Kourosh Hakhamaneshi

According to our database, Kourosh Hakhamaneshi authored at least 13 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

LLMs Can Easily Learn to Reason from Demonstrations Structure, not content, is what matters!

Dacheng Li, Shiyi Cao, Tyler Griggs, Shu Liu, Xiangxi Mo, Eric Tang, Sumanth Hegde, Kourosh Hakhamaneshi, Shishir G. Patil, Matei Zaharia, Joseph E. Gonzalez, Ion Stoica

CoRR, February, 2025

Language Models Can Easily Learn to Reason from Demonstrations.

Dacheng Li, Shiyi Cao, Tyler Griggs, Shu Liu, Xiangxi Mo, Eric Tang, Sumanth Hegde, Kourosh Hakhamaneshi, Shishir G. Patil, Matei Zaharia, Joseph E. Gonzalez, Ion Stoica

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

2024

Semi-Supervised One Shot Imitation Learning.

Philipp Wu, Kourosh Hakhamaneshi, Yuqing Du, Igor Mordatch, Aravind Rajeswaran, Pieter Abbeel

RLJ, 2024

2023

Pretraining Graph Neural Networks for Few-Shot Analog Circuit Modeling and Design.

Kourosh Hakhamaneshi, Marcel Nassar, Mariano Phielipp, Pieter Abbeel, Vladimir Stojanovic

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., July, 2023

2022

Pre-training Agents for Design Optimization and Control

Kourosh Hakhamaneshi

PhD thesis, 2022

Hands-on Reinforcement Learning for Recommender Systems - From Bandits to SlateQ to Offline RL with Ray RLlib.

Christy D. Bergman, Kourosh Hakhamaneshi

Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

Hierarchical Few-Shot Imitation with Skill Transition Models.

Kourosh Hakhamaneshi, Ruihan Zhao, Albert Zhan, Pieter Abbeel, Michael Laskin

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

JUMBO: Scalable Multi-task Bayesian Optimization using Offline Data.

Kourosh Hakhamaneshi, Pieter Abbeel, Vladimir Stojanovic, Aditya Grover

CoRR, 2021

Skill Preferences: Learning to Extract and Execute Robotic Skills from Human Feedback.

Xiaofei Wang, Kimin Lee, Kourosh Hakhamaneshi, Pieter Abbeel, Michael Laskin

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

2020

GACEM: Generalized Autoregressive Cross Entropy Method for Multi-Modal Black Box Constraint Satisfaction.

Kourosh Hakhamaneshi, Keertana Settaluri, Pieter Abbeel, Vladimir Stojanovic

CoRR, 2020

AutoCkt: Deep Reinforcement Learning of Analog Circuit Designs.

Keertana Settaluri, Ameer Haj-Ali, Qijing Huang, Kourosh Hakhamaneshi, Borivoje Nikolic

Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020

2019

BagNet: Berkeley Analog Generator with Layout Optimizer Boosted with Deep Neural Networks.

Kourosh Hakhamaneshi, Nick Werblun, Pieter Abbeel, Vladimir Stojanovic

Proceedings of the International Conference on Computer-Aided Design, 2019

Analog Circuit Generator based on Deep Neural Network enhanced Combinatorial Optimization.

Kourosh Hakhamaneshi, Nick Werblun, Pieter Abbeel, Vladimir Stojanovic

Proceedings of the 56th Annual Design Automation Conference 2019, 2019