Tianjin Huang

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 35

Top Topics

Sparse Approximation

Linearly Combined

Supervised Learning

Top Venues

Publications

Arinbjorn Kolbeinsson, Kyle O'Brien, Tianjin Huang, Shanghua Gao, Shiwei Liu, Jonathan Richard Schwarz, Anurag Vaidya, Faisal Mahmood, Marinka Zitnik, Tianlong Chen, Thomas Hartvigsen
Composable Interventions for Language Models. CoRR (2024)
Tianjin Huang, Meng Fang, Li Shen, Fan Liu, Yulong Pei, Mykola Pechenizkiy, Shiwei Liu, Tianlong Chen
(PASS) Visual Prompt Locates Good Structure Sparsity through a Recurrent HyperNetwork. CoRR (2024)
Yutian Liu, Soora Rasouli, Melvin Wong, Tao Feng, Tianjin Huang
RT-GCN: Gaussian-based spatiotemporal graph convolutional network for robust traffic prediction. Inf. Fusion 102 (2024)
Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu
Dynamic Sparsity Is Channel-Level Sparsity Learner. NeurIPS (2023)
Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy
Enhancing Adversarial Training via Reweighting Optimization Trajectory. ECML/PKDD (1) (2023)
Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Kumar Jaiswal, Zhangyang Wang
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! ICLR (2023)
Tianjin Huang, Tianlong Chen, Zhangyang Wang, Shiwei Liu
The Counterattack of CNNs in Self-Supervised Learning: Larger Kernel Size might be All You Need. CoRR (2023)
Lu Yin, Gen Li, Meng Fang, Li Shen, Tianjin Huang, Zhangyang Wang, Vlado Menkovski, Xiaolong Ma, Mykola Pechenizkiy, Shiwei Liu
Dynamic Sparsity Is Channel-Level Sparsity Learner. CoRR (2023)
Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy
Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost. AAAI (2023)
Tianjin Huang, Shiwei Liu, Tianlong Chen, Meng Fang, Li Shen, Vlado Menkovski, Lu Yin, Yulong Pei, Mykola Pechenizkiy
Enhancing Adversarial Training via Reweighting Optimization Trajectory. CoRR (2023)
Shiwei Liu, Tianlong Chen, Zhenyu Zhang, Xuxi Chen, Tianjin Huang, Ajay Jaiswal, Zhangyang Wang
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! CoRR (2023)
Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu
Are Large Kernels Better Teachers than Transformers for ConvNets? ICML (2023)
Zirui Liang, Yuntao Li, Tianjin Huang, Akrati Saxena, Yulong Pei, Mykola Pechenizkiy
Heterophily-Based Graph Neural Network for Imbalanced Classification. CoRR (2023)
Zirui Liang, Yuntao Li, Tianjin Huang, Akrati Saxena, Yulong Pei, Mykola Pechenizkiy
Heterophily-Based Graph Neural Network for Imbalanced Classification. COMPLEX NETWORKS (1) (2023)
Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang Wang, Shiwei Liu
Are Large Kernels Better Teachers than Transformers for ConvNets? CoRR (2023)
Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen
Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective. CoRR (2023)
Lu Yin, Shiwei Liu, Meng Fang, Tianjin Huang, Vlado Menkovski, Mykola Pechenizkiy
Lottery Pools: Winning More by Interpolating Tickets without Increasing Training or Inference Cost. CoRR (2022)
Yulong Pei, Tianjin Huang, Werner van Ipenburg, Mykola Pechenizkiy
ResGCN: attention-based deep residual modeling for anomaly detection on attributed networks. Mach. Learn. 111 (2) (2022)
Tianjin Huang, Vlado Menkovski, Yulong Pei, Yuhao Wang, Mykola Pechenizkiy
Direction-aggregated Attack for Transferable Adversarial Examples. ACM J. Emerg. Technol. Comput. Syst. 18 (3) (2022)
Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
Hop-Count Based Self-supervised Anomaly Detection on Attributed Networks. ECML/PKDD (1) (2022)
Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy
Superposing many tickets into one: A performance booster for sparse neural network training. UAI (2022)
Lu Yin, Vlado Menkovski, Meng Fang, Tianjin Huang, Yulong Pei, Mykola Pechenizkiy, Decebal Constantin Mocanu, Shiwei Liu
Superposing Many Tickets into One: A Performance Booster for Sparse Neural Network Training. CoRR (2022)
Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. LoG (2022)
Tianjin Huang, Tianlong Chen, Meng Fang, Vlado Menkovski, Jiaxu Zhao, Lu Yin, Yulong Pei, Decebal Constantin Mocanu, Zhangyang Wang, Mykola Pechenizkiy, Shiwei Liu
You Can Have Better Graph Neural Networks by Not Training Weights at All: Finding Untrained GNNs Tickets. CoRR (2022)
Tianjin Huang, Vlado Menkovski, Yulong Pei, Yuhao Wang, Mykola Pechenizkiy
Direction-Aggregated Attack for Transferable Adversarial Examples. CoRR (2021)
Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
On Generalization of Graph Autoencoders with Adversarial Training. CoRR (2021)
Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
Hop-Count Based Self-Supervised Anomaly Detection on Attributed Networks. CoRR (2021)
Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
Calibrated Adversarial Training. CoRR (2021)
Yulong Pei, Tianjin Huang, Werner van Ipenburg, Mykola Pechenizkiy
ResGCN: Attention-based Deep Residual Modeling for Anomaly Detection on Attributed Networks. DSAA (2021)
Tianjin Huang, Yulong Pei, Vlado Menkovski, Mykola Pechenizkiy
On Generalization of Graph Autoencoders with Adversarial Training. ECML/PKDD (2) (2021)
Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
calibrated adversarial training. ACML (2021)
Yulong Pei, Tianjin Huang, Werner van Ipenburg, Mykola Pechenizkiy
ResGCN: Attention-based Deep Residual Modeling for Anomaly Detection on Attributed Networks. CoRR (2020)
Tianjin Huang, Vlado Menkovski, Yulong Pei, Mykola Pechenizkiy
Bridging the Performance Gap between FGSM and PGD Adversarial Training. CoRR (2020)
Tianjin Huang, Li Jia, Massimo Menenti, Jing Lu, Jie Zhou, Guangcheng Hu
A New Method to Estimate Changes in Glacier Surface Elevation Based on Polynomial Fitting of Sparse ICESat - GLAS Footprints. Sensors 17 (8) (2017)
Tianjin Huang, Li Jia, Jing Lu, Jie Zhou
An improved method of using icesat altimetry data to extract Tibetan Plateau glacier thickness change rate. IGARSS (2016)