Erdem Biyik

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 68

Top Topics

Markov Decision Process

Reinforcement Learning

Preference Elicitation

Reward Function

Top Venues

Publications

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 (2024)
Evan Ellis, Gaurav R. Ghosal, Stuart J. Russell, Anca D. Dragan, Erdem Biyik
A Generalized Acquisition Function for Preference-based Reward Learning. CoRR (2024)
Erdem Biyik, Nima Anari, Dorsa Sadigh
Batch Active Learning of Reward Functions from Human Preferences. ACM Trans. Hum. Robot Interact. 13 (2) (2024)
Erdem Biyik, Nicolas Huynh, Mykel J. Kochenderfer, Dorsa Sadigh
Active preference-based Gaussian process regression for reward learning and optimization. Int. J. Robotics Res. 43 (5) (2024)
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 (2024)
Anthony Liang, Jesse Thomason, Erdem Biyik
ViSaRL: Visual Reinforcement Learning Guided by Human Saliency. CoRR (2024)
Evan Ellis, Gaurav R. Ghosal, Stuart J. Russell, Anca D. Dragan, Erdem Biyik
A Generalized Acquisition Function for Preference-based Reward Learning. ICRA (2024)
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 (2024)
Erdem Biyik, Nima Anari, Dorsa Sadigh
Batch Active Learning of Reward Functions from Human Preferences. CoRR (2024)
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 (2024)
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)
Stephen Casper, Xander Davies, Claudia Shi, Thomas Krendl Gilbert, Jérémy Scheurer, Javier Rando, Rachel Freedman, Tomasz Korbak, David Lindner, Pedro Freire, Tony 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 (2023)
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 (2023)
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)
Erdem Biyik, Fan Yao, Yinlam Chow, Alex Haig, Chih-Wei Hsu, Mohammad Ghavamzadeh, Craig Boutilier
Preference Elicitation with Soft Attributes in Interactive Recommendation. CoRR (2023)
Vivek Myers, Erdem Biyik, Dorsa Sadigh
Active Reward Learning from Online Preferences. ICRA (2023)
Vivek Myers, Erdem Biyik, Dorsa Sadigh
Active Reward Learning from Online Preferences. CoRR (2023)
Erdem Biyik, Anusha Lalitha, Rajarshi Saha, Andrea Goldsmith, Dorsa Sadigh
Partner-Aware Algorithms in Decentralized Cooperative Bandit Teams. AAAI (2022)
Megha Srivastava, Erdem Biyik, Suvir Mirchandani, Noah D. Goodman, Dorsa Sadigh
Assistive Teaching of Motor Control Tasks to Humans. NeurIPS (2022)
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. Int. J. Robotics Res. 41 (1) (2022)
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)
Erdem Biyik
Learning from Humans for Adaptive Interaction. HRI (2022)
Erdem Biyik, Aditi Talati, Dorsa Sadigh
APReL: A Library for Active Preference-based Reward Learning Algorithms. HRI (2022)
Zhangjie Cao, Erdem Biyik, Guy Rosman, Dorsa Sadigh
Leveraging Smooth Attention Prior for Multi-Agent Trajectory Prediction. CoRR (2022)
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 (2022)
Erdem Biyik
Learning Preferences for Interactive Autonomy. CoRR (2022)
Megha Srivastava, Erdem Biyik, Suvir Mirchandani, Noah D. Goodman, Dorsa Sadigh
Assistive Teaching of Motor Control Tasks to Humans. CoRR (2022)
Zhangjie Cao, Erdem Biyik, Guy Rosman, Dorsa Sadigh
Leveraging Smooth Attention Prior for Multi-Agent Trajectory Prediction. ICRA (2022)
Woodrow Z. Wang, Mark Beliaev, Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh
Emergent Prosociality in Multi-Agent Games Through Gifting. CoRR (2021)
Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh
Incentivizing Efficient Equilibria in Traffic Networks with Mixed Autonomy. CoRR (2021)
Erdem Biyik, Anusha Lalitha, Rajarshi Saha, Andrea Goldsmith, Dorsa Sadigh
Partner-Aware Algorithms in Decentralized Cooperative Bandit Teams. CoRR (2021)
Woodrow Z. Wang, Mark Beliaev, Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh
Emergent Prosociality in Multi-Agent Games Through Gifting. IJCAI (2021)
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. ICRA (2021)
Nils Wilde, Erdem Biyik, Dorsa Sadigh, Stephen L. Smith
Learning Reward Functions from Scale Feedback. CoRR (2021)
Erdem Biyik, Aditi Talati, Dorsa Sadigh
APReL: A Library for Active Preference-based Reward Learning Algorithms. CoRR (2021)
Vivek Myers, Erdem Biyik, Nima Anari, Dorsa Sadigh
Learning Multimodal Rewards from Rankings. CoRR (2021)
Sydney M. Katz, Amir Maleki, Erdem Biyik, Mykel J. Kochenderfer
Preference-based Learning of Reward Function Features. CoRR (2021)
Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh
Incentivizing Efficient Equilibria in Traffic Networks With Mixed Autonomy. IEEE Trans. Control. Netw. Syst. 8 (4) (2021)
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)
Nils Wilde, Erdem Biyik, Dorsa Sadigh, Stephen L. Smith
Learning Reward Functions from Scale Feedback. CoRL (2021)
Vivek Myers, Erdem Biyik, Nima Anari, Dorsa Sadigh
Learning Multimodal Rewards from Rankings. CoRL (2021)
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. HRI (2020)
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 (2020)
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 (2020)
Zheqing Zhu, Erdem Biyik, Dorsa Sadigh
Multi-Agent Safe Planning with Gaussian Processes. IROS (2020)
Erdem Biyik, Nicolas Huynh, Mykel J. Kochenderfer, Dorsa Sadigh
Active Preference-Based Gaussian Process Regression for Reward Learning. CoRR (2020)
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 (2020)
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 (2020)
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)
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 (2020)
Zheqing Zhu, Erdem Biyik, Dorsa Sadigh
Multi-Agent Safe Planning with Gaussian Processes. CoRR (2020)
Erdem Biyik, Nicolas Huynh, Mykel J. Kochenderfer, Dorsa Sadigh
Active Preference-Based Gaussian Process Regression for Reward Learning. Robotics: Science and Systems (2020)
Daniel A. Lazar, Erdem Biyik, Dorsa Sadigh, Ramtin Pedarsani
Learning How to Dynamically Route Autonomous Vehicles on Shared Roads. CoRR (2019)
Erdem Biyik, Jonathan Margoliash, Shahrouz Ryan Alimo, Dorsa Sadigh
Efficient and Safe Exploration in Deterministic Markov Decision Processes with Unknown Transition Models. ACC (2019)
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)
Erdem Biyik, Malayandi Palan, Nicholas C. Landolfi, Dylan P. Losey, Dorsa Sadigh
Asking Easy Questions: A User-Friendly Approach to Active Reward Learning. CoRR (2019)
Chandrayee Basu, Erdem Biyik, Zhixun He, Mukesh Singhal, Dorsa Sadigh
Active Learning of Reward Dynamics from Hierarchical Queries. IROS (2019)
Erdem Biyik, Kenneth Wang, Nima Anari, Dorsa Sadigh
Batch Active Learning Using Determinantal Point Processes. CoRR (2019)
Erdem Biyik, Daniel A. Lazar, Dorsa Sadigh, Ramtin Pedarsani
The Green Choice: Learning and Influencing Human Decisions on Shared Roads. CoRR (2019)
Erdem Biyik, Daniel A. Lazar, Dorsa Sadigh, Ramtin Pedarsani
The Green Choice: Learning and Influencing Human Decisions on Shared Roads. CDC (2019)
Erdem Biyik, Jonathan Margoliash, Shahrouz Ryan Alimo, Dorsa Sadigh
Efficient and Safe Exploration in Deterministic Markov Decision Processes with Unknown Transition Models. CoRR (2019)
Erdem Biyik, Dorsa Sadigh
Batch Active Preference-Based Learning of Reward Functions. CoRL (2018)
Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh
Altruistic Autonomy: Beating Congestion on Shared Roads. WAFR (2018)
Erdem Biyik, Dorsa Sadigh
Batch Active Preference-Based Learning of Reward Functions. CoRR (2018)
Erdem Biyik, Daniel A. Lazar, Ramtin Pedarsani, Dorsa Sadigh
Altruistic Autonomy: Beating Congestion on Shared Roads. CoRR (2018)
Erdem Biyik, Jean Barbier, Mohamad Dia
Generalized Approximate Message-Passing Decoder for Universal Sparse Superposition Codes. CoRR (2017)
Erdem Biyik, Jean Barbier, Mohamad Dia
Generalized approximate message-passing decoder for universal sparse superposition codes. ISIT (2017)
Huseyin Can Baykara, Erdem Biyik, Gamze Gul, Deniz Onural, Ahmet Safa Ozturk
Real-Time Detection, Tracking and Classification of Multiple Moving Objects in UAV Videos. ICTAI (2017)