Tianjin Huang - RankMe

68 papers A* 10A 3B 1C 2Journal 45Unranked 7

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Beyond Segmentation: An Oil Spill Change Detection Framework Using Synthetic SAR Imagery. CoRR Chenyang Lai, Shuaiyu Chen, Tianjin Huang, Siyang Song, Guangliang Cheng, Chunbo Luo, Zeyu Fu
2026	J	`jnl`	Confusion-Aware Spectral Regularizer for Long-Tailed Recognition. CoRR Ziquan Zhu, Gaojie Jin, Hanruo Zhu, Si-Yuan Lu, Yunxiao Zhang, Zeyu Fu, Ronghui Mu, Guoqiang Zhang, Zhao Sun, Xia Yuhang, Jiaxing Shang, Xiang Li, Lu Liu, Tianjin Huang
2026	J	`jnl`	Dual-Kernel Adapter: Expanding Spatial Horizons for Data-Constrained Medical Image Analysis. CoRR Ziquan Zhu, Hanruo Zhu, Siyuan Lu, Xiang Li, Yanda Meng, Gaojie Jin, Lu Yin, Lijie Hu, Di Wang, Lu Liu, Tianjin Huang
2026	A	`conf`	SARC: Sentiment-Augmented Deep Role Clustering for Fake News Detection. WSDM Jingqing Wang, Jiaxing Shang, Rong Xu, Fei Hao, Tianjin Huang, Geyong Min
2026	J	`jnl`	SCOPE: Scene-Contextualized Incremental Few-Shot 3D Segmentation. CoRR Vishal Thengane, Zhaochong An, Tianjin Huang, Son Lam Phung, Abdesselam Bouzerdoum, Lu Yin, Na Zhao, Xiatian Zhu
2026	J	`jnl`	StealthMark: Harmless and Stealthy Ownership Verification for Medical Segmentation via Uncertainty-Guided Backdoors. CoRR Qinkai Yu, Chong Zhang, Gaojie Jin, Tianjin Huang, Wei Zhou, Wenhui Li, Xiaobo Jin, Bo Huang, Yitian Zhao, Guang Yang, Gregory Yoke Hong Lip, Yalin Zheng, Aline Villavicencio, Yanda Meng
2026	J	`jnl`	StealthMark: Harmless and Stealthy Ownership Verification for Medical Segmentation via Uncertainty-Guided Backdoors. IEEE Trans. Image Process. Qinkai Yu, Chong Zhang, Gaojie Jin, Tianjin Huang, Wei Zhou, Wenhui Li, Xiaobo Jin, Bo Huang, Yitian Zhao, Guang Yang, Gregory Yoke Hong Lip, Yalin Zheng, Aline Villavicencio, Yanda Meng
2026	A*	`conf`	TimeCAP: A Channel-Aware Pre-Training Framework for Multivariate Time Series Forecasting. AAAI Chuanru Ren, Yao Lu, Tianjin Huang, Haowen Zheng, Hengde Zhu, Yunyin Li, Hengxiao Li, Lu Liu
2026	J	`jnl`	Unraveling the impact of environmental factors on wheat yield across the European Union via explainable machine learning. Comput. Electron. Agric. Wei Zhou, Wang Zhou, Davide Cammarano, Klaus Butterbach-Bahl, Jørgen E. Olesen, Zhixian Lin, Tianjin Huang, Gaochao Cai, Jingwen Zhang, Jianxiu Qiu, Sheng Wang
2025	—	`conf`	Benchmarking Audio Deepfake Detection Robustness in Real-World Communication Scenarios. EUSIPCO Haohan Shi, Xiyu Shi, Safak Dogan, Saif Alzubi, Tianjin Huang, Yunxiao Zhang
2025	A*	`conf`	Composable Interventions for Language Models. ICLR Arinbjörn Kolbeinsson, Kyle O'Brien, Tianjin Huang, Shanghua Gao, Shiwei Liu, Jonathan Richard Schwarz, Anurag Jayant Vaidya, Faisal Mahmood, Marinka Zitnik, Tianlong Chen, Thomas Hartvigsen
2025	A*	`conf`	Enhancing Robust Fairness via Confusional Spectral Regularization. ICLR Gaojie Jin, Sihao Wu, Jiaxu Liu, Tianjin Huang, Ronghui Mu
2025	J	`jnl`	Enhancing Robust Fairness via Confusional Spectral Regularization. CoRR Gaojie Jin, Sihao Wu, Jiaxu Liu, Tianjin Huang, Ronghui Mu
2025	J	`jnl`	FS-GNN: Improving Fairness in Graph Neural Networks via Joint Sparsification. Neurocomputing Jiaxu Zhao, Tianjin Huang, Shiwei Liu, Jie Yin, Yulong Pei, Meng Fang, Mykola Pechenizkiy
2025	J	`jnl`	Few-Shot Oriented Object Detection in Remote Sensing Images via Memorable Contrastive Learning. IEEE Trans. Geosci. Remote. Sens. Jiawei Zhou, Wuzhou Li, Yi Cao, Hongtao Cai, Tianjin Huang, Gui-Song Xia, Xiang Li
2025	J	`jnl`	Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models. CoRR Liangyu Wang, Huanyi Xie, Xinhai Wang, Tianjin Huang, Mengdi Li, Di Wang
2025	A*	`conf`	LIFT the Veil for the Truth: Principal Weights Emerge after Rank Reduction for Reasoning-Focused Supervised Fine-Tuning. ICML Zihang Liu, Tianyu Pang, Oleg Balabanov, Chaoqun Yang, Tianjin Huang, Lu Yin, Yaoqing Yang, Shiwei Liu
2025	J	`jnl`	LIFT the Veil for the Truth: Principal Weights Emerge after Rank Reduction for Reasoning-Focused Supervised Fine-Tuning. CoRR Zihang Liu, Tianyu Pang, Oleg Balabanov, Chaoqun Yang, Tianjin Huang, Lu Yin, Yaoqing Yang, Shiwei Liu
2025	—	`conf`	LKA: Large Kernel Adapter for Enhanced Medical Image Classification. MICCAI (6) Ziquan Zhu, Si-Yuan Lu, Tianjin Huang, Lu Liu, Zhe Liu
2025	J	`jnl`	LOST: Low-rank and Sparse Pre-training for Large Language Models. CoRR Jiaxi Li, Lu Yin, Li Shen, Jinjin Xu, Liwu Xu, Tianjin Huang, Wenwu Wang, Shiwei Liu, Xilu Wang
2025	J	`jnl`	POT: Inducing Overthinking in LLMs via Black-Box Iterative Optimization. CoRR Xinyu Li, Tianjin Huang, Ronghui Mu, Xiaowei Huang, Gaojie Jin
2025	J	`jnl`	Principal Eigenvalue Regularization for Improved Worst-Class Certified Robustness of Smoothed Classifiers. CoRR Gaojie Jin, Tianjin Huang, Ronghui Mu, Xiaowei Huang
2025	J	`jnl`	Pushing the Limits of Sparsity: A Bag of Tricks for Extreme Pruning. Trans. Mach. Learn. Res. Andy Li, Aiden Durrant, Milan Markovic, Tianjin Huang, Souvik Kundu, Tianlong Chen, Lu Yin, Georgios Leontidis
2025	J	`jnl`	REOBench: Benchmarking Robustness of Earth Observation Foundation Models. CoRR Xiang Li, Yong Tao, Siyuan Zhang, Siwei Liu, Zhitong Xiong, Chunbo Luo, Lu Liu, Mykola Pechenizkiy, Xiao Xiang Zhu, Tianjin Huang
2025	J	`jnl`	SARC: Sentiment-Augmented Deep Role Clustering for Fake News Detection. CoRR Jingqing Wang, Jiaxing Shang, Rong Xu, Fei Hao, Tianjin Huang, Geyong Min
2025	A*	`conf`	SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training. ICLR Tianjin Huang, Ziquan Zhu, Gaojie Jin, Lu Liu, Zhangyang Wang, Shiwei Liu
2025	J	`jnl`	SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training. CoRR Tianjin Huang, Ziquan Zhu, Gaojie Jin, Lu Liu, Zhangyang Wang, Shiwei Liu
2025	J	`jnl`	Stable-SPAM: How to Train in 4-Bit More Stably than 16-Bit Adam. CoRR Tianjin Huang, Haotian Hu, Zhenyu Zhang, Gaojie Jin, Xiang Li, Li Shen, Tianlong Chen, Lu Liu, Qingsong Wen, Zhangyang Wang, Shiwei Liu
2025	J	`jnl`	The Compositional Architecture of Regret in Large Language Models. CoRR Xiangxiang Cui, Shu Yang, Tianjin Huang, Wanyu Lin, Lijie Hu, Di Wang
2025	J	`jnl`	Traffic congestion predictor: A spatiotemporal graph neural network with congestion-conditional adaptive mechanism and optimization algorithm. Expert Syst. Appl. Yutian Liu, Jian Gong, Tianjin Huang, Jinde Cao
2025	A*	`conf`	Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective. AAAI Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen
2024	J	`jnl`	(PASS) Visual Prompt Locates Good Structure Sparsity through a Recurrent HyperNetwork. CoRR Tianjin Huang, Meng Fang, Li Shen, Fan Liu, Yulong Pei, Mykola Pechenizkiy, Shiwei Liu, Tianlong Chen
2024	A	`conf`	Are Sparse Neural Networks Better Hard Sample Learners? BMVC Qiao Xiao, Boqian Wu, Lu Yin, Christopher Neil Gadzinski, Tianjin Huang, Mykola Pechenizkiy, Decebal Constantin Mocanu
2024	J	`jnl`	Are Sparse Neural Networks Better Hard Sample Learners? CoRR Qiao Xiao, Boqian Wu, Lu Yin, Christopher Neil Gadzinski, Tianjin Huang, Mykola Pechenizkiy, Decebal Constantin Mocanu
2024	J	`jnl`	Composable Interventions for Language Models. CoRR Arinbjörn Kolbeinsson, Kyle O'Brien, Tianjin Huang, Shanghua Gao, Shiwei Liu, Jonathan Richard Schwarz, Anurag Vaidya, Faisal Mahmood, Marinka Zitnik, Tianlong Chen, Thomas Hartvigsen
2024	J	`jnl`	RT-GCN: Gaussian-based spatiotemporal graph convolutional network for robust traffic prediction. Inf. Fusion Yutian Liu, Soora Rasouli, Melvin Wong, Tao Feng, Tianjin Huang
2023	A*	`conf`	Are Large Kernels Better Teachers than Transformers for ConvNets? ICML Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu
2023	J	`jnl`	Are Large Kernels Better Teachers than Transformers for ConvNets? CoRR Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu
2023	A*	`conf`	Dynamic Sparsity Is Channel-Level Sparsity Learner. NeurIPS Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu
2023	J	`jnl`	Dynamic Sparsity Is Channel-Level Sparsity Learner. CoRR Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu
2023	—	`conf`	Enhancing Adversarial Training via Reweighting Optimization Trajectory. ECML/PKDD (1) Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy
2023	J	`jnl`	Enhancing Adversarial Training via Reweighting Optimization Trajectory. CoRR Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy
2023	—	`conf`	Heterophily-Based Graph Neural Network for Imbalanced Classification. COMPLEX NETWORKS (1) Zirui Liang, Yuntao Li, Tianjin Huang, Akrati Saxena, Yulong Pei, Mykola Pechenizkiy
2023	J	`jnl`	Heterophily-Based Graph Neural Network for Imbalanced Classification. CoRR Zirui Liang, Yuntao Li, Tianjin Huang, Akrati Saxena, Yulong Pei, Mykola Pechenizkiy
2023	A*	`conf`	Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost. AAAI Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy
2023	A*	`conf`	Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! ICLR Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Kumar Jaiswal, Zhangyang Wang
2023	J	`jnl`	Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! CoRR Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Jaiswal, Zhangyang Wang
2023	J	`jnl`	The Counterattack of CNNs in Self-Supervised Learning: Larger Kernel Size might be All You Need. CoRR Tianjin Huang, Tianlong Chen, Zhangyang Wang, Shiwei Liu
2023	J	`jnl`	Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective. CoRR Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen
2022	J	`jnl`	Direction-aggregated Attack for Transferable Adversarial Examples. ACM J. Emerg. Technol. Comput. Syst. Tianjin Huang, Vlado Menkovski, Yulong Pei, Yuhao Wang, Mykola Pechenizkiy
2022	—	`conf`	Hop-Count Based Self-supervised Anomaly Detection on Attributed Networks. ECML/PKDD (1) Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
2022	J	`jnl`	Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost. CoRR Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy
2022	J	`jnl`	ResGCN: attention-based deep residual modeling for anomaly detection on attributed networks. Mach. Learn. Yulong Pei, Tianjin Huang, Werner van Ipenburg, Mykola Pechenizkiy
2022	J	`jnl`	Superposing Many Tickets into One: A Performance Booster for Sparse Neural Network Training. CoRR Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy, Decebal Constantin Mocanu, Shiwei Liu
2022	A	`conf`	Superposing many tickets into one: A performance booster for sparse neural network training. UAI Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy
2022	—	`conf`	You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. LoG Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu
2022	J	`jnl`	You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. CoRR Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu
2021	J	`jnl`	Calibrated Adversarial Training. CoRR Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
2021	J	`jnl`	Direction-Aggregated Attack for Transferable Adversarial Examples. CoRR Tianjin Huang, Vlado Menkovski, Yulong Pei, Yuhao Wang, Mykola Pechenizkiy
2021	J	`jnl`	Hop-Count Based Self-Supervised Anomaly Detection on Attributed Networks. CoRR Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
2021	—	`conf`	On Generalization of Graph Autoencoders with Adversarial Training. ECML/PKDD (2) Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
2021	J	`jnl`	On Generalization of Graph Autoencoders with Adversarial Training. CoRR Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
2021	B	`conf`	ResGCN: Attention-based Deep Residual Modeling for Anomaly Detection on Attributed Networks. DSAA Yulong Pei, Tianjin Huang, Werner van Ipenburg, Mykola Pechenizkiy
2021	C	`conf`	calibrated adversarial training. ACML Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
2020	J	`jnl`	Bridging the Performance Gap between FGSM and PGD Adversarial Training. CoRR Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
2020	J	`jnl`	ResGCN: Attention-based Deep Residual Modeling for Anomaly Detection on Attributed Networks. CoRR Yulong Pei, Tianjin Huang, Werner van Ipenburg, Mykola Pechenizkiy
2017	J	`jnl`	A New Method to Estimate Changes in Glacier Surface Elevation Based on Polynomial Fitting of Sparse ICESat - GLAS Footprints. Sensors Tianjin Huang, Li Jia, Massimo Menenti, Jing Lu, Jie Zhou, Guangcheng Hu
2016	C	`conf`	An improved method of using icesat altimetry data to extract Tibetan Plateau glacier thickness change rate. IGARSS Tianjin Huang, Li Jia, Jing Lu, Jie Zhou