Maryam Hashemzadeh

Research: I'm passionate about leveraging learning-based systems to address complex challenges. Currently, my research focuses on Large Language Models (LLMs) and their application in interactive decision-making, akin to Reinforcement Learning (RL) agents, while emphasizing the prevention of hallucinations. Additionally, I'm exploring how LLMs can enhance generalization in Lifelong learning.

Bio: I'm a research associate at Mila supervised by Sarath Chandar with close collaboration with Marc-Alexandre Côté. I hold an MSc from the University of Alberta, where I conducted research with Martha White and Alona Fyshe, specializing in Offline Reinforcement Learning.

For any inquiries, feel free to reach out to me via mail!

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Publications

Offline-Online Reinforcement Learning: Extending Batch and Online RL
Maryam Hashemzadeh, Wesley Chung, Martha White
-, 2021
Paper /

@InProceedings{hashemzadeh2021offline, 
	author = {Maryam Hashemzadeh and Wesley Chung and Martha White}, 
	title = {Offline-Online Reinforcement Learning: Extending Batch and Online RL}, 
	booktitle = {-}, 
	year = {2021}, 
}

From Language to Language-ish: How Brain-Like is an LSTM's Representation of Nonsensical Language Stimuli?
Maryam Hashemzadeh, Greta Kaufeld, Martha White, Andrea Martin, Alona Fyshe
EMNLP, 2020
Paper /

@InProceedings{hashemzadeh2020language, 
	author = {Maryam Hashemzadeh and Greta Kaufeld and Martha White and Andrea Martin and Alona Fyshe}, 
	title = {From Language to Language-ish: How Brain-Like is an LSTM's Representation of Nonsensical Language Stimuli?}, 
	booktitle = {EMNLP}, 
	year = {2020}, 
}

Value signals guide abstraction during learning
Aurelio Cortese, Asuka Yamamoto, Maryam Hashemzadeh, Pradyumna Sepulveda, Mitsuo Kawato, Benedetto De Martino
Elife, 2021
Paper /

@InProceedings{cortese2021value, 
	author = {Aurelio Cortese and Asuka Yamamoto and Maryam Hashemzadeh and Pradyumna Sepulveda and Mitsuo Kawato and Benedetto De Martino}, 
	title = {Value signals guide abstraction during learning}, 
	booktitle = {Elife}, 
	year = {2021}, 
}

Clustering subspace generalization to obtain faster reinforcement learning
Maryam Hashemzadeh, Reshad Hosseini, Majid Ahmadabadi
Evolving Systems, Springer, 2020
Paper /

@InProceedings{hashemzadeh2020clustering, 
	author = {Maryam Hashemzadeh and Reshad Hosseini and Majid Ahmadabadi}, 
	title = {Clustering subspace generalization to obtain faster reinforcement learning}, 
	booktitle = {Evolving Systems, Springer}, 
	year = {2020}, 
}

Exploiting generalization in the subspaces for faster model-based reinforcement learning
Maryam Hashemzadeh, Reshad Hosseini, Majid Ahmadabadi
IEEE transactions on neural networks and learning systems, 2018
Paper /

@InProceedings{hashemzadeh2018exploiting, 
	author = {Maryam Hashemzadeh and Reshad Hosseini and Majid Ahmadabadi}, 
	title = {Exploiting generalization in the subspaces for faster model-based reinforcement learning}, 
	booktitle = {IEEE transactions on neural networks and learning systems}, 
	year = {2018}, 
}