A New Paradigm for Generative Adversarial Networks based on Randomized Decision Rules

1 code implementation • 23 Jun 2023 • Sehwan Kim, Qifan Song, Faming Liang

In the new formulation, the discriminator converges to a fixed point while the generator converges to a distribution at the Nash equilibrium.

Clustering Generative Adversarial Network +2

Differentially Private Topological Data Analysis

1 code implementation • 5 May 2023 • Taegyu Kang, Sehwan Kim, Jinwon Sohn, Jordan Awan

We analyze the sensitivity of persistence diagrams in terms of the bottleneck distance, and we show that the commonly used \v{C}ech complex has sensitivity that does not decrease as the sample size $n$ increases.

Topological Data Analysis

Melon Playlist Dataset: a public dataset for audio-based playlist generation and music tagging

1 code implementation • 30 Jan 2021 • Andres Ferraro, Yuntae Kim, Soohyeon Lee, Biho Kim, Namjun Jo, Semi Lim, Suyon Lim, Jungtaek Jang, Sehwan Kim, Xavier Serra, Dmitry Bogdanov

We present Melon Playlist Dataset, a public dataset of mel-spectrograms for 649, 091tracks and 148, 826 associated playlists annotated by 30, 652 different tags.

Audio Signal Processing Collaborative Filtering +6

Stochastic Gradient Langevin Dynamics Algorithms with Adaptive Drifts

no code implementations • 20 Sep 2020 • Sehwan Kim, Qifan Song, Faming Liang

Bayesian deep learning offers a principled way to address many issues concerning safety of artificial intelligence (AI), such as model uncertainty, model interpretability, and prediction bias.