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cs.LG2026
Foundation-Preserving Optimization in Generalized Eigenspace
Dongjun Kim, Adrian de Wynter, Huancheng Chen +2
While finetuning effectively adapts foundation models to specialized downstream tasks, it can degrade nontarget capabilities acquired during pretraining. Existing forgetting aware…
cs.LG2025
Efficient Weighted Sampling via Score-based Generative Models
Heasung Kim, Taekyun Lee, Hyeji Kim +1
Weighted sampling -- sampling from a probability density function (PDF) proportional to the product of a base PDF and a weight function -- is a fundamental technique with wide-rang…
cs.LG2023
Learning RL-Policies for Joint Beamforming Without Exploration: A Batch Constrained Off-Policy Approach
Heasung Kim, Sravan Kumar Ankireddy
In this work, we consider the problem of network parameter optimization for rate maximization. We frame this as a joint optimization problem of power control, beam forming, and int…