5 papers
IPPRO: Importance-based Pruning with PRojective Offset for Magnitude-indifferent Structural Pruning
Jaeheun Jung, Jaehyuk Lee, Yeajin Lee +1
Importance-based structured pruning overwhelmingly relies on filter magnitude. This proxy is fundamentally flawed: due to scale invariance, functionally identical filters can recei…
One-Point Contraction: Erasing Representational Separability toward Irreversible Deep Forgetting
Jaeheun Jung, Bosung Jung, Suhyun Bae +1
Machine unlearning is usually evaluated by what the classifier outputs: forget-set accuracy, confidence, membership-inference scores. We show that this is not enough. Across 14 rep…
Data-Driven Dimensional Synthesis of Diverse Planar Four-bar Function Generation Mechanisms via Direct Parameterization
Woon Ryong Kim, Jaeheun Jung, Jeong Un Ha +2
Dimensional synthesis of planar four-bar mechanisms is a challenging inverse problem in kinematics, requiring the determination of mechanism dimensions from desired motion specific…
Catalyst: a Novel Regularizer for Structured Pruning with Auxiliary Extension of Parameter Space
Jaeheun Jung, Donghun Lee
Structured pruning aims to reduce the size and computational cost of deep neural networks by removing entire filters or channels. The traditional regularizers such as L1 or Group L…
Broadband Ground Motion Synthesis by Diffusion Model with Minimal Condition
Jaeheun Jung, Jaehyuk Lee, Changhae Jung +3
Shock waves caused by earthquakes can be devastating. Generating realistic earthquake-caused ground motion waveforms help reducing losses in lives and properties, yet generative mo…