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Seven papers accepted to ICML 2024

Seven papers authored by Computer Science researchers from ý have been accepted for publication at the , one of the top three global venues for machine learning research, which will be held on 21-27 July 2024 in Vienna, Austria:

  • Agent-Specific Effects: A Causal Effect Propagation Analysis in Multi-Agent MDPs, by Stelios Triantafyllou, Aleksa Sukovic, , and Goran Radanovic
  • Dynamic Facility Location in High Dimensional Euclidean Spaces, by , Gramoz Goranci, Shaofeng Jiang, Yi Qian, and Yubo Zhang
  • High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization, by Yihang Chen, , Taiji Suzuki, and Volkan Cevher
  • Revisiting character-level adversarial attacks, by Elias Abad Rocamora, Yongtao Wu, , Grigorios Chrysos, and Volkan Cevher
  • Reward Model Learning vs. Direct Policy Optimization: A Comparative Analysis of Learning from Human Preferences, by Andi Nika, , Parameswaran Kamalaruban, Georgios Tzannetos, Goran Radanovic, and Adish Singla
  • To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models, by George-Octavian Bărbulescu and Peter Triantafillou
  • Towards Neural Architecture Search through Hierarchical Generative Modeling, by Lichuan Xiang, Łukasz Dudziak, Mohamed Abdelfattah, Abhinav Mehrotra, Nicholas Lane, and

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