We are pleased to announce that our new results on order learning will be presented in ICLR 2024.

• Seon-Ho Lee, Nyeong-Ho Shin, and Chang-Su Kim, “Unsupervised order learning,” in Proc. ICLR, Vienna, Austria, May 2024.

Congratuluations to Seon-Ho and Nyeong-Ho!

Order learning is a new concept that we proposed in a series of papers:

1. 1. Kyungsun Lim, Nyeong-Ho Shin, Young-Yoon Lee, and Chang-Su Kim, “Order learning and its application to age estimation,” ICLR 2020.
2. 2. Seon-Ho Lee and Chang-Su Kim, “Deep repulsive clustering of ordered data based on order-identity decomposition” ICLR 2021.
3. 3. Nyeong Ho Shin, Seon-Ho Lee, and Chang-Su Kim, “Moving window regression: A novel approach to ordinal regression,” CVPR 2022.
4. 4. Seon-Ho Lee and Chang-Su Kim, “Order learning using partially ordered data via chainization,” ECCV 2022.
5. 5. Seon-Ho Lee, Nyeong Ho Shin, and Chang-Su Kim, “Geometric order learning for rank estimation,” NeurIPS 2022.
6. 6. Seon-Ho Lee, Nyeong-Ho Shin, and Chang-Su Kim, “Unsupervised order learning,” ICLR 2024.

The very first exploration of order learning (from fully supervised to unsupervised) is now complete, and the second stage started.