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Adish Singla
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2020 – today
- 2024
- [j7]Victor-Alexandru Padurean, Georgios Tzannetos, Adish Singla:
Neural Task Synthesis for Visual Programming. Trans. Mach. Learn. Res. 2024 (2024) - [c84]Chao Wen, Ahana Ghosh, Jacqueline Staub, Adish Singla:
Task Synthesis for Elementary Visual Programming in XLogoOnline Environment. AIED Companion (2) 2024: 308-316 - [c83]Andi Nika, Debmalya Mandal, Adish Singla, Goran Radanovic:
Corruption-Robust Offline Two-Player Zero-Sum Markov Games. AISTATS 2024: 1243-1251 - [c82]Rati Devidze, Parameswaran Kamalaruban, Adish Singla:
Informativeness of Reward Functions in Reinforcement Learning. AAMAS 2024: 444-452 - [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 - [i86]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) - [i85]Debmalya Mandal, Andi Nika, Parameswaran Kamalaruban, Adish Singla, Goran Radanovic:
Corruption Robust Offline Reinforcement Learning with Human Feedback. CoRR abs/2402.06734 (2024) - [i84]Rati Devidze, Parameswaran Kamalaruban, Adish Singla:
Informativeness of Reward Functions in Reinforcement Learning. CoRR abs/2402.07019 (2024) - [i83]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) - [i82]Andi Nika, Debmalya Mandal, Adish Singla, Goran Radanovic:
Corruption-Robust Offline Two-Player Zero-Sum Markov Games. CoRR abs/2403.07933 (2024) - [i81]Ahana Ghosh, Liina Malva, Adish Singla:
Analyzing-Evaluating-Creating: Assessing Computational Thinking and Problem Solving in Visual Programming Domains. CoRR abs/2403.12227 (2024) - [i80]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) - [i79]Chao Wen, Ahana Ghosh, Jacqueline Staub, Adish Singla:
Task Synthesis for Elementary Visual Programming in XLogoOnline Environment. CoRR abs/2405.02173 (2024) - [i78]Georgios Tzannetos, Parameswaran Kamalaruban, Adish Singla:
Proximal Curriculum with Task Correlations for Deep Reinforcement Learning. CoRR abs/2405.02481 (2024) - [i77]Nachiket Kotalwar, Alkis Gotovos, Adish Singla:
Hints-In-Browser: Benchmarking Language Models for Programming Feedback Generation. CoRR abs/2406.05053 (2024) - [i76]Victor-Alexandru Padurean, Adish Singla:
Benchmarking Generative Models on Computational Thinking Tests in Elementary Visual Programming. CoRR abs/2406.09891 (2024) - [i75]Chao Wen, Jacqueline Staub, Adish Singla:
Program Synthesis Benchmark for Visual Programming in XLogoOnline Environment. CoRR abs/2406.11334 (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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