Published in NeurIPS, 2023
Recommended citation: Fang, S., Yu, X., Li, S., Wang, Z., Kirby R., & Zhe, S. Streaming Factor Trajectory Learning for Temporal Tensor Decomposition. Advances in Neural Information Processing Systems (NeurIPS 2023) http://yuxwind.github.io/files/2023_neurips
Published in CPAIOR, 2023
Recommended citation: Cai J., Nguyen K., Shrestha N., Good A., Tu R., Yu X., & Serra T. Getting away with more network pruning: From sparsity to geometry and linear regions. International Confer- ence on Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR 2023) http://yuxwind.github.io/files/2023_cpaior.pdf
Published in NeurIPS, 2022
Recommended citation: Li, S.*, Phillips, J.*, Yu, X., Kirby, R., & Zhe, S. Batch Multi-Fidelity Active Learning with Budget Constraints. Advances in Neural Information Processing Systems (NeurIPS 2022). http://yuxwind.github.io/files/2022_neurips_active.pdf
Published in NeurIPS, 2022
Recommended citation: Good A.*, Lin J.*, Yu X.*, Sieg H., Ferguson M., Zhe S., Wieczore J., & Serra T. Recall Ditortion in Neural Network Pruning and the Undecayed Pruning Algorithm. Advances in Neural Information Processing Systems (NeurIPS 2022) http://yuxwind.github.io/files/2022_neurips.pdf
Published in ICML, 2022
Recommended citation: Yu X.*, Serra T.*, Ramalingam S., Zhe S. The Combinatorial Brain Surgeon: Pruning Weights That Cancel One Another in Neural Networks. In International Conference on Machine Learning (ICML 2022). http://yuxwind.github.io/files/2022_icml.pdf
Published in 3DV, 2021
Recommended citation: Yu X., & Baar J, Chen S. Joint 3D Human Shape Recovery and Pose Estimation from A Single Image with Bilayer-Graph. in International Conference on 3D Vision (3DV 2021) http://yuxwind.github.io/files/2021_3dv.pdf
Published in NeurIPS, 2021
Recommended citation: Serra, T., Yu, X., Kumar, A. and Ramalingam, S., 2021. Scaling Up Exact Neural Network Compression by ReLU Stability. arXiv preprint arXiv:2102.07804. (NeurIPS 2021) http://yuxwind.github.io/files/pruning-nips2021.pdf
Published in ACCV, 2020
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Ranade, S.*, ,Yu, X.*, Kakkar, S., Miraldo, P. and Ramalingam, S., 2020. Mapping of Sparse 3D Data using Alternating Projection. In Proceedings of the Asian Conference on Computer Vision.(ACCV 2020 Oral) http://yuxwind.github.io/files/3D-accv.pdf
Published in IROS, 2018
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Yu, X., Chaturvedi, S., Feng, C., Taguchi, Y., Lee, T.Y., Fernandes, C. and Ramalingam, S., 2018, October. Vlase: Vehicle localization by aggregating semantic edges. In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 3196-3203). IEEE. (IROS 2018) http://academicpages.github.io/files/paper3.pdf
Published in CVPR, 2018
We hypothesize that it is easier to optimize the residual mapping than to optimize the original, unreferenced mapping.
Recommended citation: Yu, X., Yu, Z. and Ramalingam, S., 2018. Learning strict identity mappings in deep residual networks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (pp. 4432-4440) (CVPR 2018) http://yuxwind.github.io/files/pruning-cvpr2018.pdf
Published in SIG-KDD, 2017
This paper is about number 1. The number 2 is left for future work.
Recommended citation: Paul, D., Li, F., Teja, M.K., Yu, X. and Frost, R., 2017, August. " Compass: Spatio temporal sentiment analysis of US election what twitter says!." In Proceedings of the 23rd ACM SIGKDD international conference on knowledge discovery and data mining (pp. 1585-1594). (KDD 2017) http://yuxwind.github.io/files/compass-kdd.pdf