. Parkes, Adish Singla:
Learning to Collaborate in Markov Decision Processes. ICML 2019: 5261-5270 - [i7]Goran Radanovic, Rati Devidze, David C. Parkes, Adish Singla:
Learning to Collaborate in Markov Decision Processes. CoRR abs/1901.08029 (2019) - 2018
- [c10]Goran Radanovic, Boi Faltings:
Partial Truthfulness in Minimal Peer Prediction Mechanisms With Limited Knowledge. AAAI 2018: 1595-1602 - [c9]Goran Radanovic, Adish Singla, Andreas Krause, Boi Faltings:
Information Gathering With Peers: Submodular Optimization With Peer-Prediction Constraints. AAAI 2018: 1603-1610 - [i6]Nripsuta Saxena, Karen Huang, Evan DeFilippis, Goran Radanovic, David C. Parkes, Yang Liu:
How Do Fairness Definitions Fare? Examining Public Attitudes Towards Algorithmic Definitions of Fairness. CoRR abs/1811.03654 (2018) - 2017
- [b2]Boi Faltings, Goran Radanovic:
Game Theory for Data Science: Eliciting Truthful Information. Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers 2017, ISBN 978-3-031-00449-0 - [j2]Boi Faltings, Goran Radanovic:
Mechanismen zur Beschaffung korrekter Daten. Inform. Spektrum 40(1): 64-74 (2017) - [c8]Christos Dimitrakakis, David C. Parkes, Goran Radanovic, Paul Tylkin:
Multi-View Decision Processes: The Helper-AI Problem. NIPS 2017: 5443-5452 - [i5]Boi Faltings, Radu Jurca, Goran Radanovic:
Peer Truth Serum: Incentives for Crowdsourcing Measurements and Opinions. CoRR abs/1704.05269 (2017) - [i4]Christos Dimitrakakis, Yang Liu, David C. Parkes, Goran Radanovic:
Subjective fairness: Fairness is in the eye of the beholder. CoRR abs/1706.00119 (2017) - [i3]Yang Liu, Goran Radanovic, Christos Dimitrakakis, Debmalya Mandal, David C. Parkes:
Calibrated Fairness in Bandits. CoRR abs/1707.01875 (2017) - [i2]Goran Radanovic, Boi Faltings:
Partial Truthfulness in Minimal Peer Prediction Mechanisms with Limited Knowledge. CoRR abs/1711.06614 (2017) - [i1]Goran Radanovic, Adish Singla, Andreas Krause, Boi Faltings:
Information Gathering with Peers: Submodular Optimization with Peer-Prediction Constraints. CoRR abs/1711.06740 (2017) - 2016
- [b1]Goran Radanovic:
Elicitation and Aggregation of Crowd Information. EPFL, Switzerland, 2016 - [j1]Goran Radanovic, Boi Faltings, Radu Jurca:
Incentives for Effort in Crowdsourcing Using the Peer Truth Serum. ACM Trans. Intell. Syst. Technol. 7(4): 48:1-48:28 (2016) - [c7]Goran Radanovic, Boi Faltings:
Limiting the Influence of Low Quality Information in Community Sensing. AAMAS 2016: 873-881 - [c6]Goran Radanovic, Boi Faltings:
Learning to Scale Payments in Crowdsourcing with PropeRBoost. HCOMP 2016: 179-188 - 2015
- [c5]Goran Radanovic, Boi Faltings:
Incentives for Subjective Evaluations with Private Beliefs. AAAI 2015: 1014-1020 - [c4]Goran Radanovic, Boi Faltings:
Incentive Schemes for Participatory Sensing. AAMAS 2015: 1081-1089 - [c3]Goran Radanovic, Boi Faltings:
Incentivizing truthful responses with the logarithmic peer truth serum. UbiComp/ISWC Adjunct 2015: 1349-1354 - 2014
- [c2]Goran Radanovic, Boi Faltings:
Incentives for Truthful Information Elicitation of Continuous Signals. AAAI 2014: 770-776 - 2013
- [c1]Goran Radanovic, Boi Faltings:
A Robust Bayesian Truth Serum for Non-Binary Signals. AAAI 2013: 833-839
Coauthor Index
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