Jiang, Daniel

14 publications

NeurIPS 2025 CATransformers: Carbon Aware Transformers Through Joint Model-Hardware Optimization Irene Wang, Mostafa Elhoushi, H Ekin Sumbul, Samuel Hsia, Daniel Jiang, Newsha Ardalani, Divya Mahajan, Carole-Jean Wu, Bilge Acun

ICLR 2025 Exploiting Structure in Offline Multi-Agent RL: The Benefits of Low Interaction Rank Wenhao Zhan, Scott Fujimoto, Zheqing Zhu, Jason D. Lee, Daniel Jiang, Yonathan Efroni

ICLR 2025 On the Linear Speedup of Personalized Federated Reinforcement Learning with Shared Representations Guojun Xiong, Shufan Wang, Daniel Jiang, Jian Li

NeurIPS 2025 Towards Understanding Camera Motions in Any Video Zhiqiu Lin, Siyuan Cen, Daniel Jiang, Jay Karhade, Hewei Wang, Chancharik Mitra, Yu Tong Tiffany Ling, Yuhan Huang, Rushikesh Zawar, Xue Bai, Yilun Du, Chuang Gan, Deva Ramanan

NeurIPSW 2024 Aligned Multi-Objective Optimization Yonathan Efroni, Daniel Jiang, Ben Kretzu, Jalaj Bhandari, Zheqing Zhu, Karen Ullrich

NeurIPS 2024 NaturalBench: Evaluating Vision-Language Models on Natural Adversarial Samples Baiqi Li, Zhiqiu Lin, Wenxuan Peng, Jean de Dieu Nyandwi, Daniel Jiang, Zixian Ma, Simran Khanuja, Ranjay Krishna, Graham Neubig, Deva Ramanan

MLOSS 2024 Pearl: A Production-Ready Reinforcement Learning Agent Zheqing Zhu, Rodrigo de Salvo Braz, Jalaj Bhandari, Daniel Jiang, Yi Wan, Yonathan Efroni, Liyuan Wang, Ruiyang Xu, Hongbo Guo, Alex Nikulkov, Dmytro Korenkevych, Urun Dogan, Frank Cheng, Zheng Wu, Wanqiao Xu

NeurIPS 2023 Weakly Coupled Deep Q-Networks Ibrahim El Shar, Daniel Jiang

NeurIPS 2021 Multi-Step Budgeted Bayesian Optimization with Unknown Evaluation Costs Raul Astudillo, Daniel Jiang, Maximilian Balandat, Eytan Bakshy, Peter Frazier

NeurIPS 2020 BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization Maximilian Balandat, Brian Karrer, Daniel Jiang, Samuel Daulton, Ben Letham, Andrew G Wilson, Eytan Bakshy

NeurIPS 2020 Efficient Nonmyopic Bayesian Optimization via One-Shot Multi-Step Trees Shali Jiang, Daniel Jiang, Maximilian Balandat, Brian Karrer, Jacob Gardner, Roman Garnett

ICML 2020 Lookahead-Bounded Q-Learning Ibrahim El Shar, Daniel Jiang

AISTATS 2020 The Power of Batching in Multiple Hypothesis Testing Tijana Zrnic, Daniel Jiang, Aaditya Ramdas, Michael Jordan

ICML 2018 Feedback-Based Tree Search for Reinforcement Learning Daniel Jiang, Emmanuel Ekwedike, Han Liu