Hong-Min Chu - RankMe

20 papers A* 8C 1Journal 9Unranked 2

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	NEFTune: Noisy Embeddings Improve Instruction Finetuning. ICLR Neel Jain, Ping-Yeh Chiang, Yuxin Wen, John Kirchenbauer, Hong-Min Chu, Gowthami Somepalli, Brian R. Bartoldson, Bhavya Kailkhura, Avi Schwarzschild, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
2024	A*	`conf`	Universal Guidance for Diffusion Models. ICLR Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	A*	`conf`	Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise. NeurIPS Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	J	`jnl`	NEFTune: Noisy Embeddings Improve Instruction Finetuning. CoRR Neel Jain, Ping-Yeh Chiang, Yuxin Wen, John Kirchenbauer, Hong-Min Chu, Gowthami Somepalli, Brian R. Bartoldson, Bhavya Kailkhura, Avi Schwarzschild, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	A*	`conf`	Panning for Gold in Federated Learning: Targeted Text Extraction under Arbitrarily Large-Scale Aggregation. ICLR Hong-Min Chu, Jonas Geiping, Liam H. Fowl, Micah Goldblum, Tom Goldstein
2023	—	`conf`	Universal Guidance for Diffusion Models. CVPR Workshops Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	J	`jnl`	Universal Guidance for Diffusion Models. CoRR Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein
2022	J	`jnl`	Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise. CoRR Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie S. Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, Tom Goldstein
2021	J	`jnl`	Active Learning at the ImageNet Scale. CoRR Zeyad Ali Sami Emam, Hong-Min Chu, Ping-Yeh Chiang, Wojciech Czaja, Richard Leapman, Micah Goldblum, Tom Goldstein
2021	A*	`conf`	WrapNet: Neural Net Inference with Ultra-Low-Precision Arithmetic. ICLR Renkun Ni, Hong-Min Chu, Oscar Castañeda, Ping-Yeh Chiang, Christoph Studer, Tom Goldstein
2020	J	`jnl`	WrapNet: Neural Net Inference with Ultra-Low-Resolution Arithmetic. CoRR Renkun Ni, Hong-Min Chu, Oscar Castañeda, Ping-Yeh Chiang, Christoph Studer, Tom Goldstein
2019	C	`conf`	Deep Learning with a Rethinking Structure for Multi-label Classification. ACML Yao-Yuan Yang, Yi-An Lin, Hong-Min Chu, Hsuan-Tien Lin
2019	J	`jnl`	Dynamic principal projection for cost-sensitive online multi-label classification. Mach. Learn. Hong-Min Chu, Kuan-Hao Huang, Hsuan-Tien Lin
2018	—	`conf`	Deep Generative Models for Weakly-Supervised Multi-Label Classification. ECCV (2) Hong-Min Chu, Chih-Kuan Yeh, Yu-Chiang Frank Wang
2018	J	`jnl`	Deep Learning with a Rethinking Structure for Multi-label Classification. CoRR Yao-Yuan Yang, Yi-An Lin, Hong-Min Chu, Hsuan-Tien Lin
2018	A*	`conf`	Robust Distributed Anomaly Detection Using Optimal Weighted One-Class Random Forests. ICDM Yu-Lin Tsou, Hong-Min Chu, Cong Li, Shao-Wen Yang
2018	A*	`conf`	Scheduling in Visual Fog Computing: NP-Completeness and Practical Efficient Solutions. AAAI Hong-Min Chu, Shao-Wen Yang, Padmanabhan Pillai, Yen-Kuang Chen
2017	J	`jnl`	Dynamic Principal Projection for Cost-Sensitive Online Multi-Label Classification. CoRR Hong-Min Chu, Kuan-Hao Huang, Hsuan-Tien Lin
2016	A*	`conf`	Can Active Learning Experience Be Transferred? ICDM Hong-Min Chu, Hsuan-Tien Lin
2016	J	`jnl`	Can Active Learning Experience Be Transferred? CoRR Hong-Min Chu, Hsuan-Tien Lin