13 Papers Accepted at ICLR 2024

Congratulations to the following scientists from A*STAR’s Centre for Frontier AI Research (CFAR) whose papers have been accepted at the International Conference on Learning Representations (ICLR) 2024:

  • Prof Ivor Tsang, Director
  • Dr Cheston Tan, Senior Principal Scientist
  • Dr Atsushi Nitanda, Principal Scientist
  • Dr Joey Zhou, Principal Scientist
  • Dr Foo Chuan Sheng, Principal Scientist
  • Dr Guo Qing, Senior Scientist
  • Dr He Yang, Scientist
  • Dr Lyu Yueming, Scientist

Held from 7 – 11 May 2024 at Vienna, Austria, ICLR 2024 is a globally renowned conference in the field of deep learning. The annual conference features cutting-edge research on all aspects of deep learning used in the fields of artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, text understanding, gaming, and robotics.

List of accepted papers:

  1. IRAD: Implicit Representation-driven Image Resampling Against Adversarial Attacks
    Yue Cao, Tianlin Li, Xiaofeng Cao, Ivor Tsang, Yang Liu, Qing Guo
  2. LRR: Language-driven Resamplable Continuous Representation Against Adversarial Tracking Attacks
    Jianlang Chen, Xuhong Ren, Qing Guo, Felix Juefei-Xu, Di Lin, Wei Feng, Lei Ma, Jianjun Zhao
  3. Koopman-Based Bound for Generalisation: New Aspect of Neural Networks Regarding Nonlinear Noise Filtering
    Yuka Hashimoto, Sho Sonoda, Isao Ishikawa, Atsushi Nitanda, and Taiji Suzuki
  4. Anisotropy Helps: Improved Statistical and Computational Complexity of the Mean-Field Langevin Dynamics Under Structured Data
    Atsushi Nitanda, Kazusato Oko, Taiji Suzuki, and Denny Wu
  5. Multisize Dataset Condensation (Oral presentation)
    Yang He, Lingao Xiao, Joey Tianyi Zhou, Ivor Tsang
  6. Data-independent Module-aware Pruning for Hierarchical Vision Transformers
    Yang He, Joey Tianyi Zhou
  7. FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data
    Zikai Xiao, Zihan Chen, Liyinglan Liu, Yang Feng, Jian Wu, Wanlu Liu, Joey Tianyi Zhou, Howard Hao Yang, Zuozhu Liu
  8. A Unified Framework for Bayesian Optimisation under Contextual Uncertainty
    Sebastian Shenghong Tay, Chuan-Sheng Foo, Daisuke Urano, Richalynn Leong, Bryan Kian Hsiang Low
  9. Self-Teaching Prompting for Multi-Intent Learning with Limited Supervision (Tiny Paper)
    Chen Cheng, Ivor Tsang
  10. Decentralised Riemannian Conjugate Gradient Method on the Stiefel Manifold
    Jun Chen, Haishan Ye, Mengmeng Wang, Tianxin Huang, Guang Dai, Ivor Tsang, Yong Liu
  11. On Harmonising Implicit Subpopulations
    Feng Hong, Jiangchao Yao, Yueming Lyu, Zhihan Zhou, Ivor Tsang, Ya Zhang, Yanfeng Wang
  12. Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning
    Feiyang Ye, Yueming Lyu, Xuehao Wang, Yu Zhang, Ivor Tsang
  13. Dissecting Zero-Shot Visual Reasoning Capabilities in Vision and Language Models (Tiny Paper)
    Aishik Nagar, Shantanu Jaiswal, Cheston Tan

Find out more about ICLR 2024.