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08/03/2022
Supervised and Reinforcement Learning from Observations in Reconnaissance Blind Chess
In this work, we adapt a training approach inspired by the original Alph...
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04/20/2022
Quantity vs Quality: Investigating the Trade-Off between Sample Size and Label Reliability
In this paper, we study learning in probabilistic domains where the lear...
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02/07/2022
Cedille: A large autoregressive French language model
Scaling up the size and training of autoregressive language models has e...
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09/21/2021
A Simple Unified Framework for Anomaly Detection in Deep Reinforcement Learning
Abnormal states in deep reinforcement learning (RL) are states that are ...
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07/29/2021
Addressing materials' microstructure diversity using transfer learning
Materials' microstructures are signatures of their alloying composition ...
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07/09/2021
A Comparison of Contextual and Non-Contextual Preference Ranking for Set Addition Problems
In this paper, we study the problem of evaluating the addition of elemen...
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05/25/2021
Predicting Human Card Selection in Magic: The Gathering with Contextual Preference Ranking
Drafting, i.e., the selection of a subset of items from a larger candida...
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05/10/2021
A Deep Dive into Conflict Generating Decisions
Boolean Satisfiability (SAT) is a well-known NP-complete problem. Despit...
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12/03/2020
Addressing machine learning concept drift reveals declining vaccine sentiment during the COVID-19 pandemic
Social media analysis has become a common approach to assess public opin...
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05/15/2020
COVID-Twitter-BERT: A Natural Language Processing Model to Analyse COVID-19 Content on Twitter
In this work, we release COVID-Twitter-BERT (CT-BERT), a transformer-bas...
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12/24/2019
Learning to Combat Compounding-Error in Model-Based Reinforcement Learning
Despite its potential to improve sample complexity versus model-free app...
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04/25/2019
Characterization of Glue Variables in CDCL SAT Solving
A state-of-the-art criterion to evaluate the importance of a given learn...
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06/16/2017
