5 papers · 1 filter
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…
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…
N: A Unified Python Package and Test Bench for Nearest Neighbor-Based Matrix Completion
Caleb Chin, Aashish Khubchandani, Harshvardhan Maskara +8
Nearest neighbor (NN) methods have re-emerged as competitive tools for matrix completion, offering strong empirical performance and recent theoretical guarantees, including entry-w…
Supervised Kernel Thinning
Albert Gong, Kyuseong Choi, Raaz Dwivedi
The kernel thinning algorithm of Dwivedi & Mackey (2024) provides a better-than-i.i.d. compression of a generic set of points. By generating high-fidelity coresets of size signific…