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2020 – today
- 2024
[c30]Cho-Jui Hsieh, Si Si, Felix Yu, Inderjit S. Dhillon:
Automatic Engineering of Long Prompts. ACL (Findings) 2024: 10672-10685- [c29]Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix Yu, Cho-Jui Hsieh, Inderjit S. Dhillon, Sanjiv Kumar:
Two-stage LLM Fine-tuning with Less Specialization and More Generalization. ICLR 2024 - [i24]Ruochen Wang, Si Si, Felix Yu, Dorothea Wiesmann, Cho-Jui Hsieh, Inderjit S. Dhillon:
Large Language Models are Interpretable Learners. CoRR abs/2406.17224 (2024) - [i23]Jui-Nan Yen, Si Si, Zhao Meng, Felix X. Yu, Sai Surya Duvvuri, Inderjit S. Dhillon, Cho-Jui Hsieh, Sanjiv Kumar:
LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization. CoRR abs/2410.20625 (2024) - 2023
- [j9]XinChao Meng
, Si Si:
Active contour model based on hybrid signed pressure force function. IET Image Process. 17(13): 3702-3712 (2023) - [c28]Si Si, Felix X. Yu, Ankit Singh Rawat, Cho-Jui Hsieh, Sanjiv Kumar:
Serving Graph Compression for Graph Neural Networks. ICLR 2023 - [c27]Justin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh:
Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory. ICML 2023: 6565-6590 - [i22]Cho-Jui Hsieh, Si Si, Felix X. Yu, Inderjit S. Dhillon:
Automatic Engineering of Long Prompts. CoRR abs/2311.10117 (2023) - 2022
- [c26]Justin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh:
DC-BENCH: Dataset Condensation Benchmark. NeurIPS 2022 - [i21]Justin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh:
DC-BENCH: Dataset Condensation Benchmark. CoRR abs/2207.09639 (2022) - [i20]Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix X. Yu, Cho-Jui Hsieh, Inderjit S. Dhillon, Sanjiv Kumar:
Preserving In-Context Learning ability in Large Language Model Fine-tuning. CoRR abs/2211.00635 (2022) - [i19]Justin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh:
Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory. CoRR abs/2211.10586 (2022) - 2021
- [j8]Shun Zhang, Xiaolei Yang, Si Si, Jinghuan Zhang:
The neurobiological basis of divergent thinking: Insight from gene co-expression network-based analysis. NeuroImage 245: 118762 (2021) - [c25]Yang Li, Si Si, Gang Li, Cho-Jui Hsieh, Samy Bengio:
Learnable Fourier Features for Multi-dimensional Spatial Positional Encoding. NeurIPS 2021: 15816-15829 - [i18]Yang Li, Si Si, Gang Li, Cho-Jui Hsieh, Samy Bengio:
Learnable Fourier Features for Multi-Dimensional Spatial Positional Encoding. CoRR abs/2106.02795 (2021) - 2020
- [j7]Si Si, Yukang Su, Shun Zhang, Jinghuan Zhang:
Genetic susceptibility to parenting style: DRD2 and COMT influence creativity. NeuroImage 213: 116681 (2020) - [c24]Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh:
How Does Noise Help Robustness? Explanation and Exploration under the Neural SDE Framework. CVPR 2020: 279-287 - [c23]Hongge Chen, Si Si, Yang Li, Ciprian Chelba, Sanjiv Kumar, Duane S. Boning, Cho-Jui Hsieh:
Multi-Stage Influence Function. NeurIPS 2020 - [i17]Yang Li, Julien Amelot, Xin Zhou, Samy Bengio, Si Si:
Auto Completion of User Interface Layout Design Using Transformer-Based Tree Decoders. CoRR abs/2001.05308 (2020) - [i16]Hongge Chen, Si Si, Yang Li, Ciprian Chelba, Sanjiv Kumar, Duane S. Boning, Cho-Jui Hsieh:
Multi-Stage Influence Function. CoRR abs/2007.09081 (2020) - [i15]Yuanhao Xiong, Xuanqing Liu, Li-Cheng Lan, Yang You, Si Si, Cho-Jui Hsieh:
How much progress have we made in neural network training? A New Evaluation Protocol for Benchmarking Optimizers. CoRR abs/2010.09889 (2020)
2010 – 2019
- 2019
- [c22]Zhourong Chen, Yang Li, Samy Bengio, Si Si:
You Look Twice: GaterNet for Dynamic Filter Selection in CNNs. CVPR 2019: 9172-9180 - [c21]Patrick H. Chen, Si Si, Sanjiv Kumar, Yang Li, Cho-Jui Hsieh:
Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Networks. ICLR (Poster) 2019 - [c20]Yang Li, Lukasz Kaiser, Samy Bengio, Si Si:
Area Attention. ICML 2019: 3846-3855 - [c19]Wei-Lin Chiang, Xuanqing Liu, Si Si, Yang Li, Samy Bengio, Cho-Jui Hsieh:
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks. KDD 2019: 257-266 - [c18]Xuanqing Liu, Si Si, Jerry Zhu, Yang Li, Cho-Jui Hsieh:
A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning. NeurIPS 2019: 9777-9787 - [c17]Hongge Chen, Huan Zhang, Si Si, Yang Li, Duane S. Boning, Cho-Jui Hsieh:
Robustness Verification of Tree-based Models. NeurIPS 2019: 12317-12328 - [i14]Wei-Lin Chiang, Xuanqing Liu, Si Si, Yang Li, Samy Bengio, Cho-Jui Hsieh:
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks. CoRR abs/1905.07953 (2019) - [i13]Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh:
Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise. CoRR abs/1906.02355 (2019) - [i12]Hongge Chen, Huan Zhang, Si Si, Yang Li, Duane S. Boning, Cho-Jui Hsieh:
Robustness Verification of Tree-based Models. CoRR abs/1906.03849 (2019) - [i11]Xuanqing Liu, Si Si, Xiaojin Zhu, Yang Li, Cho-Jui Hsieh:
A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning. CoRR abs/1910.14147 (2019) - 2018
- [c16]Patrick H. Chen, Si Si, Yang Li, Ciprian Chelba, Cho-Jui Hsieh:
GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking. NeurIPS 2018: 11011-11021 - [i10]Si Si, Sanjiv Kumar, Yang Li:
Nonlinear Online Learning with Adaptive Nyström Approximation. CoRR abs/1802.07887 (2018) - [i9]Patrick H. Chen, Si Si, Yang Li, Ciprian Chelba, Cho-Jui Hsieh:
GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking. CoRR abs/1806.06950 (2018) - [i8]Yang Li, Lukasz Kaiser, Samy Bengio, Si Si:
Area Attention. CoRR abs/1810.10126 (2018) - [i7]Patrick H. Chen, Si Si, Sanjiv Kumar, Yang Li, Cho-Jui Hsieh:
Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Networks. CoRR abs/1810.12406 (2018) - [i6]Zhourong Chen, Yang Li, Samy Bengio, Si Si:
GaterNet: Dynamic Filter Selection in Convolutional Neural Network via a Dedicated Global Gating Network. CoRR abs/1811.11205 (2018) - 2017
- [j6]Si Si, Cho-Jui Hsieh, Inderjit S. Dhillon:
Memory Efficient Kernel Approximation. J. Mach. Learn. Res. 18: 20:1-20:32 (2017) - [c15]Si Si, Huan Zhang, S. Sathiya Keerthi, Dhruv Mahajan, Inderjit S. Dhillon, Cho-Jui Hsieh:
Gradient Boosted Decision Trees for High Dimensional Sparse Output. ICML 2017: 3182-3190 - [c14]Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon:
Communication-Efficient Distributed Block Minimization for Nonlinear Kernel Machines. KDD 2017: 245-254 - [i5]Huan Zhang, Si Si, Cho-Jui Hsieh:
GPU-acceleration for Large-scale Tree Boosting. CoRR abs/1706.08359 (2017) - 2016
- [c13]Si Si, Cho-Jui Hsieh, Inderjit S. Dhillon:
Computationally Efficient Nyström Approximation using Fast Transforms. ICML 2016: 2655-2663 - [c12]Si Si, Kai-Yang Chiang, Cho-Jui Hsieh, Nikhil Rao, Inderjit S. Dhillon:
Goal-Directed Inductive Matrix Completion. KDD 2016: 1165-1174 - [i4]Rashish Tandon, Si Si, Pradeep Ravikumar, Inderjit S. Dhillon:
Kernel Ridge Regression via Partitioning. CoRR abs/1608.01976 (2016) - [i3]Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon:
Communication-Efficient Parallel Block Minimization for Kernel Machines. CoRR abs/1608.02010 (2016) - 2014
- [j5]Hsiang-Fu Yu, Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon:
Parallel matrix factorization for recommender systems. Knowl. Inf. Syst. 41(3): 793-819 (2014) - [c11]Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon:
A Divide-and-Conquer Solver for Kernel Support Vector Machines. ICML 2014: 566-574 - [c10]Si Si, Cho-Jui Hsieh, Inderjit S. Dhillon:
Memory Efficient Kernel Approximation. ICML 2014: 701-709 - [c9]Si Si, Donghyuk Shin, Inderjit S. Dhillon, Beresford N. Parlett:
Multi-Scale Spectral Decomposition of Massive Graphs. NIPS 2014: 2798-2806 - [c8]Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon:
Fast Prediction for Large-Scale Kernel Machines. NIPS 2014: 3689-3697 - [c7]Atish Das Sarma, Si Si, Elizabeth F. Churchill, Neel Sundaresan:
The "expression gap": do you like what you share? WWW (Companion Volume) 2014: 247-248 - [c6]Si Si, Atish Das Sarma, Elizabeth F. Churchill, Neel Sundaresan:
Beyond modeling private actions: predicting social shares. WWW (Companion Volume) 2014: 377-378 - 2013
- [i2]Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon:
A Divide-and-Conquer Solver for Kernel Support Vector Machines. CoRR abs/1311.0914 (2013) - 2012
- [j4]Si Si, Dacheng Tao, Meng Wang, Kwok-Ping Chan:
Social image annotation via cross-domain subspace learning. Multim. Tools Appl. 56(1): 91-108 (2012) - [c5]Donghyuk Shin, Si Si, Inderjit S. Dhillon:
Multi-scale link prediction. CIKM 2012: 215-224 - [c4]Hsiang-Fu Yu, Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon:
Scalable Coordinate Descent Approaches to Parallel Matrix Factorization for Recommender Systems. ICDM 2012: 765-774 - [i1]Donghyuk Shin, Si Si, Inderjit S. Dhillon:
Multi-Scale Link Prediction. CoRR abs/1206.1891 (2012) - 2011
- [j3]Si Si, Wei Liu, Dacheng Tao, Kwok-Ping Chan:
Distribution Calibration in Riemannian Symmetric Space. IEEE Trans. Syst. Man Cybern. Part B 41(4): 921-930 (2011) - 2010
- [j2]Si Si, Dacheng Tao, Kwok-Ping Chan:
Evolutionary Cross-Domain Discriminative Hessian Eigenmaps. IEEE Trans. Image Process. 19(4): 1075-1086 (2010) - [j1]Si Si, Dacheng Tao, Bo Geng:
Bregman Divergence-Based Regularization for Transfer Subspace Learning. IEEE Trans. Knowl. Data Eng. 22(7): 929-942 (2010) - [c3]Si Si, Dacheng Tao, Kwok-Ping Chan:
Discriminative Hessian Eigenmaps for face recognition. ICASSP 2010: 5586-5589
2000 – 2009
- 2009
- [c2]Si Si, Dacheng Tao, Kwok-Ping Chan:
Cross-Domain Web Image Annotation. ICDM Workshops 2009: 184-189 - [c1]Si Si, Dacheng Tao, Kwok-Ping Chan:
Transfer Discriminative Logmaps. PCM 2009: 131-143
Coauthor Index
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