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Erdem Biyik
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2020 – today
- 2024
- [j5]Erdem Biyik
, Nicolas Huynh, Mykel J. Kochenderfer
Active preference-based Gaussian process regression for reward learning and optimization. Int. J. Robotics Res. 43(5): 665-684 (2024) - [j4]Erdem Biyik
Batch Active Learning of Reward Functions from Human Preferences. ACM Trans. Hum. Robot Interact. 13(2): 24:1-24:27 (2024) - [c29]Harbani Jaggi, Kashyap Coimbatore Murali, Eve Fleisig, Erdem Biyik:
Accurate and Data-Efficient Toxicity Prediction when Annotators Disagree. EMNLP 2024: 21910-21917 - [c28]Michelle Pan, Mariah L. Schrum, Vivek Myers, Erdem Biyik, Anca D. Dragan:
Coprocessor Actor Critic: A Model-Based Reinforcement Learning Approach For Adaptive Brain Stimulation. ICML 2024 - [c27]Yufei Wang, Zhanyi Sun, Jesse Zhang, Zhou Xian, Erdem Biyik, David Held, Zackory Erickson:
RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback. ICML 2024 - [c26]Evan Ellis, Gaurav R. Ghosal, Stuart J. Russell, Anca D. Dragan, Erdem Biyik:
A Generalized Acquisition Function for Preference-based Reward Learning. ICRA 2024: 2814-2821 - [i38]Yufei Wang, Zhanyi Sun, Jesse Zhang, Zhou Xian, Erdem Biyik, David Held, Zackory Erickson:
RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback. CoRR abs/2402.03681 (2024) - [i37]Erdem Biyik, Nima Anari, Dorsa Sadigh:
Batch Active Learning of Reward Functions from Human Preferences. CoRR abs/2402.15757 (2024) - [i36]Anthony Liang, Guy Tennenholtz, Chih-Wei Hsu, Yinlam Chow, Erdem Biyik, Craig Boutilier:
DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning. CoRR abs/2402.15957 (2024) - [i35]Evan Ellis, Gaurav R. Ghosal, Stuart J. Russell, Anca D. Dragan, Erdem Biyik:
A Generalized Acquisition Function for Preference-based Reward Learning. CoRR abs/2403.06003 (2024) - [i34]Anthony Liang, Jesse Thomason, Erdem Biyik:
ViSaRL: Visual Reinforcement Learning Guided by Human Saliency. CoRR abs/2403.10940 (2024) - [i33]Michelle Pan, Mariah Schrum, Vivek Myers, Erdem Biyik, Anca D. Dragan:
Coprocessor Actor Critic: A Model-Based Reinforcement Learning Approach For Adaptive Brain Stimulation. CoRR abs/2406.06714 (2024) - [i32]Jesse Zhang, Minho Heo, Zuxin Liu, Erdem Biyik, Joseph J. Lim, Yao Liu, Rasool Fakoor:
EXTRACT: Efficient Policy Learning by Extracting Transferrable Robot Skills from Offline Data. CoRR abs/2406.17768 (2024) - [i31]Zhaojing Yang, Miru Jun, Jeremy Tien, Stuart J. Russell, Anca D. Dragan, Erdem Biyik:
Trajectory Improvement and Reward Learning from Comparative Language Feedback. CoRR abs/2410.06401 (2024) - 2023
- [j3]Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Tong Wang, Samuel Marks, Charbel-Raphaël Ségerie, Micah Carroll, Andi Peng, Phillip J. K. Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca D. Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell:
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. Trans. Mach. Learn. Res. 2023 (2023) - [c25]Vivek Myers, Erdem Biyik, Dorsa Sadigh:
Active Reward Learning from Online Preferences. ICRA 2023: 7511-7518 - [c24]Sumedh Sontakke, Jesse Zhang, Sébastien M. R. Arnold, Karl Pertsch, Erdem Biyik, Dorsa Sadigh, Chelsea Finn, Laurent Itti:
RoboCLIP: One Demonstration is Enough to Learn Robot Policies. NeurIPS 2023 - [i30]Vivek Myers, Erdem Biyik, Dorsa Sadigh:
Active Reward Learning from Online Preferences. CoRR abs/2302.13507 (2023) - [i29]Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony Tong Wang, Samuel Marks, Charbel-Raphaël Ségerie, Micah Carroll, Andi Peng, Phillip J. K. Christoffersen, Mehul Damani, Stewart Slocum, Usman Anwar, Anand Siththaranjan, Max Nadeau, Eric J. Michaud, Jacob Pfau, Dmitrii Krasheninnikov, Xin Chen, Lauro Langosco, Peter Hase, Erdem Biyik, Anca D. Dragan, David Krueger, Dorsa Sadigh, Dylan Hadfield-Menell:
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback. CoRR abs/2307.15217 (2023) - [i28]Sumedh A. Sontakke, Jesse Zhang, Sébastien M. R. Arnold, Karl Pertsch, Erdem Biyik, Dorsa Sadigh, Chelsea Finn, Laurent Itti:
RoboCLIP: One Demonstration is Enough to Learn Robot Policies. CoRR abs/2310.07899 (2023) - [i27]Erdem Biyik, Fan Yao, Yinlam Chow, Alex Haig, Chih-Wei Hsu, Mohammad Ghavamzadeh, Craig Boutilier:
Preference Elicitation with Soft Attributes in Interactive Recommendation. CoRR abs/2311.02085 (2023) - 2022
- [j2]Erdem Biyik
Learning reward functions from diverse sources of human feedback: Optimally integrating demonstrations and preferences. Int. J. Robotics Res. 41(1): 45-67 (2022) - [c23]Erdem Biyik, Anusha Lalitha, Rajarshi Saha, Andrea Goldsmith, Dorsa Sadigh:
Partner-Aware Algorithms in Decentralized Cooperative Bandit Teams. AAAI 2022: 9296-9303 - [c22]Erik Brockbank, Haoliang Wang, Justin Yang, Suvir Mirchandani, Erdem Biyik, Dorsa Sadigh, Judith E. Fan:
How do people incorporate advice from artificial agents when making physical judgments? CogSci 2022 - [c21]Erdem Biyik, Aditi Talati, Dorsa Sadigh:
APReL: A Library for Active Preference-based Reward Learning Algorithms. HRI 2022: 613-617 - [c20]Erdem Biyik:
Learning from Humans for Adaptive Interaction. HRI 2022: 1152-1154 - [c19]Zhangjie Cao, Erdem Biyik, Guy Rosman, Dorsa Sadigh:
Leveraging Smooth Attention Prior for Multi-Agent Trajectory Prediction. ICRA 2022: 10723-10730 - [c18]Megha Srivastava, Erdem Biyik, Suvir Mirchandani, Noah D. Goodman, Dorsa Sadigh:
Assistive Teaching of Motor Control Tasks to Humans. NeurIPS 2022 - [i26]Zhangjie Cao, Erdem Biyik, Guy Rosman, Dorsa Sadigh:
Leveraging Smooth Attention Prior for Multi-Agent Trajectory Prediction. CoRR abs/2203.04421 (2022) - [i25]Erik Brockbank, Haoliang Wang, Justin Yang, Suvir Mirchandani, Erdem Biyik, Dorsa Sadigh, Judith E. Fan:
How do people incorporate advice from artificial agents when making physical judgments? CoRR abs/2205.11613 (2022) - [i24]Erdem Biyik:
Learning Preferences for Interactive Autonomy. CoRR abs/2210.10899 (2022) - [i23]Megha Srivastava, Erdem Biyik, Suvir Mirchandani, Noah D. Goodman, Dorsa Sadigh:
Assistive Teaching of Motor Control Tasks to Humans. CoRR abs/2211.14003 (2022) - 2021
- [j1]Erdem Biyik
Incentivizing Efficient Equilibria in Traffic Networks With Mixed Autonomy. IEEE Trans. Control. Netw. Syst. 8(4): 1717-1729 (2021) - [c17]Vivek Myers, Erdem Biyik, Nima Anari, Dorsa Sadigh:
Learning Multimodal Rewards from Rankings. CoRL 2021: 342-352 - [c16]Nils Wilde, Erdem Biyik, Dorsa Sadigh, Stephen L. Smith:
Learning Reward Functions from Scale Feedback. CoRL 2021: 353-362 - [c15]Mark Beliaev, Erdem Biyik, Daniel A. Lazar, Woodrow Z. Wang, Dorsa Sadigh, Ramtin Pedarsani:
Incentivizing routing choices for safe and efficient transportation in the face of the COVID-19 pandemic. ICCPS 2021: 187-197 - [c14]Kejun Li, Maegan Tucker
ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes. ICRA 2021: 3212-3218 - [c13]Woodrow Z. Wang, Mark Beliaev, Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh:
Emergent Prosociality in Multi-Agent Games Through Gifting. IJCAI 2021: 434-442 - [i22]Sydney M. Katz, Amir Maleki, Erdem Biyik, Mykel J. Kochenderfer:
Preference-based Learning of Reward Function Features. CoRR abs/2103.02727 (2021) - [i21]Woodrow Z. Wang, Mark Beliaev, Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh:
Emergent Prosociality in Multi-Agent Games Through Gifting. CoRR abs/2105.06593 (2021) - [i20]Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh:
Incentivizing Efficient Equilibria in Traffic Networks with Mixed Autonomy. CoRR abs/2106.04678 (2021) - [i19]Erdem Biyik, Aditi Talati, Dorsa Sadigh:
APReL: A Library for Active Preference-based Reward Learning Algorithms. CoRR abs/2108.07259 (2021) - [i18]Vivek Myers, Erdem Biyik, Nima Anari, Dorsa Sadigh:
Learning Multimodal Rewards from Rankings. CoRR abs/2109.12750 (2021) - [i17]Nils Wilde, Erdem Biyik, Dorsa Sadigh, Stephen L. Smith:
Learning Reward Functions from Scale Feedback. CoRR abs/2110.00284 (2021) - [i16]Erdem Biyik, Anusha Lalitha, Rajarshi Saha, Andrea Goldsmith, Dorsa Sadigh:
Partner-Aware Algorithms in Decentralized Cooperative Bandit Teams. CoRR abs/2110.00751 (2021) - 2020
- [c12]Minae Kwon, Erdem Biyik
When Humans Aren't Optimal: Robots that Collaborate with Risk-Aware Humans. HRI 2020: 43-52 - [c11]Zheqing Zhu, Erdem Biyik, Dorsa Sadigh:
Multi-Agent Safe Planning with Gaussian Processes. IROS 2020: 6260-6267 - [c10]Erdem Biyik, Nicolas Huynh, Mykel J. Kochenderfer, Dorsa Sadigh:
Active Preference-Based Gaussian Process Regression for Reward Learning. Robotics: Science and Systems 2020 - [c9]Zhangjie Cao, Erdem Biyik, Woodrow Z. Wang, Allan Raventos, Adrien Gaidon, Guy Rosman, Dorsa Sadigh:
Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving. Robotics: Science and Systems 2020 - [i15]Minae Kwon, Erdem Biyik, Aditi Talati, Karan Bhasin, Dylan P. Losey, Dorsa Sadigh:
When Humans Aren't Optimal: Robots that Collaborate with Risk-Aware Humans. CoRR abs/2001.04377 (2020) - [i14]Erdem Biyik, Nicolas Huynh, Mykel J. Kochenderfer, Dorsa Sadigh:
Active Preference-Based Gaussian Process Regression for Reward Learning. CoRR abs/2005.02575 (2020) - [i13]Erdem Biyik, Dylan P. Losey, Malayandi Palan, Nicholas C. Landolfi, Gleb Shevchuk, Dorsa Sadigh:
Learning Reward Functions from Diverse Sources of Human Feedback: Optimally Integrating Demonstrations and Preferences. CoRR abs/2006.14091 (2020) - [i12]Zhangjie Cao, Erdem Biyik, Woodrow Z. Wang, Allan Raventos, Adrien Gaidon, Guy Rosman, Dorsa Sadigh:
Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving. CoRR abs/2007.00178 (2020) - [i11]Zheqing Zhu, Erdem Biyik, Dorsa Sadigh:
Multi-Agent Safe Planning with Gaussian Processes. CoRR abs/2008.04452 (2020) - [i10]Kejun Li, Maegan Tucker, Erdem Biyik, Ellen R. Novoseller, Joel W. Burdick, Yanan Sui, Dorsa Sadigh, Yisong Yue, Aaron D. Ames:
ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes. CoRR abs/2011.04812 (2020) - [i9]Mark Beliaev, Erdem Biyik, Daniel A. Lazar, Woodrow Z. Wang, Dorsa Sadigh, Ramtin Pedarsani:
Incentivizing Routing Choices for Safe and Efficient Transportation in the Face of the COVID-19 Pandemic. CoRR abs/2012.15749 (2020)
2010 – 2019
- 2019
- [c8]Erdem Biyik
Efficient and Safe Exploration in Deterministic Markov Decision Processes with Unknown Transition Models. ACC 2019: 1792-1799 - [c7]Erdem Biyik
The Green Choice: Learning and Influencing Human Decisions on Shared Roads. CDC 2019: 347-354 - [c6]Erdem Biyik, Malayandi Palan, Nicholas C. Landolfi, Dylan P. Losey, Dorsa Sadigh:
Asking Easy Questions: A User-Friendly Approach to Active Reward Learning. CoRL 2019: 1177-1190 - [c5]Chandrayee Basu, Erdem Biyik
Active Learning of Reward Dynamics from Hierarchical Queries. IROS 2019: 120-127 - [i8]Erdem Biyik, Jonathan Margoliash, Shahrouz Ryan Alimo, Dorsa Sadigh:
Efficient and Safe Exploration in Deterministic Markov Decision Processes with Unknown Transition Models. CoRR abs/1904.01068 (2019) - [i7]Erdem Biyik, Daniel A. Lazar, Dorsa Sadigh, Ramtin Pedarsani:
The Green Choice: Learning and Influencing Human Decisions on Shared Roads. CoRR abs/1904.02209 (2019) - [i6]Erdem Biyik, Kenneth Wang, Nima Anari, Dorsa Sadigh:
Batch Active Learning Using Determinantal Point Processes. CoRR abs/1906.07975 (2019) - [i5]Daniel A. Lazar, Erdem Biyik, Dorsa Sadigh, Ramtin Pedarsani:
Learning How to Dynamically Route Autonomous Vehicles on Shared Roads. CoRR abs/1909.03664 (2019) - [i4]Erdem Biyik, Malayandi Palan, Nicholas C. Landolfi, Dylan P. Losey, Dorsa Sadigh:
Asking Easy Questions: A User-Friendly Approach to Active Reward Learning. CoRR abs/1910.04365 (2019) - 2018
- [c4]Erdem Biyik, Dorsa Sadigh:
Batch Active Preference-Based Learning of Reward Functions. CoRL 2018: 519-528 - [c3]Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh:
Altruistic Autonomy: Beating Congestion on Shared Roads. WAFR 2018: 887-904 - [i3]Erdem Biyik, Dorsa Sadigh:
Batch Active Preference-Based Learning of Reward Functions. CoRR abs/1810.04303 (2018) - [i2]Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh:
Altruistic Autonomy: Beating Congestion on Shared Roads. CoRR abs/1810.11978 (2018) - 2017
- [c2]Huseyin Can Baykara, Erdem Biyik
Real-Time Detection, Tracking and Classification of Multiple Moving Objects in UAV Videos. ICTAI 2017: 945-950 - [c1]Erdem Biyik
Generalized approximate message-passing decoder for universal sparse superposition codes. ISIT 2017: 1593-1597 - [i1]Erdem Biyik, Jean Barbier, Mohamad Dia:
Generalized Approximate Message-Passing Decoder for Universal Sparse Superposition Codes. CoRR abs/1701.03590 (2017)
Coauthor Index
[j5] [j4] [i37] [j3] [c25] [c24] [i30] [i29] [i28] [j2] [c23] [c22] [c21] [c19] [c18] [i26] [i25] [i23] [j1] [c17] [c16] [c15] [c14] [c13] [i21] [i20] [i19] [i18] [i17] [i16] [c12] [c11] [c10] [c9] [i15] [i14] [i13] [i12] [i11] [i10] [i9] [c8] [c7] [c6] [c5] [i8] [i7] [i6] [i5] [i4] [c4] [c3] [i3] [i2]
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last updated on 2024-11-19 20:48 CET by the dblp team
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