5 papers
MatrixFormer: A Foundation Model for Matrix Completion
Dwaipayan Saha, Jacob Feitelberg, Kyuseong Choi +2
Matrix completion underlies problems from tabular imputation to causal inference, yet existing tabular foundation models treat it as entry-by-entry prediction, repeating context fo…
GOPO: Policy Optimization using Ranked Rewards
Kyuseong Choi, Dwaipayan Saha, Woojeong Kim +2
Standard reinforcement learning from human feedback (RLHF) trains a reward model on pairwise preference data and then uses it for policy optimization. However, while reward models…
Manifold Random Features
Ananya Parashar, Derek Long, Dwaipayan Saha +1
We present a new paradigm for creating random features to approximate bi-variate functions (in particular, kernels) defined on general manifolds. This new mechanism of Manifold Ran…
One Pipeline, Many Transformers: Pattern-Specific Imputation Specialists for Tabular Missing Data
Jacob Feitelberg, Dwaipayan Saha, Kyuseong Choi +3
Missing data in tabular datasets forces practitioners into a hard choice: deploy a general-purpose imputer that may perform poorly for the problem at hand, or wait for someone to d…
Synthetic Blips: Generalizing Synthetic Controls for Dynamic Treatment Effects
Anish Agarwal, Sukjin Han, Dwaipayan Saha +2
We propose a generalization of the synthetic control methods to the setting with dynamic treatment effects, in which each unit receives multiple treatments sequentially, according…