Session 4: Unsupervised, Semi-supervised Learning, Reinforcement Learning

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Information

Day 3 (Nov.19), talks: 10:50-11:30, poster session: 11:30-14:00

  • Each oral presentation consists of a 12-minute talk and a 2-minute discussion (except for best paper presentations).
  • Each spotlight presentation consists of 2.5-minute talk.
  • Both oral and spotlight presentations are also presented in the poster session.

List of papers

  • [Spotlight] [Poster: Tue13] Self-Weighted Multi-View Clustering with Deep Matrix Factorization
    • Beilei Cui (Dalian University of Technology); Hong Yu (Dalian University of Technology); Tiantian Zhang (Dalian University of Technology); Siwen Li (Dalian University of Technology) [Conference Track, Paper ID: 263]
  • [Spotlight] [Poster: Tue14] Latent Multi-view Semi-Supervised Classification
    • Xiaofan Bo (University of Electronic Science and Technology); Zhao Kang (University of Electronic Science and Technology of China); Zhitong Zhao (University of Electronic Science and Technology); yuanzhang su (University of Electronic Science and Technology); Wenyu Chen (University of Electronic Science and Technology of China) [Conference Track, Paper ID: 202]
  • [Spotlight] [Poster: Tue15] Self-Supervised Deep Multi-View Subspace Clustering
    • Xiukun Sun (Beijing Jiaotong University); Miaomiao Cheng (Beijing Jiaotong University); Chen Min (Beijing Jiaotong University); Liping Jing (Beijing Jiaotong University) [Conference Track, Paper ID: 374]
  • [Spotlight] [Poster: Tue16] Geometry-Aware Maximum Likelihood Estimation of Intrinsic Dimension
    • Marina Gomtsyan (Skolkovo Institute of Science and Technology); Nikita Mokrov (Skolkovo Institute of Science and Technology); Maxim Panov (Skolkovo Institute of Science and Technology); Yury Yanovich (Skolkovo Institute of Science and Technology) [Conference Track, Paper ID: 399]
  • [Spotlight] [Poster: Tue17] Exemplar Based Mixture Models with Censored Data
    • Masahiro Kohjima (NTT Corporation); Tatsushi Matsubayashi (NTT Corporation); Hiroyuki Toda (NTT) [Conference Track, Paper ID: 257]
  • [Spotlight] [Poster: Tue18] Efficient Learning of Restricted Boltzmann Machines Using Covariance estimates
    • Vidyadhar Upadhya (Indian Institute of Science, Bangalore); P. S.Sastry (Indian Institute of Science) [Conference Track, Paper ID: 325]
  • [Spotlight] [Poster: Tue19] Gradient-based Training of Slow Feature Analysis by Differentiable Approximate Whitening
    • Merlin Schueler (RUB); Hlynur Davíð Hlynsson (RUB); Laurenz Wiskott (RUB) [Conference Track, Paper ID: 139]
  • [Spotlight] [Poster: Tue20] Random Projection in Neural Episodic Control
    • Daichi Nishio (Kanazawa University); Satoshi Yamane (Kanazawa University) [Conference Track, Paper ID: 20]
  • [Spotlight] [Poster: Tue21] Active Change-Point Detection
    • Shogo Hayashi (Kyoto University); Yoshinobu Kawahara (Kyushu University / RIKEN); Hisashi Kashima (Kyoto University/RIKEN Center for AIP) [Conference Track, Paper ID: 382]
  • [Spotlight] [Poster: Tue22] Trust Region Sequential Variational Inference
    • Geon-Hyeong Kim (KAIST); Youngsoo Jang (KAIST); Jongmin Lee (KAIST); Wonseok Jeon (MILA, McGill University); Hongseok Yang (KAIST); Kee-Eung Kim (KAIST) [Conference Track, Paper ID: 385]
  • [Spotlight] [Poster: Tue23] Functional Isolation Forest
    • Guillaume Staerman (Télécom Paris); Pavlo Mozharovskyi (Télécom Paristech); Stéphan Clémençon (Télécom ParisTech); Florence d’Alche-Buc (Télécom ParisTech) [Conference Track, Paper ID: 191]