| Tensor vs. matrix methods: Robust tensor decomposition under block sparse perturbations A Anandkumar, P Jain, Y Shi, UN Niranjan Artificial Intelligence and Statistics, 268-276, 2016 | 88 | 2016 |
| Tensor contractions with extended BLAS kernels on CPU and GPU Y Shi, UN Niranjan, A Anandkumar, C Cecka 2016 IEEE 23rd International Conference on High Performance Computing (HiPC …, 2016 | 73 | 2016 |
| Question type guided attention in visual question answering Y Shi, T Furlanello, S Zha, A Anandkumar Proceedings of the European Conference on Computer Vision (ECCV), 151-166, 2018 | 48 | 2018 |
| Higher-order Count Sketch: Dimensionality Reduction That Retains Efficient Tensor Operations Y Shi, A Anandkumar Data Compression Conference (DCC) 2019 poster, 2019 | 11* | 2019 |
| Streaming robust PCA UN Niranjan, Y Shi 10th NeurIPS Workshop on Optimization for Machine Learning (NeurIPS 2017), 2016 | 5 | 2016 |
| Efficient tensor operations via compression and parallel computation Y Shi University of California, Irvine, 2019 | 4 | 2019 |
| Learning Similarity Preserving Binary Codes for Recommender Systems Y Shi, Y Chung arXiv preprint arXiv:2204.08569, 2022 | 1 | 2022 |
| Efficient Cross-Modal Retrieval via Deep Binary Hashing and Quantization Y Shi, Y Chung arXiv preprint arXiv:2202.10232, 2022 | 1 | 2022 |
| Compact Tensor Pooling for Visual Question Answering Y Shi, T Furlanello, A Anandkumar CVPR 2017 VQA workshop, 2017 | 1 | 2017 |
| REDUCING SAMPLE SELECTION BIAS IN A MACHINE LEARNING-BASED RECOMMENDER SYSTEM Y Shi, Y Chung US Patent App. 17/554,640, 2023 | | 2023 |
| Reducing sample selection bias in a machine learning-based recommender system Y Shi, G Liang, Y Chung US Patent App. 17/589,802, 2023 | | 2023 |
| Reducing sample selection bias in a machine learning-based recommender system Y Shi, Y Chung US Patent App. 17/588,099, 2023 | | 2023 |
| Reducing sample selection bias in a machine learning-based recommender system Y Shi, G Liang, Y Chung US Patent App. 17/713,855, 2023 | | 2023 |
| Meta-Shop: Improving Item Advertisement For Small Businesses Y Shi, G Liang, Y Chung arXiv preprint arXiv:2212.01414, 2022 | | 2022 |
| Efficient Cross-Modal Retrieval via Deep Binary Hashing and Quantization Y Shi, C Young-joo BMVC, 2021 | | 2021 |
| Improving Cold-start Item Advertisement For Small Businesses Y Shi, Y Chung | | 2021 |
| Streaming Robust PCA Y Shi, UN Niranjan | | |
| Matrix vs Tensor Denoising Methods under Block Sparse Perturbations A Anandkumar, P Jain, Y Shi, UN Niranjan | | |
