arxivAug 3bullish

Application of machine learning to monster level prediction in tabletop RPG game design

arXiv:2607.09196v2 Announce Type: replace Abstract: Designing balanced adversaries is a central but labor-intensive task in tabletop role-playing game (TTRPG) development. In systems such as Pathfinder, each monster is described by many numerical attributes that jointly determine its power, summariz

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arxivJul 10

Distributed Sketching on Data Partitions for OLS Regression

arXiv:2607.07888v1 Announce Type: new Abstract: This paper studies distributed sketching for ordinary least squares (OLS) regression, an approach that distributes small sketches of a large data set over multiple machines to separately construct OLS estimators and average them. Unlike prior studies t

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arxivJul 1

Conformalized Regression for Continuous Bounded Outcomes

arXiv:2507.14023v2 Announce Type: replace-cross Abstract: Regression problems with bounded continuous outcomes frequently arise in statistical and machine learning applications, such as the analysis of rates and proportions. A central challenge in this setting is predicting the response at a new cov

BELO2 models #regression #conformal-prediction #machine-learning Read on arxiv →

arxivJun 25

Alternate loss functions and regression models that achieve robustness to outliers by modulating the learning rate

arXiv:2606.22068v2 Announce Type: replace-cross Abstract: Most real-world datasets used for training supervised learning models are contaminated with noisy data and outliers leading to large prediction errors. This paper proposes a new approach for achieving robustness where the learning rate is mod

SQSM2 models #robustness #outliers #regression Read on arxiv →

arxivMay 22bullish

Distribution-Aware Reward: Reinforcement Learning over Predictive Distributions for LLM Regression

arXiv:2605.20740v1 Announce Type: cross Abstract: Large language models can predict real-valued quantities from heterogeneous inputs such as text, code, and molecular strings, but most training objectives score each decoded floating-point number independently, improving point estimates without ensur

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arxivMay 20bullish

Cubit: Token Mixer with Kernel Ridge Regression

arXiv:2605.06501v2 Announce Type: replace-cross Abstract: Since its introduction in 2017, the Transformer has become one of the most widely adopted architectures in modern deep learning. Despite extensive efforts to improve positional encoding, attention mechanisms, and feed-forward networks, the co

TRCU2 models #machine-learning #architecture #regression Read on arxiv →