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Jason Pazis
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2020 – today
- 2020
- [j1]Dong-Ki Kim
, Shayegan Omidshafiei, Jason Pazis, Jonathan P. How:
Crossmodal attentive skill learner: learning in Atari and beyond with audio-video inputs. Auton. Agents Multi Agent Syst. 34(1): 16 (2020)
2010 – 2019
- 2018
- [c12]Shayegan Omidshafiei, Dong-Ki Kim, Jason Pazis, Jonathan P. How:
Crossmodal Attentive Skill Learner. AAMAS 2018: 139-146 - 2017
- [c11]Shayegan Omidshafiei, Jason Pazis, Christopher Amato, Jonathan P. How, John Vian:
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability. ICML 2017: 2681-2690 - [c10]Liam Paull, Jacopo Tani, Heejin Ahn
, Javier Alonso-Mora
, Luca Carlone, Michal Cáp, Yu Fan Chen, Changhyun Choi
, Jeff Dusek, Yajun Fang, Daniel Hoehener, Shih-Yuan Liu, Michael Novitzky, Igor Franzoni Okuyama, Jason Pazis, Guy Rosman, Valerio Varricchio, Hsueh-Cheng Wang, Dmitry S. Yershov, Hang Zhao, Michael Benjamin, Christopher Carr
, Maria T. Zuber, Sertac Karaman, Emilio Frazzoli, Domitilla Del Vecchio, Daniela Rus, Jonathan P. How, John J. Leonard, Andrea Censi:
Duckietown: An open, inexpensive and flexible platform for autonomy education and research. ICRA 2017: 1497-1504 - [i2]Shayegan Omidshafiei, Jason Pazis, Christopher Amato, Jonathan P. How, John Vian:
Deep Decentralized Multi-task Multi-Agent Reinforcement Learning under Partial Observability. CoRR abs/1703.06182 (2017) - [i1]Shayegan Omidshafiei, Dong-Ki Kim, Jason Pazis, Jonathan P. How:
Crossmodal Attentive Skill Learner. CoRR abs/1711.10314 (2017) - 2016
- [c9]Jason Pazis, Ronald Parr:
Efficient PAC-Optimal Exploration in Concurrent, Continuous State MDPs with Delayed Updates. AAAI 2016: 1977-1985 - [c8]Jason Pazis, Ronald Parr, Jonathan P. How:
Improving PAC Exploration Using the Median Of Means. NIPS 2016: 3891-3899 - 2015
- [b1]Jason Pazis:
PAC-optimal, Non-parametric Algorithms and Bounds for Exploration in Concurrent MDPs with Delayed Updates. Duke University, Durham, NC, USA, 2015 - 2013
- [c7]Jason Pazis, Ronald Parr:
PAC Optimal Exploration in Continuous Space Markov Decision Processes. AAAI 2013: 774-781 - [c6]Jason Pazis, Ronald Parr:
Sample Complexity and Performance Bounds for Non-Parametric Approximate Linear Programming. AAAI 2013: 782-788 - 2011
- [c5]Jason Pazis, Ronald Parr:
Non-Parametric Approximate Linear Programming for MDPs. AAAI 2011: 459-464 - [c4]Jason Pazis, Michail G. Lagoudakis:
Reinforcement learning in multidimensional continuous action spaces. ADPRL 2011: 97-104 - [c3]Jason Pazis, Ronald Parr:
Generalized Value Functions for Large Action Sets. ICML 2011: 1185-1192
2000 – 2009
- 2009
- [c2]Jason Pazis, Michail G. Lagoudakis:
Learning continuous-action control policies. ADPRL 2009: 169-176 - [c1]Jason Pazis, Michail G. Lagoudakis:
Binary action search for learning continuous-action control policies. ICML 2009: 793-800
Coauthor Index
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