| Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction E Chien, WC Chang, CJ Hsieh, HF Yu, J Zhang, O Milenkovic, IS Dhillon International Conference on Learning Representations (ICLR), 2022 | 140 | 2022 |
| Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization J Zhang, Q Lei, IS Dhillon International Conference on Machine Learning, 5806-5814, 2018 | 137 | 2018 |
| Fast multi-resolution transformer fine-tuning for extreme multi-label text classification J Zhang, WC Chang, HF Yu, I Dhillon Advances in Neural Information Processing Systems 34, 7267-7280, 2021 | 118 | 2021 |
| Pecos: Prediction for enormous and correlated output spaces HF Yu, K Zhong, J Zhang, WC Chang, IS Dhillon Journal of Machine Learning Research 23 (98), 1-32, 2020 | 88 | 2020 |
| Extreme multi-label learning for semantic matching in product search WC Chang, D Jiang, HF Yu, CH Teo, J Zhang, K Zhong, K Kolluri, Q Hu, ... Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 69 | 2021 |
| Learning Long Term Dependencies via Fourier Recurrent Units J Zhang, Y Lin, Z Song, IS Dhillon International Conference on Machine Learning, 5815-5823, 2018 | 49 | 2018 |
| Autoassist: A framework to accelerate training of deep neural networks J Zhang, HF Yu, IS Dhillon Advances in Neural Information Processing Systems 32, 5998--6008, 2019 | 37 | 2019 |
| A convex atomic-norm approach to multiple sequence alignment and motif discovery IEH Yen, X Lin, J Zhang, P Ravikumar, I Dhillon International Conference on Machine Learning, 2272-2280, 2016 | 14 | 2016 |
| PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation E Chien, J Zhang, CJ Hsieh, JY Jiang, WC Chang, O Milenkovic, HF Yu International Conference on Machine Learning, 5616-5630, 2023 | 11 | 2023 |
| Relevance under the Iceberg: Reasonable Prediction for Extreme Multi-label Classification JY Jiang, WC Chang, J Zhang, CJ Hsieh, HF Yu The 45th International ACM SIGIR Conference on Research and Development in …, 2022 | 5 | 2022 |
| Extreme stochastic variational inference: Distributed inference for large scale mixture models J Zhang, P Raman, S Ji, HF Yu, SVN Vishwanathan, I Dhillon The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 5 | 2019 |
| Uncertainty in Extreme Multi-label Classification JY Jiang, WC Chang, J Zhong, CJ Hsieh, HF Yu SIGIR, 2023 | 4 | 2023 |
| Representer Point Selection for Explaining Regularized High-dimensional Models CP Tsai, J Zhang, HF Yu, E Chien, CJ Hsieh, PK Ravikumar International Conference on Machine Learning, 34469-34490, 2023 | 3 | 2023 |
| Build Faster with Less: A Journey to Accelerate Sparse Model Building for Semantic Matching in Product Search J Zhang, YS Wang, WC Chang, W Li, JY Jiang, CJ Hsieh, HF Yu Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 1 | 2023 |
| Scalable Convex Multiple Sequence Alignment via Entropy-Regularized Dual Decomposition J Zhang, IEH Yen, P Ravikumar, IS Dhillon Artificial Intelligence and Statistics., 1514-1522, 2017 | 1 | 2017 |
| PEFA: ParamEter-Free Adapters for large-scale embedding-based retrieval models WC Chang, JY Jiang, J Zhang, M Al-Darabsah, CH Teo, CJ Hsieh, HF Yu, ... Proceedings of the 17th ACM International Conference on Web Search and Data …, 2024 | | 2024 |
Hsiang-Fu YuPrincipal Applied Scientist at AmazonVerified email at cs.utexas.edu
