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2020 – today
- 2024
[j8]Stratis Tsirtsis
, Behzad Tabibian, Moein Khajehnejad, Adish Singla, Bernhard Schölkopf, Manuel Gomez-Rodriguez:
Optimal Decision Making Under Strategic Behavior. Manag. Sci. 70(12): 8506-8519 (2024)- [j7]Victor-Alexandru Padurean, Georgios Tzannetos, Adish Singla:
Neural Task Synthesis for Visual Programming. Trans. Mach. Learn. Res. 2024 (2024) - [c90]Chao Wen, Ahana Ghosh, Jacqueline Staub, Adish Singla:
Task Synthesis for Elementary Visual Programming in XLogoOnline Environment. AIED Companion (2) 2024: 308-316 - [c89]Andi Nika, Debmalya Mandal, Adish Singla, Goran Radanovic:
Corruption-Robust Offline Two-Player Zero-Sum Markov Games. AISTATS 2024: 1243-1251 - [c88]Rati Devidze, Parameswaran Kamalaruban, Adish Singla:
Informativeness of Reward Functions in Reinforcement Learning. AAMAS 2024: 444-452 - [c87]Neil T. Heffernan, Rose E. Wang, Christopher MacLellan, Arto Hellas, Chenglu Li, Candace Walkington, Joshua Littenberg-Tobias, David Joyner, Steven Moore, Adish Singla, Zach A. Pardos, Maciej Pankiewicz, Juho Kim, Shashank Sonkar, Clayton Cohn, Anthony Botelho, Andrew Lan, Lan Jiang, Mingyu Feng, Tanja Käser, Eamon Worden:
Leveraging Large Language Models for Next-Generation Educational Technologies. EDM 2024 - [c86]Manh Hung Nguyen, Sebastian Tschiatschek, Adish Singla:
Large Language Models for In-Context Student Modeling: Synthesizing Student's Behavior in Visual Programming. EDM 2024 - [c85]Bahar Radmehr, Adish Singla, Tanja Käser:
Towards Generalizable Agents in Text-Based Educational Environments: A Study of Integrating RL with LLMs. EDM 2024 - [c84]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 - [c83]Mridul Mahajan, Georgios Tzannetos, Goran Radanovic, Adish Singla:
Learning Embeddings for Sequential Tasks Using Population of Agents. IJCAI 2024: 4733-4741 - [c82]Georgios Tzannetos, Parameswaran Kamalaruban, Adish Singla:
Proximal Curriculum with Task Correlations for Deep Reinforcement Learning. IJCAI 2024: 5027-5036 - [c81]Tung Phung, Victor-Alexandru Padurean, Anjali Singh, Christopher Brooks, José Cambronero, Sumit Gulwani, Adish Singla, Gustavo Soares:
Automating Human Tutor-Style Programming Feedback: Leveraging GPT-4 Tutor Model for Hint Generation and GPT-3.5 Student Model for Hint Validation. LAK 2024: 12-23 - [c80]Ahana Ghosh, Liina Malva, Adish Singla:
Analyzing-Evaluating-Creating: Assessing Computational Thinking and Problem Solving in Visual Programming Domains. SIGCSE (1) 2024: 387-393 - [e1]Juan D. Pinto, Eamon Worden, Anthony Botelho, Lea Cohausz, Clayton Cohn, Mingyu Feng, Neil T. Heffernan, Arto Hellas, Lan Jiang, David Joyner, Tanja Käser, Juho Kim, Andrew Lan, Chenglu Li, Joshua Littenberg-Tobias, Qianhui Liu, Christopher MacLellan, Steven Moore, Maciej Pankiewicz, Luc Paquette, Zach A. Pardos, Anna N. Rafferty, Adish Singla, Shashank Sonkar, Vinitra Swamy, Rose E. Wang, Candace Walkington:
Joint Proceedings of the Human-Centric eXplainable AI in Education and the Leveraging Large Language Models for Next Generation Educational Technologies Workshops (HEXED-L3MNGET 2024) co-located with 17th International Conference on Educational Data Mining (EDM 2024), Atlanta, Georgia, USA, July 14, 2024. CEUR Workshop Proceedings 3840, CEUR-WS.org 2024 [contents] - [i89]Paul Denny, Sumit Gulwani, Neil T. Heffernan, Tanja Käser, Steven Moore, Anna N. Rafferty, Adish Singla:
Generative AI for Education (GAIED): Advances, Opportunities, and Challenges. CoRR abs/2402.01580 (2024) - [i88]Debmalya Mandal, Andi Nika, Parameswaran Kamalaruban, Adish Singla, Goran Radanovic:
Corruption Robust Offline Reinforcement Learning with Human Feedback. CoRR abs/2402.06734 (2024) - [i87]Rati Devidze, Parameswaran Kamalaruban, Adish Singla:
Informativeness of Reward Functions in Reinforcement Learning. CoRR abs/2402.07019 (2024) - [i86]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) - [i85]Andi Nika, Debmalya Mandal, Adish Singla, Goran Radanovic:
Corruption-Robust Offline Two-Player Zero-Sum Markov Games. CoRR abs/2403.07933 (2024) - [i84]Ahana Ghosh, Liina Malva, Adish Singla:
Analyzing-Evaluating-Creating: Assessing Computational Thinking and Problem Solving in Visual Programming Domains. CoRR abs/2403.12227 (2024) - [i83]Bahar Radmehr, Adish Singla, Tanja Käser:
Towards Generalizable Agents in Text-Based Educational Environments: A Study of Integrating RL with LLMs. CoRR abs/2404.18978 (2024) - [i82]Chao Wen, Ahana Ghosh, Jacqueline Staub, Adish Singla:
Task Synthesis for Elementary Visual Programming in XLogoOnline Environment. CoRR abs/2405.02173 (2024) - [i81]Georgios Tzannetos, Parameswaran Kamalaruban, Adish Singla:
Proximal Curriculum with Task Correlations for Deep Reinforcement Learning. CoRR abs/2405.02481 (2024) - [i80]Nachiket Kotalwar, Alkis Gotovos, Adish Singla:
Hints-In-Browser: Benchmarking Language Models for Programming Feedback Generation. CoRR abs/2406.05053 (2024) - [i79]Victor-Alexandru Padurean, Adish Singla:
Benchmarking Generative Models on Computational Thinking Tests in Elementary Visual Programming. CoRR abs/2406.09891 (2024) - [i78]Chao Wen, Jacqueline Staub, Adish Singla:
Program Synthesis Benchmark for Visual Programming in XLogoOnline Environment. CoRR abs/2406.11334 (2024) - [i77]Ahana Ghosh, Liina Malva, Alkis Gotovos, Danial Hooshyar, Adish Singla:
Exploring the Impact of Quizzes Interleaved with Write-Code Tasks in Elementary-Level Visual Programming. CoRR abs/2411.14275 (2024) - [i76]Victor-Alexandru Padurean, Paul Denny, Adish Singla:
BugSpotter: Automated Generation of Code Debugging Exercises. CoRR abs/2411.14303 (2024) - [i75]Ruchit Rawal, Victor-Alexandru Padurean, Sven Apel, Adish Singla, Mariya Toneva:
Hints Help Finding and Fixing Bugs Differently in Python and Text-based Program Representations. CoRR abs/2412.12471 (2024) - 2023
- [j6]Junaid Ali, Mahmoudreza Babaei, Abhijnan Chakraborty, Baharan Mirzasoleiman, Krishna P. Gummadi, Adish Singla:
On the Fairness of Time-Critical Influence Maximization in Social Networks. IEEE Trans. Knowl. Data Eng. 35(3): 2875-2886 (2023) - [j5]Kiarash Banihashem, Adish Singla, Goran Radanovic:
Defense Against Reward Poisoning Attacks in Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023) - [j4]Georgios Tzannetos, Bárbara Gomes Ribeiro, Parameswaran Kamalaruban, Adish Singla:
Proximal Curriculum for Reinforcement Learning Agents. Trans. Mach. Learn. Res. 2023 (2023) - [c79]Debmalya Mandal, Goran Radanovic, Jiarui Gan, Adish Singla, Rupak Majumdar:
Online Reinforcement Learning with Uncertain Episode Lengths. AAAI 2023: 9064-9071 - [c78]Andi Nika, Adish Singla, Goran Radanovic:
Online Defense Strategies for Reinforcement Learning Against Adaptive Reward Poisoning. AISTATS 2023: 335-358 - [c77]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 - [c76]Tung Phung, José Cambronero, Sumit Gulwani, Tobias Kohn, Rupak Majumdar, Adish Singla, Gustavo Soares:
Generating High-Precision Feedback for Programming Syntax Errors using Large Language Models. EDM 2023 - [c75]Adish Singla:
Evaluating ChatGPT and GPT-4 for Visual Programming. ICER (2) 2023: 14-15 - [c74]Tung Phung, Victor-Alexandru Padurean, José Cambronero, Sumit Gulwani, Tobias Kohn, Rupak Majumdar, Adish Singla, Gustavo Soares:
Generative AI for Programming Education: Benchmarking ChatGPT, GPT-4, and Human Tutors. ICER (2) 2023: 41-42 - [c73]Maria Christakis, Hasan Ferit Eniser, Jörg Hoffmann, Adish Singla, Valentin Wüstholz:
Specifying and Testing k-Safety Properties for Machine-Learning Models. IJCAI 2023: 4748-4757 - [i74]Debmalya Mandal, Goran Radanovic, Jiarui Gan, Adish Singla, Rupak Majumdar:
Online Reinforcement Learning with Uncertain Episode Lengths. CoRR abs/2302.03608 (2023) - [i73]Tung Phung, José Cambronero, Sumit Gulwani, Tobias Kohn, Rupak Majumdar, Adish Singla, Gustavo Soares:
Generating High-Precision Feedback for Programming Syntax Errors using Large Language Models. CoRR abs/2302.04662 (2023) - [i72]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) - [i71]Ahana Ghosh, Sebastian Tschiatschek, Sam Devlin, Adish Singla:
Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes. CoRR abs/2303.16359 (2023) - [i70]Georgios Tzannetos, Bárbara Gomes Ribeiro, Parameswaran Kamalaruban, Adish Singla:
Proximal Curriculum for Reinforcement Learning Agents. CoRR abs/2304.12877 (2023) - [i69]Alperen Tercan, Ahana Ghosh, Hasan Ferit Eniser, Maria Christakis, Adish Singla:
Synthesizing a Progression of Subtasks for Block-Based Visual Programming Tasks. CoRR abs/2305.17518 (2023) - [i68]Victor-Alexandru Padurean, Georgios Tzannetos, Adish Singla:
Neural Task Synthesis for Visual Programming. CoRR abs/2305.18342 (2023) - [i67]Mridul Mahajan, Georgios Tzannetos, Goran Radanovic, Adish Singla:
Learning Embeddings for Sequential Tasks Using Population of Agents. CoRR abs/2306.03311 (2023) - [i66]Tung Phung, Victor-Alexandru Padurean, José Cambronero, Sumit Gulwani, Tobias Kohn, Rupak Majumdar, Adish Singla, Gustavo Soares:
Generative AI for Programming Education: Benchmarking ChatGPT, GPT-4, and Human Tutors. CoRR abs/2306.17156 (2023) - [i65]Adish Singla:
Evaluating ChatGPT and GPT-4 for Visual Programming. CoRR abs/2308.02522 (2023) - [i64]Tung Phung, Victor-Alexandru Padurean, Anjali Singh, Christopher Brooks, José Cambronero, Sumit Gulwani, Adish Singla, Gustavo Soares:
Automating Human Tutor-Style Programming Feedback: Leveraging GPT-4 Tutor Model for Hint Generation and GPT-3.5 Student Model for Hint Validation. CoRR abs/2310.03780 (2023) - [i63]Manh Hung Nguyen, Sebastian Tschiatschek, Adish Singla:
Large Language Models for In-Context Student Modeling: Synthesizing Student's Behavior in Visual Programming from One-Shot Observation. CoRR abs/2310.10690 (2023) - [i62]Shubham Kumar Bharti, Stephen Wright, Adish Singla, Xiaojin Zhu:
Optimally Teaching a Linear Behavior Cloning Agent. CoRR abs/2311.15399 (2023) - [i61]Timo Klein, Susanna Weinberger, Adish Singla, Sebastian Tschiatschek:
Active Third-Person Imitation Learning. CoRR abs/2312.16365 (2023) - 2022
- [j3]Vahid Balazadeh Meresht, Abir De, Adish Singla, Manuel Gomez Rodriguez:
Learning to Switch Among Agents in a Team. Trans. Mach. Learn. Res. 2022 (2022) - [c72]Jiarui Gan, Rupak Majumdar, Goran Radanovic, Adish Singla:
Bayesian Persuasion in Sequential Decision-Making. AAAI 2022: 5025-5033 - [c71]Kiarash Banihashem, Adish Singla, Jiarui Gan, Goran Radanovic:
Admissible Policy Teaching through Reward Design. AAAI 2022: 6037-6045 - [c70]Ahana Ghosh, Sebastian Tschiatschek, Sam Devlin, Adish Singla:
Adaptive Scaffolding in Block-Based Programming via Synthesizing New Tasks as Pop Quizzes. AIED (1) 2022: 28-40 - [c69]Stelios Triantafyllou, Adish Singla, Goran Radanovic:
Actual Causality and Responsibility Attribution in Decentralized Partially Observable Markov Decision Processes. AIES 2022: 739-752 - [c68]Jiarui Gan, Rupak Majumdar, Goran Radanovic, Adish Singla:
Sequential Decision Making With Information Asymmetry (Invited Talk). CONCUR 2022: 4:1-4:18 - [c67]Adish Singla, Nikitas Theodoropoulos:
From Solution Synthesis to Student Attempt Synthesis for Block-Based Visual Programming Tasks. EDM 2022 - [c66]Sebastian Tschiatschek, Maria Knobelsdorf, Adish Singla:
Equity and Fairness of Bayesian Knowledge Tracing. EDM 2022 - [c65]Junaid Ali, Mahmoudreza Babaei, Abhijnan Chakraborty, Baharan Mirzasoleiman, Krishna P. Gummadi, Adish Singla:
On the Fairness of Time-Critical Influence Maximization in Social Networks (Extended Abstract). ICDE 2022: 1541-1542 - [c64]Shubham Kumar Bharti, Xuezhou Zhang, Adish Singla, Jerry Zhu:
Provable Defense against Backdoor Policies in Reinforcement Learning. NeurIPS 2022 - [c63]Rati Devidze, Parameswaran Kamalaruban, Adish Singla:
Exploration-Guided Reward Shaping for Reinforcement Learning under Sparse Rewards. NeurIPS 2022 - [c62]Jiarui Gan, Rupak Majumdar, Adish Singla, Goran Radanovic:
Envy-free Policy Teaching to Multiple Agents. NeurIPS 2022 - [c61]Farnam Mansouri, Hans Simon, Adish Singla, Sandra Zilles:
On Batch Teaching with Sample Complexity Bounded by VCD. NeurIPS 2022 - [i60]Kiarash Banihashem, Adish Singla, Jiarui Gan, Goran Radanovic:
Admissible Policy Teaching through Reward Design. CoRR abs/2201.02185 (2022) - [i59]Stelios Triantafyllou, Adish Singla, Goran Radanovic:
Actual Causality and Responsibility Attribution in Decentralized Partially Observable Markov Decision Processes. CoRR abs/2204.00302 (2022) - [i58]Adish Singla, Nikitas Theodoropoulos:
From {Solution Synthesis} to {Student Attempt Synthesis} for Block-Based Visual Programming Tasks. CoRR abs/2205.01265 (2022) - [i57]Sebastian Tschiatschek, Maria Knobelsdorf, Adish Singla:
Equity and Fairness of Bayesian Knowledge Tracing. CoRR abs/2205.02333 (2022) - [i56]Maria Christakis, Hasan Ferit Eniser, Jörg Hoffmann, Adish Singla, Valentin Wüstholz:
Specifying and Testing k-Safety Properties for Machine-Learning Models. CoRR abs/2206.06054 (2022) - [i55]Shubham Kumar Bharti, Xuezhou Zhang, Adish Singla, Xiaojin Zhu:
Provable Defense against Backdoor Policies in Reinforcement Learning. CoRR abs/2211.10530 (2022) - 2021
- [j2]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) - [c60]Xuezhou Zhang, Shubham Kumar Bharti, Yuzhe Ma, Adish Singla, Xiaojin Zhu:
The Sample Complexity of Teaching by Reinforcement on Q-Learning. AAAI 2021: 10939-10947 - [c59]Anshuman Chhabra, Adish Singla, Prasant Mohapatra:
Fair Clustering Using Antidote Data. AFCR 2021: 19-39 - [c58]Akash Kumar, Hanqi Zhang, Adish Singla, Yuxin Chen:
The Teaching Dimension of Kernel Perceptron. AISTATS 2021: 2071-2079 - [c57]Joy He-Yueya, Adish Singla:
Quizzing Policy Using Reinforcement Learning for Inferring the Student Knowledge State. EDM 2021 - [c56]Gaurav Yengera, Rati Devidze, Parameswaran Kamalaruban, Adish Singla:
Curriculum Design for Teaching via Demonstrations: Theory and Applications. NeurIPS 2021: 10496-10509 - [c55]Stelios Triantafyllou, Adish Singla, Goran Radanovic:
On Blame Attribution for Accountable Multi-Agent Sequential Decision Making. NeurIPS 2021: 15774-15786 - [c54]Chaoqi Wang, Adish Singla, Yuxin Chen:
Teaching an Active Learner with Contrastive Examples. NeurIPS 2021: 17968-17980 - [c53]Rati Devidze, Goran Radanovic, Parameswaran Kamalaruban, Adish Singla:
Explicable Reward Design for Reinforcement Learning Agents. NeurIPS 2021: 20118-20131 - [c52]Akash Kumar, Yuxin Chen, Adish Singla:
Teaching via Best-Case Counterexamples in the Learning-with-Equivalence-Queries Paradigm. NeurIPS 2021: 26897-26910 - [i54]Kiarash Banihashem, Adish Singla, Goran Radanovic:
Defense Against Reward Poisoning Attacks in Reinforcement Learning. CoRR abs/2102.05776 (2021) - [i53]Amin Rakhsha, Xuezhou Zhang, Xiaojin Zhu, Adish Singla:
Reward Poisoning in Reinforcement Learning: Attacks Against Unknown Learners in Unknown Environments. CoRR abs/2102.08492 (2021) - [i52]Junaid Ali, Muhammad Bilal Zafar, Adish Singla, Krishna P. Gummadi:
Loss-Aversively Fair Classification. CoRR abs/2105.04273 (2021) - [i51]Anshuman Chhabra, Adish Singla, Prasant Mohapatra:
Fair Clustering Using Antidote Data. CoRR abs/2106.00600 (2021) - [i50]Gaurav Yengera, Rati Devidze, Parameswaran Kamalaruban, Adish Singla:
Curriculum Design for Teaching via Demonstrations: Theory and Applications. CoRR abs/2106.04696 (2021) - [i49]Jiarui Gan, Rupak Majumdar, Goran Radanovic, Adish Singla:
Bayesian Persuasion in Sequential Decision-Making. CoRR abs/2106.05137 (2021) - [i48]Adish Singla, Anna N. Rafferty, Goran Radanovic, Neil T. Heffernan:
Reinforcement Learning for Education: Opportunities and Challenges. CoRR abs/2107.08828 (2021) - [i47]Stelios Triantafyllou, Adish Singla, Goran Radanovic:
On Blame Attribution for Accountable Multi-Agent Sequential Decision Making. CoRR abs/2107.11927 (2021) - [i46]Eleni Straitouri, Adish Singla, Vahid Balazadeh Meresht, Manuel Gomez-Rodriguez:
Reinforcement Learning Under Algorithmic Triage. CoRR abs/2109.11328 (2021) - [i45]Anshuman Chhabra, Adish Singla, Prasant Mohapatra:
Fairness Degrading Adversarial Attacks Against Clustering Algorithms. CoRR abs/2110.12020 (2021) - [i44]Chaoqi Wang, Adish Singla, Yuxin Chen:
Teaching an Active Learner with Contrastive Examples. CoRR abs/2110.14888 (2021) - 2020
- [c51]Ahana Ghosh, Sebastian Tschiatschek, Hamed Mahdavi, Adish Singla:
Towards Deployment of Robust Cooperative AI Agents: An Algorithmic Framework for Learning Adaptive Policies. AAMAS 2020: 447-455 - [c50]Aleksandr Efremov, Ahana Ghosh, Adish Singla:
Zero-shot Learning of Hint Policy via Reinforcement Learning and Program Synthesis. EDM 2020 - [c49]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 - [c48]Xuezhou Zhang, Yuzhe Ma, Adish Singla, Xiaojin Zhu:
Adaptive Reward-Poisoning Attacks against Reinforcement Learning. ICML 2020: 11225-11234 - [c47]Rati Devidze, Farnam Mansouri, Luis Haug, Yuxin Chen, Adish Singla:
Understanding the Power and Limitations of Teaching with Imperfect Knowledge. IJCAI 2020: 2647-2654 - [c46]Umair Z. Ahmed, Maria Christakis, Aleksandr Efremov, Nigel Fernandez, Ahana Ghosh, Abhik Roychoudhury, Adish Singla:
Synthesizing Tasks for Block-based Programming. NeurIPS 2020 - [c45]Xuezhou Zhang, Yuzhe Ma, Adish Singla:
Task-agnostic Exploration in Reinforcement Learning. NeurIPS 2020 - [c44]Abir De, Adish Singla, Utkarsh Upadhyay, Manuel Gomez-Rodriguez:
Can A User Guess What Her Followers Want? WSDM 2020: 142-150 - [i43]Vahid Balazadeh Meresht, Abir De, Adish Singla, Manuel Gomez-Rodriguez:
Learning to Switch Between Machines and Humans. CoRR abs/2002.04258 (2020) - [i42]Rati Devidze, Farnam Mansouri, Luis Haug, Yuxin Chen, Adish Singla:
Understanding the Power and Limitations of Teaching with Imperfect Knowledge. CoRR abs/2003.09712 (2020) - [i41]Xuezhou Zhang, Yuzhe Ma, Adish Singla, Xiaojin Zhu:
Adaptive Reward-Poisoning Attacks against Reinforcement Learning. CoRR abs/2003.12613 (2020) - [i40]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) - [i39]Xuezhou Zhang, Shubham Kumar Bharti, Yuzhe Ma, Adish Singla, Xiaojin Zhu:
The Teaching Dimension of Q-learning. CoRR abs/2006.09324 (2020) - [i38]Xuezhou Zhang, Yuzhe Ma, Adish Singla:
Task-agnostic Exploration in Reinforcement Learning. CoRR abs/2006.09497 (2020) - [i37]Parameswaran Kamalaruban, Rati Devidze, Volkan Cevher, Adish Singla:
Environment Shaping in Reinforcement Learning using State Abstraction. CoRR abs/2006.13160 (2020) - [i36]Akash Kumar, Adish Singla, Yisong Yue, Yuxin Chen:
Average-case Complexity of Teaching Convex Polytopes via Halfspace Queries. CoRR abs/2006.14677 (2020) - [i35]Umair Z. Ahmed, Maria Christakis, Aleksandr Efremov, Nigel Fernandez, Ahana Ghosh, Abhik Roychoudhury, Adish Singla:
Synthesizing Tasks for Block-based Programming. CoRR abs/2006.16913 (2020) - [i34]Farnam Mansouri, Yuxin Chen, Ara Vartanian, Xiaojin Zhu, Adish Singla:
Preference-Based Batch and Sequential Teaching. CoRR abs/2010.10012 (2020) - [i33]Akash Kumar, Hanqi Zhang, Adish Singla, Yuxin Chen:
The Teaching Dimension of Kernel Perceptron. CoRR abs/2010.14043 (2020) - [i32]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
- [c43]Teresa Yeo, Parameswaran Kamalaruban, Adish Singla, Arpit Merchant, Thibault Asselborn, Louis Faucon, Pierre Dillenbourg, Volkan Cevher:
Iterative Classroom Teaching. AAAI 2019: 5684-5692 - [c42]Junaid Ali, Muhammad Bilal Zafar, Adish Singla, Krishna P. Gummadi:
Loss-Aversively Fair Classification. AIES 2019: 211-218 - [c41]Goran Radanovic, Rati Devidze, David C. Parkes, Adish Singla:
Learning to Collaborate in Markov Decision Processes. ICML 2019: 5261-5270 - [c40]Paul Rolland, Ali Kavis, Alexander Immer, Adish Singla, Volkan Cevher:
Efficient learning of smooth probability functions from Bernoulli tests with guarantees. ICML 2019: 5459-5467 - [c39]Parameswaran Kamalaruban, Rati Devidze, Volkan Cevher, Adish Singla:
Interactive Teaching Algorithms for Inverse Reinforcement Learning. IJCAI 2019: 2692-2700 - [c38]Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla:
Teaching Multiple Concepts to a Forgetful Learner. NeurIPS 2019: 4050-4060 - [c37]Sebastian Tschiatschek, Ahana Ghosh, Luis Haug, Rati Devidze, Adish Singla:
Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints. NeurIPS 2019: 4147-4157 - [c36]Farnam Mansouri, Yuxin Chen, Ara Vartanian, Xiaojin (Jerry) Zhu, Adish Singla:
Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models. NeurIPS 2019: 9195-9205 - [i31]Goran Radanovic, Rati Devidze, David C. Parkes, Adish Singla:
Learning to Collaborate in Markov Decision Processes. CoRR abs/1901.08029 (2019) - [i30]Rishav Chourasia, Adish Singla:
Unifying Ensemble Methods for Q-learning via Social Choice Theory. CoRR abs/1902.10646 (2019) - [i29]Junaid Ali, Mahmoudreza Babaei, Abhijnan Chakraborty, Baharan Mirzasoleiman, Krishna P. Gummadi, Adish Singla:
On the Fairness of Time-Critical Influence Maximization in Social Networks. CoRR abs/1905.06618 (2019) - [i28]Moein Khajehnejad, Behzad Tabibian, Bernhard Schölkopf, Adish Singla, Manuel Gomez-Rodriguez:
Optimal Decision Making Under Strategic Behavior. CoRR abs/1905.09239 (2019) - [i27]Parameswaran Kamalaruban, Rati Devidze, Volkan Cevher, Adish Singla:
Interactive Teaching Algorithms for Inverse Reinforcement Learning. CoRR abs/1905.11867 (2019) - [i26]Sebastian Tschiatschek, Ahana Ghosh, Luis Haug, Rati Devidze, Adish Singla:
Learner-aware Teaching: Inverse Reinforcement Learning with Preferences and Constraints. CoRR abs/1906.00429 (2019) - [i25]Abir De, Adish Singla, Utkarsh Upadhyay, Manuel Gomez-Rodriguez:
Can A User Anticipate What Her Followers Want? CoRR abs/1909.00440 (2019) - [i24]Ahana Ghosh, Sebastian Tschiatschek, Hamed Mahdavi, Adish Singla:
Towards Deployment of Robust AI Agents for Human-Machine Partnerships. CoRR abs/1910.02330 (2019) - [i23]Farnam Mansouri, Yuxin Chen, Ara Vartanian, Xiaojin Zhu, Adish Singla:
Preference-Based Batch and Sequential Teaching: Towards a Unified View of Models. CoRR abs/1910.10944 (2019) - 2018
- [c35]Goran Radanovic, Adish Singla, Andreas Krause, Boi Faltings:
Information Gathering With Peers: Submodular Optimization With Peer-Prediction Constraints. AAAI 2018: 1603-1610 - [c34]Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek, Andreas Krause:
Learning User Preferences to Incentivize Exploration in the Sharing Economy. AAAI 2018: 2248-2256 - [c33]Adish Singla, Seyed Hamed Hassani, Andreas Krause:
Learning to Interact With Learning Agents. AAAI 2018: 4083-4090 - [c32]Michael Backenköhler, Felix Scherzinger, Adish Singla, Verena Wolf:
Data-Driven Approach Towards a Personalized Curriculum. EDM 2018 - [c31]Till Speicher, Hoda Heidari, Nina Grgic-Hlaca, Krishna P. Gummadi, Adish Singla, Adrian Weller, Muhammad Bilal Zafar:
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual &Group Unfairness via Inequality Indices. KDD 2018: 2239-2248 - [c30]Yuxin Chen, Adish Singla, Oisin Mac Aodha, Pietro Perona, Yisong Yue:
Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners. NeurIPS 2018: 1483-1493 - [c29]Isabel Valera, Adish Singla, Manuel Gomez Rodriguez:
Enhancing the Accuracy and Fairness of Human Decision Making. NeurIPS 2018: 1774-1783 - [c28]Luis Haug, Sebastian Tschiatschek, Adish Singla:
Teaching Inverse Reinforcement Learners via Features and Demonstrations. NeurIPS 2018: 8473-8482 - [c27]Sebastian Tschiatschek, Adish Singla, Manuel Gomez-Rodriguez, Arpit Merchant, Andreas Krause:
Fake News Detection in Social Networks via Crowd Signals. WWW (Companion Volume) 2018: 517-524 - [i22]Xiaojin Zhu, Adish Singla, Sandra Zilles, Anna N. Rafferty:
An Overview of Machine Teaching. CoRR abs/1801.05927 (2018) - [i21]Yuxin Chen, Adish Singla, Oisin Mac Aodha, Pietro Perona, Yisong Yue:
Understanding the Role of Adaptivity in Machine Teaching: The Case of Version Space Learners. CoRR abs/1802.05190 (2018) - [i20]Anette Hunziker, Yuxin Chen, Oisin Mac Aodha, Manuel Gomez-Rodriguez, Andreas Krause, Pietro Perona, Yisong Yue, Adish Singla:
Teaching Multiple Concepts to Forgetful Learners. CoRR abs/1805.08322 (2018) - [i19]Isabel Valera, Adish Singla, Manuel Gomez Rodriguez:
Enhancing the Accuracy and Fairness of Human Decision Making. CoRR abs/1805.10318 (2018) - [i18]Till Speicher, Hoda Heidari, Nina Grgic-Hlaca, Krishna P. Gummadi, Adish Singla, Adrian Weller, Muhammad Bilal Zafar:
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices. CoRR abs/1807.00787 (2018) - [i17]Luis Haug, Sebastian Tschiatschek, Adish Singla:
Teaching Inverse Reinforcement Learners via Features and Demonstrations. CoRR abs/1810.08926 (2018) - [i16]Teresa Yeo, Parameswaran Kamalaruban, Adish Singla, Arpit Merchant, Thibault Asselborn, Louis Faucon, Pierre Dillenbourg, Volkan Cevher:
Iterative Classroom Teaching. CoRR abs/1811.03537 (2018) - [i15]Paul Rolland, Ali Kavis, Adish Singla, Volkan Cevher:
Efficient learning of smooth probability functions from Bernoulli tests with guarantees. CoRR abs/1812.04428 (2018) - 2017
- [c26]Sebastian Tschiatschek, Adish Singla, Andreas Krause:
Selecting Sequences of Items via Submodular Maximization. AAAI 2017: 2667-2673 - [i14]Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek, Andreas Krause:
Coordinated Online Learning With Applications to Learning User Preferences. CoRR abs/1702.02849 (2017) - [i13]Adish Singla, Seyed Hamed Hassani, Andreas Krause:
Learning to Use Learners' Advice. CoRR abs/1702.04825 (2017) - [i12]Goran Radanovic, Adish Singla, Andreas Krause, Boi Faltings:
Information Gathering with Peers: Submodular Optimization with Peer-Prediction Constraints. CoRR abs/1711.06740 (2017) - [i11]Christoph Hirnschall, Adish Singla, Sebastian Tschiatschek, Andreas Krause:
Learning User Preferences to Incentivize Exploration in the Sharing Economy. CoRR abs/1711.08331 (2017) - [i10]Sebastian Tschiatschek, Adish Singla, Manuel Gomez-Rodriguez, Arpit Merchant, Andreas Krause:
Detecting Fake News in Social Networks via Crowdsourcing. CoRR abs/1711.09025 (2017) - 2016
- [b1]Adish Singla:
Learning and Incentives in Crowd-Powered Systems. ETH Zurich, Zürich, Switzerland, 2016 - [c25]Adish Singla, Sebastian Tschiatschek, Andreas Krause:
Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization. AAAI 2016: 2037-2043 - [c24]Besmira Nushi, Adish Singla, Andreas Krause, Donald Kossmann:
Learning and Feature Selection under Budget Constraints in Crowdsourcing. HCOMP 2016: 159-168 - [c23]Yuyin Sun, Adish Singla, Tori Qiao Yan, Andreas Krause, Dieter Fox:
Evaluating Task-Dependent Taxonomies for Navigation. HCOMP 2016: 229-238 - [c22]Adish Singla, Sebastian Tschiatschek, Andreas Krause:
Actively Learning Hemimetrics with Applications to Eliciting User Preferences. ICML 2016: 412-420 - [i9]Adish Singla, Sebastian Tschiatschek, Andreas Krause:
Actively Learning Hemimetrics with Applications to Eliciting User Preferences. CoRR abs/1605.07144 (2016) - 2015
- [c21]Adish Singla, Marco Santoni, Gábor Bartók, Pratik Mukerji, Moritz Meenen, Andreas Krause:
Incentivizing Users for Balancing Bike Sharing Systems. AAAI 2015: 723-729 - [c20]Adish Singla, Eric Horvitz, Pushmeet Kohli, Andreas Krause:
Learning to Hire Teams. HCOMP 2015: 34-35 - [c19]Besmira Nushi, Adish Singla, Anja Gruenheid, Erfan Zamanian, Andreas Krause, Donald Kossmann:
Crowd Access Path Optimization: Diversity Matters. HCOMP 2015: 130-139 - [c18]Yuyin Sun, Adish Singla, Dieter Fox, Andreas Krause:
Building Hierarchies of Concepts via Crowdsourcing. IJCAI 2015: 844-853 - [c17]Adish Singla, Eric Horvitz, Pushmeet Kohli, Ryen White, Andreas Krause:
Information Gathering in Networks via Active Exploration. IJCAI 2015: 891-988 - [i8]Adish Singla, Eric Horvitz, Pushmeet Kohli, Ryen W. White, Andreas Krause:
Information Gathering in Networks via Active Exploration. CoRR abs/1504.06423 (2015) - [i7]Yuyin Sun, Adish Singla, Dieter Fox, Andreas Krause:
Building Hierarchies of Concepts via Crowdsourcing. CoRR abs/1504.07302 (2015) - [i6]Besmira Nushi, Adish Singla, Anja Gruenheid, Erfan Zamanian, Andreas Krause, Donald Kossmann:
Crowd Access Path Optimization: Diversity Matters. CoRR abs/1508.01951 (2015) - [i5]Adish Singla, Eric Horvitz, Pushmeet Kohli, Andreas Krause:
Learning to Hire Teams. CoRR abs/1508.02823 (2015) - [i4]Adish Singla, Sebastian Tschiatschek, Andreas Krause:
Noisy Submodular Maximization via Adaptive Sampling with Applications to Crowdsourced Image Collection Summarization. CoRR abs/1511.07211 (2015) - 2014
- [c16]Adish Singla, Eric Horvitz, Ece Kamar, Ryen White:
Stochastic Privacy. AAAI 2014: 152-158 - [c15]Arthur Gervais, Reza Shokri, Adish Singla, Srdjan Capkun, Vincent Lenders:
Quantifying Web-Search Privacy. CCS 2014: 966-977 - [c14]Adish Singla, Ian Lienert, Gábor Bartók, Andreas Krause:
Contextual Procurement in Online Crowdsourcing Markets. HCOMP 2014: 58-59 - [c13]Gagan Goel, Afshin Nikzad, Adish Singla:
Mechanism Design for Crowdsourcing Markets with Heterogeneous Tasks. HCOMP 2014: 77-86 - [c12]Adish Singla, Ilija Bogunovic, Gábor Bartók, Amin Karbasi, Andreas Krause:
Near-Optimally Teaching the Crowd to Classify. ICML 2014: 154-162 - [c11]Adish Singla, Ryen W. White, Ahmed Hassan Awadallah, Eric Horvitz:
Enhancing personalization via search activity attribution. SIGIR 2014: 1063-1066 - [c10]Gagan Goel, Afshin Nikzad, Adish Singla:
Allocating tasks to workers with matching constraints: truthful mechanisms for crowdsourcing markets. WWW (Companion Volume) 2014: 279-280 - [c9]Ryen W. White, Ahmed Hassan Awadallah, Adish Singla, Eric Horvitz:
From devices to people: attribution of search activity in multi-user settings. WWW 2014: 431-442 - [i3]Adish Singla, Ilija Bogunovic, Gábor Bartók, Amin Karbasi, Andreas Krause:
Near-Optimally Teaching the Crowd to Classify. CoRR abs/1402.2092 (2014) - [i2]Adish Singla, Eric Horvitz, Ece Kamar, Ryen White:
Stochastic Privacy. CoRR abs/1404.5454 (2014) - 2013
- [c8]Adish Singla, Andreas Krause:
Incentives for Privacy Tradeoff in Community Sensing. HCOMP 2013: 165-173 - [c7]Adish Singla, Andreas Krause:
Truthful incentives in crowdsourcing tasks using regret minimization mechanisms. WWW 2013: 1167-1178 - [i1]Adish Singla, Andreas Krause:
Incentives for Privacy Tradeoff in Community Sensing. CoRR abs/1308.4013 (2013) - 2012
- [c6]Weizhu Chen, Dong Wang, Yuchen Zhang, Zheng Chen, Adish Singla, Qiang Yang:
A noise-aware click model for web search. WSDM 2012: 313-322 - 2011
- [j1]Adish Singla, Ingmar Weber:
Camera Brand Congruence and Camera Model Propagation in the Flickr Social Graph. ACM Trans. Web 5(4): 20:1-20:25 (2011) - [c5]Ryen W. White, Adish Singla:
Finding our way on the web: exploring the role of waypoints in search interaction. WWW (Companion Volume) 2011: 147-148 - 2010
- [c4]Adish Singla, Ryen White, Jeff Huang:
Studying trailfinding algorithms for enhanced web search. SIGIR 2010: 443-450 - [c3]Adish Singla, Ingmar Weber:
Tagging and navigability. WWW 2010: 1185-1186 - [c2]Adish Singla, Ryen W. White:
Sampling high-quality clicks from noisy click data. WWW 2010: 1187-1188
2000 – 2009
- 2009
- [c1]Adish Singla, Ingmar Weber:
Camera brand congruence in the Flickr social graph. WSDM 2009: 252-261
Coauthor Index
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