51 citations · 155 across the 11 of their papers we have counts for
11 papers
TabDPT: Scaling Tabular Foundation Models on Real Data
Junwei Ma, Valentin Thomas, Rasa Hosseinzadeh +7
Tabular data is one of the most ubiquitous sources of information worldwide, spanning a wide variety of domains. This inherent heterogeneity has slowed the development of Tabular F…
Retrieval & Fine-Tuning for In-Context Tabular Models
Valentin Thomas, Junwei Ma, Rasa Hosseinzadeh +4
Tabular data is a pervasive modality spanning a wide range of domains, and the inherent diversity poses a considerable challenge for deep learning. Recent advancements using transf…
In-Context Data Distillation with TabPFN
Junwei Ma, Valentin Thomas, Guangwei Yu +1
Foundation models have revolutionized tasks in computer vision and natural language processing. However, in the realm of tabular data, tree-based models like XGBoost continue to do…
The Role of Baselines in Policy Gradient Optimization
Jincheng Mei, Wesley Chung, Valentin Thomas +3
We study the effect of baselines in on-policy stochastic policy gradient optimization, and close the gap between the theory and practice of policy optimization methods. Our first c…
Bridging the Gap Between Target Networks and Functional Regularization
Alexandre Piche, Valentin Thomas, Joseph Marino +4
Bootstrapping is behind much of the successes of Deep Reinforcement Learning. However, learning the value function via bootstrapping often leads to unstable training due to fast-ch…
Bridging the Gap Between Target Networks and Functional Regularization
Alexandre Piché, Valentin Thomas, Rafael Pardinas +4
Bootstrapping is behind much of the successes of deep Reinforcement Learning. However, learning the value function via bootstrapping often leads to unstable training due to fast-ch…