Ying Wei - RankMe

112 papers A* 48A 1B 2Journal 49Unranked 12

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	One-Token Verification for Reasoning Correctness Estimation. CoRR Zhan Zhuang, Xiequn Wang, Zebin Chen, Feiyang Ye, Ying Wei, Kede Ma, Yu Zhang
2026	J	`jnl`	Scaling Reasoning Hop Exposes Weaknesses: Demystifying and Improving Hop Generalization in Large Language Models. CoRR Zhaoyi Li, Jiatong Li, Gangwei Jiang, Linqi Song, Defu Lian, Ying Wei
2025	—	`conf`	Automatic Expert Discovery in LLM Upcycling via Sparse Interpolated Mixture-of-Experts. ACL (1) Shengzhuang Chen, Ying Wei, Jonathan Richard Schwarz
2025	J	`jnl`	Automatic Expert Discovery in LLM Upcycling via Sparse Interpolated Mixture-of-Experts. CoRR Shengzhuang Chen, Ying Wei, Jonathan Richard Schwarz
2025	A*	`conf`	CLDyB: Towards Dynamic Benchmarking for Continual Learning with Pre-trained Models. ICLR Shengzhuang Chen, Yikai Liao, Xiaoxiao Sun, Kede Ma, Ying Wei
2025	J	`jnl`	CLDyB: Towards Dynamic Benchmarking for Continual Learning with Pre-trained Models. CoRR Shengzhuang Chen, Yikai Liao, Xiaoxiao Sun, Kede Ma, Ying Wei
2025	A*	`conf`	Come Together, But Not Right Now: A Progressive Strategy to Boost Low-Rank Adaptation. ICML Zhan Zhuang, Xiequn Wang, Wei Li, Yulong Zhang, Qiushi Huang, Shuhao Chen, Xuehao Wang, Yanbin Wei, Yuhe Nie, Kede Ma, Yu Zhang, Ying Wei
2025	J	`jnl`	Come Together, But Not Right Now: A Progressive Strategy to Boost Low-Rank Adaptation. CoRR Zhan Zhuang, Xiequn Wang, Wei Li, Yulong Zhang, Qiushi Huang, Shuhao Chen, Xuehao Wang, Yanbin Wei, Yuhe Nie, Kede Ma, Yu Zhang, Ying Wei
2025	J	`jnl`	Learning to Substitute Components for Compositional Generalization. CoRR Zhaoyi Li, Gangwei Jiang, Chenwang Wu, Ying Wei, Defu Lian, Enhong Chen
2025	J	`jnl`	Quantization Meets dLLMs: A Systematic Study of Post-training Quantization for Diffusion LLMs. CoRR Haokun Lin, Haobo Xu, Yichen Wu, Ziyu Guo, Renrui Zhang, Zhichao Lu, Ying Wei, Qingfu Zhang, Zhenan Sun
2025	A*	`conf`	Reaction Graph: Towards Reaction-Level Modeling for Chemical Reactions with 3D Structures. ICML Yingzhao Jian, Yue Zhang, Ying Wei, Hehe Fan, Yi Yang
2025	J	`jnl`	S-LoRA: Scalable Low-Rank Adaptation for Class Incremental Learning. CoRR Yichen Wu, Hongming Piao, Long-Kai Huang, Renzhen Wang, Wanhua Li, Hanspeter Pfister, Deyu Meng, Kede Ma, Ying Wei
2025	A*	`conf`	SD-LoRA: Scalable Decoupled Low-Rank Adaptation for Class Incremental Learning. ICLR Yichen Wu, Hongming Piao, Long-Kai Huang, Renzhen Wang, Wanhua Li, Hanspeter Pfister, Deyu Meng, Kede Ma, Ying Wei
2025	J	`jnl`	TokLIP: Marry Visual Tokens to CLIP for Multimodal Comprehension and Generation. CoRR Haokun Lin, Teng Wang, Yixiao Ge, Yuying Ge, Zhichao Lu, Ying Wei, Qingfu Zhang, Zhenan Sun, Ying Shan
2025	A*	`conf`	Unlocking the Power of Function Vectors for Characterizing and Mitigating Catastrophic Forgetting in Continual Instruction Tuning. ICLR Gangwei Jiang, Caigao Jiang, Zhaoyi Li, Siqiao Xue, Jun Zhou, Linqi Song, Defu Lian, Ying Wei
2025	J	`jnl`	Unlocking the Power of Function Vectors for Characterizing and Mitigating Catastrophic Forgetting in Continual Instruction Tuning. CoRR Gangwei Jiang, Caigao Jiang, Zhaoyi Li, Siqiao Xue, Jun Zhou, Linqi Song, Defu Lian, Ying Wei
2025	A*	`conf`	What Makes a Good Reasoning Chain? Uncovering Structural Patterns in Long Chain-of-Thought Reasoning. EMNLP Gangwei Jiang, Yahui Liu, Zhaoyi Li, Wei Bi, Fuzheng Zhang, Linqi Song, Ying Wei, Defu Lian
2025	J	`jnl`	What Makes a Good Reasoning Chain? Uncovering Structural Patterns in Long Chain-of-Thought Reasoning. CoRR Gangwei Jiang, Yahui Liu, Zhaoyi Li, Qi Wang, Fuzheng Zhang, Linqi Song, Ying Wei, Defu Lian
2024	B	`conf`	A Multi-objective Perspective Towards Improving Meta-Generalization. IJCNN Weiduo Liao, Ying Wei, Qirui Sun, Qingfu Zhang, Hisao Ishibuchi
2024	A*	`conf`	Active Retrosynthetic Planning Aware of Route Quality. ICLR Luotian Yuan, Yemin Yu, Ying Wei, Yongwei Wang, Zhihua Wang, Fei Wu
2024	—	`conf`	Benchmarking and Improving Compositional Generalization of Multi-aspect Controllable Text Generation. ACL (1) Tianqi Zhong, Zhaoyi Li, Quan Wang, Linqi Song, Ying Wei, Defu Lian, Zhendong Mao
2024	J	`jnl`	Benchmarking and Improving Compositional Generalization of Multi-aspect Controllable Text Generation. CoRR Tianqi Zhong, Zhaoyi Li, Quan Wang, Linqi Song, Ying Wei, Defu Lian, Zhendong Mao
2024	A*	`conf`	DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs. NeurIPS Haokun Lin, Haobo Xu, Yichen Wu, Jingzhi Cui, Yingtao Zhang, Linzhan Mou, Linqi Song, Zhenan Sun, Ying Wei
2024	A*	`conf`	Federated Continual Learning via Prompt-based Dual Knowledge Transfer. ICML Hongming Piao, Yichen Wu, Dapeng Wu, Ying Wei
2024	J	`jnl`	From Words to Molecules: A Survey of Large Language Models in Chemistry. CoRR Chang Liao, Yemin Yu, Yu Mei, Ying Wei
2024	J	`jnl`	Global-local aware Heterogeneous Graph Contrastive Learning for multifaceted association prediction in miRNA-gene-disease networks. Briefings Bioinform. Yuxuan Si, Zihan Huang, Zhengqing Fang, Zhouhang Yuan, Zhengxing Huang, Yingming Li, Ying Wei, Fei Wu, Yu-Feng Yao
2024	J	`jnl`	Interpretable Catastrophic Forgetting of Large Language Model Fine-tuning via Instruction Vector. CoRR Gangwei Jiang, Caigao Jiang, Zhaoyi Li, Siqiao Xue, Jun Zhou, Linqi Song, Defu Lian, Ying Wei
2024	A*	`conf`	Learning Where to Edit Vision Transformers. NeurIPS Yunqiao Yang, Long-Kai Huang, Shengzhuang Chen, Kede Ma, Ying Wei
2024	J	`jnl`	Learning Where to Edit Vision Transformers. CoRR Yunqiao Yang, Long-Kai Huang, Shengzhuang Chen, Kede Ma, Ying Wei
2024	A*	`conf`	Meta Continual Learning Revisited: Implicitly Enhancing Online Hessian Approximation via Variance Reduction. ICLR Yichen Wu, Long-Kai Huang, Renzhen Wang, Deyu Meng, Ying Wei
2024	A*	`conf`	Mitigating Catastrophic Forgetting in Online Continual Learning by Modeling Previous Task Interrelations via Pareto Optimization. ICML Yichen Wu, Hong Wang, Peilin Zhao, Yefeng Zheng, Ying Wei, Long-Kai Huang
2024	A*	`conf`	Mitigating the Language Mismatch and Repetition Issues in LLM-based Machine Translation via Model Editing. EMNLP Weichuan Wang, Zhaoyi Li, Defu Lian, Chen Ma, Linqi Song, Ying Wei
2024	J	`jnl`	Mitigating the Language Mismatch and Repetition Issues in LLM-based Machine Translation via Model Editing. CoRR Weichuan Wang, Zhaoyi Li, Defu Lian, Chen Ma, Linqi Song, Ying Wei
2024	A*	`conf`	MoPE-CLIP: Structured Pruning for Efficient Vision-Language Models with Module-Wise Pruning Error Metric. CVPR Haokun Lin, Haoli Bai, Zhili Liu, Lu Hou, Muyi Sun, Linqi Song, Ying Wei, Zhenan Sun
2024	J	`jnl`	MoPE-CLIP: Structured Pruning for Efficient Vision-Language Models with Module-wise Pruning Error Metric. CoRR Haokun Lin, Haoli Bai, Zhili Liu, Lu Hou, Muyi Sun, Linqi Song, Ying Wei, Zhenan Sun
2024	A*	`conf`	RetroOOD: Understanding Out-of-Distribution Generalization in Retrosynthesis Prediction. AAAI Yemin Yu, Luotian Yuan, Ying Wei, Hanyu Gao, Fei Wu, Zhihua Wang, Xinhai Ye
2024	J	`jnl`	Rotation and Permutation for Advanced Outlier Management and Efficient Quantization of LLMs. CoRR Haokun Lin, Haobo Xu, Yichen Wu, Jingzhi Cui, Yingtao Zhang, Linzhan Mou, Linqi Song, Zhenan Sun, Ying Wei
2024	A*	`conf`	Time-Varying LoRA: Towards Effective Cross-Domain Fine-Tuning of Diffusion Models. NeurIPS Zhan Zhuang, Yulong Zhang, Xuehao Wang, Jiangang Lu, Ying Wei, Yu Zhang
2024	—	`conf`	Understanding and Patching Compositional Reasoning in LLMs. ACL (Findings) Zhaoyi Li, Gangwei Jiang, Hong Xie, Linqi Song, Defu Lian, Ying Wei
2024	J	`jnl`	Understanding and Patching Compositional Reasoning in LLMs. CoRR Zhaoyi Li, Gangwei Jiang, Hong Xie, Linqi Song, Defu Lian, Ying Wei
2024	A*	`conf`	Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts. ICML Shengzhuang Chen, Jihoon Tack, Yunqiao Yang, Yee Whye Teh, Jonathan Richard Schwarz, Ying Wei
2024	J	`jnl`	Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts. CoRR Shengzhuang Chen, Jihoon Tack, Yunqiao Yang, Yee Whye Teh, Jonathan Richard Schwarz, Ying Wei
2023	—	`conf`	A Joint Attention Module and Deformable Transformer Network for Hyperparathyroidism Detection. BIBM Qing Guo, Jie Yang, Yufeng Xiao, Huaqing Wang, Mingan Yu, Ying Wei, Zhenlong Zhao
2023	A*	`conf`	Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspective. CVPR Weixia Zhang, Guangtao Zhai, Ying Wei, Xiaokang Yang, Kede Ma
2023	J	`jnl`	Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspective. CoRR Weixia Zhang, Guangtao Zhai, Ying Wei, Xiaokang Yang, Kede Ma
2023	A*	`conf`	Concept-wise Fine-tuning Matters in Preventing Negative Transfer. ICCV Yunqiao Yang, Long-Kai Huang, Ying Wei
2023	J	`jnl`	Concept-wise Fine-tuning Matters in Preventing Negative Transfer. CoRR Yunqiao Yang, Long-Kai Huang, Ying Wei
2023	J	`jnl`	DeepAlgPro: an interpretable deep neural network model for predicting allergenic proteins. Briefings Bioinform. Chun He, Xinhai Ye, Yi Yang, Liya Hu, Yuxuan Si, Xianxin Zhao, Longfei Chen, Qi Fang, Ying Wei, Fei Wu, Gongyin Ye
2023	A*	`conf`	Does Continual Learning Meet Compositionality? New Benchmarks and An Evaluation Framework. NeurIPS Weiduo Liao, Ying Wei, Mingchen Jiang, Qingfu Zhang, Hisao Ishibuchi
2023	A*	`conf`	Learning Chemical Rules of Retrosynthesis with Pre-training. AAAI Yinjie Jiang, Ying Wei, Fei Wu, Zhengxing Huang, Kun Kuang, Zhihua Wang
2023	—	`conf`	Learning to Substitute Spans towards Improving Compositional Generalization. ACL (1) Zhaoyi Li, Ying Wei, Defu Lian
2023	J	`jnl`	Learning to Substitute Spans towards Improving Compositional Generalization. CoRR Zhaoyi Li, Ying Wei, Defu Lian
2023	J	`jnl`	On the Opportunities of Green Computing: A Survey. CoRR You Zhou, Xiujing Lin, Xiang Zhang, Maolin Wang, Gangwei Jiang, Huakang Lu, Yupeng Wu, Kai Zhang, Zhe Yang, Kehang Wang, Yongduo Sui, Fengwei Jia, Zuoli Tang, Yao Zhao, Hongxuan Zhang, Tiannuo Yang, Weibo Chen, Yunong Mao, Yi Li, De Bao, Yu Li, Hongrui Liao, Ting Liu, Jingwen Liu, Jinchi Guo, Xiangyu Zhao, Ying Wei, Hong Qian, Qi Liu, Xiang Wang, Wai Kin Chan, Chenliang Li, Yusen Li, Shiyu Yang, Jining Yan, Chao Mou, Shuai Han, Wuxia Jin, Guannan Zhang, Xiaodong Zeng
2023	J	`jnl`	RetroOOD: Understanding Out-of-Distribution Generalization in Retrosynthesis Prediction. CoRR Yemin Yu, Luotian Yuan, Ying Wei, Hanyu Gao, Xinhai Ye, Zhihua Wang, Fei Wu
2023	A*	`conf`	Secure Out-of-Distribution Task Generalization with Energy-Based Models. NeurIPS Shengzhuang Chen, Long-Kai Huang, Jonathan Richard Schwarz, Yilun Du, Ying Wei
2023	J	`jnl`	Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompt. CoRR Gangwei Jiang, Caigao Jiang, Siqiao Xue, James Y. Zhang, Jun Zhou, Defu Lian, Ying Wei
2023	—	`conf`	Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompts. EMNLP (Findings) Gangwei Jiang, Caigao Jiang, Siqiao Xue, James Zhang, Jun Zhou, Defu Lian, Ying Wei
2022	B	`conf`	A Benchmark and Transformer-based Approach for Automated Hyperparathyroidism Detection. SMC Qing Guo, Yufeng Xiao, Huaqing Wang, Mingan Yu, Ying Wei, Zhenlong Zhao
2022	A*	`conf`	Adversarial Task Up-sampling for Meta-learning. NeurIPS Yichen Wu, Long-Kai Huang, Ying Wei
2022	—	`conf`	Disentangling Task Relations for Few-shot Text Classification via Self-Supervised Hierarchical Task Clustering. EMNLP (Findings) Juan Zha, Zheng Li, Ying Wei, Yu Zhang
2022	J	`jnl`	Disentangling Task Relations for Few-shot Text Classification via Self-Supervised Hierarchical Task Clustering. CoRR Juan Zha, Zheng Li, Ying Wei, Yu Zhang
2022	A*	`conf`	Frustratingly Easy Transferability Estimation. ICML Long-Kai Huang, Junzhou Huang, Yu Rong, Qiang Yang, Ying Wei
2022	A*	`conf`	GRASP: Navigating Retrosynthetic Planning with Goal-driven Policy. NeurIPS Yemin Yu, Ying Wei, Kun Kuang, Zhengxing Huang, Huaxiu Yao, Fei Wu
2022	A*	`conf`	Improving Task-Specific Generalization in Few-Shot Learning via Adaptive Vicinal Risk Minimization. NeurIPS Long-Kai Huang, Ying Wei
2022	J	`jnl`	Learning to generate imaginary tasks for improving generalization in meta-learning. CoRR Yichen Wu, Long-Kai Huang, Ying Wei
2022	A*	`conf`	Self-Supervised Text Erasing with Controllable Image Synthesis. ACM Multimedia Gangwei Jiang, Shiyao Wang, Tiezheng Ge, Yuning Jiang, Ying Wei, Defu Lian
2022	J	`jnl`	Self-Supervised Text Erasing with Controllable Image Synthesis. CoRR Gangwei Jiang, Shiyao Wang, Tiezheng Ge, Yuning Jiang, Ying Wei, Defu Lian
2022	A*	`conf`	The Role of Deconfounding in Meta-learning. ICML Yinjie Jiang, Zhengyu Chen, Kun Kuang, Luotian Yuan, Xinhai Ye, Zhihua Wang, Fei Wu, Ying Wei
2021	J	`jnl`	Frustratingly Easy Transferability Estimation. CoRR Long-Kai Huang, Ying Wei, Yu Rong, Qiang Yang, Junzhou Huang
2021	A*	`conf`	Functionally Regionalized Knowledge Transfer for Low-resource Drug Discovery. NeurIPS Huaxiu Yao, Ying Wei, Long-Kai Huang, Ding Xue, Junzhou Huang, Zhenhui Li
2021	A*	`conf`	Improving Generalization in Meta-learning via Task Augmentation. ICML Huaxiu Yao, Long-Kai Huang, Linjun Zhang, Ying Wei, Li Tian, James Zou, Junzhou Huang, Zhenhui Li
2021	A*	`conf`	Meta-learning Hyperparameter Performance Prediction with Neural Processes. ICML Ying Wei, Peilin Zhao, Junzhou Huang
2021	A*	`conf`	Meta-learning with an Adaptive Task Scheduler. NeurIPS Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn
2021	J	`jnl`	Meta-learning with an Adaptive Task Scheduler. CoRR Huaxiu Yao, Yu Wang, Ying Wei, Peilin Zhao, Mehrdad Mahdavi, Defu Lian, Chelsea Finn
2021	—	`conf`	MetaTS: Meta Teacher-Student Network for Multilingual Sequence Labeling with Minimal Supervision. EMNLP (1) Zheng Li, Danqing Zhang, Tianyu Cao, Ying Wei, Yiwei Song, Bing Yin
2020	A*	`conf`	Adversarial Sparse Transformer for Time Series Forecasting. NeurIPS Sifan Wu, Xi Xiao, Qianggang Ding, Peilin Zhao, Ying Wei, Junzhou Huang
2020	J	`jnl`	COVID-DA: Deep Domain Adaptation from Typical Pneumonia to COVID-19. CoRR Yifan Zhang, Shuaicheng Niu, Zhen Qiu, Ying Wei, Peilin Zhao, Jianhua Yao, Junzhou Huang, Qingyao Wu, Mingkui Tan
2020	J	`jnl`	Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis. CoRR Yifan Zhang, Ying Wei, Qingyao Wu, Peilin Zhao, Shuaicheng Niu, Junzhou Huang, Mingkui Tan
2020	J	`jnl`	Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis. IEEE Trans. Image Process. Yifan Zhang, Ying Wei, Qingyao Wu, Peilin Zhao, Shuaicheng Niu, Junzhou Huang, Mingkui Tan
2020	J	`jnl`	Don't Overlook the Support Set: Towards Improving Generalization in Meta-learning. CoRR Huaxiu Yao, Longkai Huang, Ying Wei, Li Tian, Junzhou Huang, Zhenhui Li
2020	A	`conf`	Fisher Deep Domain Adaptation. SDM Yinghua Zhang, Yu Zhang, Ying Wei, Kun Bai, Yangqiu Song, Qiang Yang
2020	J	`jnl`	Fisher Deep Domain Adaptation. CoRR Yinghua Zhang, Yu Zhang, Ying Wei, Kun Bai, Yangqiu Song, Qiang Yang
2020	J	`jnl`	GROVER: Self-supervised Message Passing Transformer on Large-scale Molecular Data. CoRR Yu Rong, Yatao Bian, Tingyang Xu, Weiyang Xie, Ying Wei, Wenbing Huang, Junzhou Huang
2020	A*	`conf`	Graph Few-Shot Learning via Knowledge Transfer. AAAI Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li
2020	—	`conf`	Learn to Cross-lingual Transfer with Meta Graph Learning Across Heterogeneous Languages. EMNLP (1) Zheng Li, Mukul Kumar, William Headden, Bing Yin, Ying Wei, Yu Zhang, Qiang Yang
2020	—	`conf`	Recognition of Hyperparathyroidism based on Transfer Learning. BIBM Jiabo Chen, Qing Guo, Zixun Jiang, Huaqing Wang, Mingan Yu, Ying Wei
2020	A*	`conf`	Self-Supervised Graph Transformer on Large-Scale Molecular Data. NeurIPS Yu Rong, Yatao Bian, Tingyang Xu, Weiyang Xie, Ying Wei, Wenbing Huang, Junzhou Huang
2020	A*	`conf`	TranSlider: Transfer Ensemble Learning from Exploitation to Exploration. KDD Kuo Zhong, Ying Wei, Chun Yuan, Haoli Bai, Junzhou Huang
2019	J	`jnl`	Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis. CoRR Yifan Zhang, Ying Wei, Peilin Zhao, Shuaicheng Niu, Qingyao Wu, Mingkui Tan, Junzhou Huang
2019	A*	`conf`	Exploiting Coarse-to-Fine Task Transfer for Aspect-Level Sentiment Classification. AAAI Zheng Li, Ying Wei, Yu Zhang, Xiang Zhang, Xin Li
2019	—	`conf`	From Whole Slide Imaging to Microscopy: Deep Microscopy Adaptation Network for Histopathology Cancer Image Classification. MICCAI (1) Yifan Zhang, Hanbo Chen, Ying Wei, Peilin Zhao, Jiezhang Cao, Xinjuan Fan, Xiaoying Lou, Hailing Liu, Jinlong Hou, Xiao Han, Jianhua Yao, Qingyao Wu, Mingkui Tan, Junzhou Huang
2019	J	`jnl`	Graph Few-shot Learning via Knowledge Transfer. CoRR Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li
2019	A*	`conf`	Hierarchically Structured Meta-learning. ICML Huaxiu Yao, Ying Wei, Junzhou Huang, Zhenhui Li
2019	J	`jnl`	Hierarchically Structured Meta-learning. CoRR Huaxiu Yao, Ying Wei, Junzhou Huang, Zhenhui Li
2019	A*	`conf`	Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction. WWW Huaxiu Yao, Yiding Liu, Ying Wei, Xianfeng Tang, Zhenhui Li
2019	J	`jnl`	Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction. CoRR Huaxiu Yao, Yiding Liu, Ying Wei, Xianfeng Tang, Zhenhui Li
2019	—	`conf`	Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning. EMNLP/IJCNLP (1) Zheng Li, Xin Li, Ying Wei, Lidong Bing, Yu Zhang, Qiang Yang
2019	J	`jnl`	Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning. CoRR Zheng Li, Xin Li, Ying Wei, Lidong Bing, Yu Zhang, Qiang Yang
2019	J	`jnl`	Transferable Neural Processes for Hyperparameter Optimization. CoRR Ying Wei, Peilin Zhao, Huaxiu Yao, Junzhou Huang
2018	J	`jnl`	Exploiting Coarse-to-Fine Task Transfer for Aspect-level Sentiment Classification. CoRR Zheng Li, Ying Wei, Yu Zhang, Xiang Zhang, Xin Li, Qiang Yang
2018	A*	`conf`	Hierarchical Attention Transfer Network for Cross-Domain Sentiment Classification. AAAI Zheng Li, Ying Wei, Yu Zhang, Qiang Yang
2018	A*	`conf`	Learning to Multitask. NeurIPS Yu Zhang, Ying Wei, Qiang Yang
2018	J	`jnl`	Learning to Multitask. CoRR Yu Zhang, Ying Wei, Qiang Yang
2018	A*	`conf`	Transfer Learning via Learning to Transfer. ICML Ying Wei, Yu Zhang, Junzhou Huang, Qiang Yang
2018	A*	`conf`	Transferable Contextual Bandit for Cross-Domain Recommendation. AAAI Bo Liu, Ying Wei, Yu Zhang, Zhixian Yan, Qiang Yang
2017	A*	`conf`	Deep Neural Networks for High Dimension, Low Sample Size Data. IJCAI Bo Liu, Ying Wei, Yu Zhang, Qiang Yang
2017	A*	`conf`	End-to-End Adversarial Memory Network for Cross-domain Sentiment Classification. IJCAI Zheng Li, Yu Zhang, Ying Wei, Yuxiang Wu, Qiang Yang
2017	J	`jnl`	Learning to Transfer. CoRR Ying Wei, Yu Zhang, Qiang Yang
2016	J	`jnl`	Heterogeneous Translated Hashing: A Scalable Solution Towards Multi-Modal Similarity Search. ACM Trans. Knowl. Discov. Data Ying Wei, Yangqiu Song, Yi Zhen, Bo Liu, Qiang Yang
2016	A*	`conf`	Instilling Social to Physical: Co-Regularized Heterogeneous Transfer Learning. AAAI Ying Wei, Yin Zhu, Cane Wing-Ki Leung, Yangqiu Song, Qiang Yang
2016	A*	`conf`	Transfer Knowledge between Cities. KDD Ying Wei, Yu Zheng, Qiang Yang
2014	A*	`conf`	Scalable heterogeneous translated hashing. KDD Ying Wei, Yangqiu Song, Yi Zhen, Bo Liu, Qiang Yang