Ryumei Nakada - RankMe

19 papers A* 1A 1Journal 16Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	PEANuT: Parameter-Efficient Adaptation with Weight-aware Neural Tweakers. KDD (1) Yibo Zhong, Haoxiang Jiang, Lincan Li, Ryumei Nakada, Tianci Liu, Linjun Zhang, Huaxiu Yao, Haoyu Wang
2025	J	`jnl`	A Theoretical Framework for Prompt Engineering: Approximating Smooth Functions with Transformer Prompts. CoRR Ryumei Nakada, Wenlong Ji, Tianxi Cai, James Zou, Linjun Zhang
2025	J	`jnl`	Contrastive Network Representation Learning. CoRR Zihan Dong, Xin Zhou, Ryumei Nakada, Lexin Li, Linjun Zhang
2025	J	`jnl`	Residual Feature Integration is Sufficient to Prevent Negative Transfer. CoRR Yichen Xu, Ryumei Nakada, Linjun Zhang, Lexin Li
2024	J	`jnl`	Contrastive Learning on Multimodal Analysis of Electronic Health Records. CoRR Tianxi Cai, Feiqing Huang, Ryumei Nakada, Linjun Zhang, Doudou Zhou
2024	J	`jnl`	Differentially Private Federated Learning: Servers Trustworthiness, Estimation, and Statistical Inference. CoRR Zhe Zhang, Ryumei Nakada, Linjun Zhang
2024	J	`jnl`	NEAT: Nonlinear Parameter-efficient Adaptation of Pre-trained Models. CoRR Yibo Zhong, Haoxiang Jiang, Lincan Li, Ryumei Nakada, Tianci Liu, Linjun Zhang, Huaxiu Yao, Haoyu Wang
2024	A*	`conf`	S NeurIPS Xinyu Yang, Jixuan Leng, Geyang Guo, Jiawei Zhao, Ryumei Nakada, Linjun Zhang, Huaxiu Yao, Beidi Chen
2024	J	`jnl`	S CoRR Xinyu Yang, Jixuan Leng, Geyang Guo, Jiawei Zhao, Ryumei Nakada, Linjun Zhang, Huaxiu Yao, Beidi Chen
2024	J	`jnl`	Synthetic Oversampling: Theory and A Practical Approach Using LLMs to Address Data Imbalance. CoRR Ryumei Nakada, Yichen Xu, Lexin Li, Linjun Zhang
2023	J	`jnl`	Safeguarding Data in Multimodal AI: A Differentially Private Approach to CLIP Training. CoRR Alyssa Huang, Peihan Liu, Ryumei Nakada, Linjun Zhang, Wanrong Zhang
2023	J	`jnl`	The Power of Contrast for Feature Learning: A Theoretical Analysis. J. Mach. Learn. Res. Wenlong Ji, Zhun Deng, Ryumei Nakada, James Zou, Linjun Zhang
2023	A	`conf`	Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data. AISTATS Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang
2023	J	`jnl`	Understanding Multimodal Contrastive Learning and Incorporating Unpaired Data. CoRR Ryumei Nakada, Halil Ibrahim Gulluk, Zhun Deng, Wenlong Ji, James Zou, Linjun Zhang
2021	J	`jnl`	Asymptotic Risk of Overparameterized Likelihood Models: Double Descent Theory for Deep Neural Networks. CoRR Ryumei Nakada, Masaaki Imaizumi
2021	J	`jnl`	Shrinkage estimation with singular priors and an application to small area estimation. J. Multivar. Anal. Ryumei Nakada, Tatsuya Kubokawa, Malay Ghosh, Sayar Karmakar
2021	J	`jnl`	The Power of Contrast for Feature Learning: A Theoretical Analysis. CoRR Wenlong Ji, Zhun Deng, Ryumei Nakada, James Zou, Linjun Zhang
2020	J	`jnl`	Adaptive Approximation and Generalization of Deep Neural Network with Intrinsic Dimensionality. J. Mach. Learn. Res. Ryumei Nakada, Masaaki Imaizumi
2019	J	`jnl`	Adaptive Approximation and Estimation of Deep Neural Network to Intrinsic Dimensionality. CoRR Ryumei Nakada, Masaaki Imaizumi