Session information

General Session

General Session » GS-2 Machine learning

[2B6-GS-2] Machine learning: Basics / Theory

Wed. May 29, 2024 5:30 PM - 7:10 PM Room B (Concert hall)

座長：中口悠輝（NEC）

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5:30 PM - 5:50 PM

[2B6-GS-2-01] Joint Estimation of Latent Event Types and Differential Equations from Temporal Point Processes

〇Shuichi Miyazawa^1,2, Daichi Mochihashi^1,3 (1. The Graduate University for Advanced Studies, 2. AGC Inc., 3. The Institue of Statistical Mathematics)

5:50 PM - 6:10 PM

[2B6-GS-2-02] Representation of Denoising Autoencoders by Tweedie's formula and its Analysis

〇Yuta Aishima¹, Kazushi Ikeda¹ (1. Nara Institute of Science and Technology)

6:10 PM - 6:30 PM

[2B6-GS-2-03] A Simple but Effective Closed-form Solution for Extreme Multi-label Learning

〇Kazuma Onishi¹, Katsuhiko Hayashi¹ (1. Hokkaido university)

6:30 PM - 6:50 PM

[2B6-GS-2-04] Efficient Stealthily Biased Sampling Using Sliced Wasserstein Distance

〇Yudai Yamamoto¹, Satoshi Hara¹ (1. Osaka University)

6:50 PM - 7:10 PM

[2B6-GS-2-05] Few-shot Concept Erasing from Text-to-Image Diffusion Models

〇Masane Fuchi¹, Tomohiro Takagi¹ (1. Meiji University)

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