Si Si

According to our database, Si Si authored at least 51 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization.

Jui-Nan Yen, Si Si, Zhao Meng, Felix X. Yu, Sai Surya Duvvuri, Inderjit S. Dhillon, Cho-Jui Hsieh, Sanjiv Kumar

CoRR, 2024

Large Language Models are Interpretable Learners.

Ruochen Wang, Si Si, Felix Yu, Dorothea Wiesmann, Cho-Jui Hsieh, Inderjit S. Dhillon

CoRR, 2024

Two-stage LLM Fine-tuning with Less Specialization and More Generalization.

Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix Yu, Cho-Jui Hsieh, Inderjit S. Dhillon, Sanjiv Kumar

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Automatic Engineering of Long Prompts.

Cho-Jui Hsieh, Si Si, Felix Yu, Inderjit S. Dhillon

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Active contour model based on hybrid signed pressure force function.

XinChao Meng, Si Si

IET Image Process., 2023

Automatic Engineering of Long Prompts.

Cho-Jui Hsieh, Si Si, Felix X. Yu, Inderjit S. Dhillon

CoRR, 2023

Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory.

Justin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh

Proceedings of the International Conference on Machine Learning, 2023

Serving Graph Compression for Graph Neural Networks.

Si Si, Felix X. Yu, Ankit Singh Rawat, Cho-Jui Hsieh, Sanjiv Kumar

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Preserving In-Context Learning ability in Large Language Model Fine-tuning.

Yihan Wang, Si Si, Daliang Li, Michal Lukasik, Felix X. Yu, Cho-Jui Hsieh, Inderjit S. Dhillon, Sanjiv Kumar

CoRR, 2022

DC-BENCH: Dataset Condensation Benchmark.

Justin Cui, Ruochen Wang, Si Si, Cho-Jui Hsieh

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

The neurobiological basis of divergent thinking: Insight from gene co-expression network-based analysis.

Shun Zhang, Xiaolei Yang, Si Si, Jinghuan Zhang

NeuroImage, 2021

Learnable Fourier Features for Multi-dimensional Spatial Positional Encoding.

Yang Li, Si Si, Gang Li, Cho-Jui Hsieh, Samy Bengio

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Genetic susceptibility to parenting style: <i>DRD2</i> and <i>COMT</i> influence creativity.

Si Si, Yukang Su, Shun Zhang, Jinghuan Zhang

NeuroImage, 2020

How much progress have we made in neural network training? A New Evaluation Protocol for Benchmarking Optimizers.

Yuanhao Xiong, Xuanqing Liu, Li-Cheng Lan, Yang You, Si Si, Cho-Jui Hsieh

CoRR, 2020

Auto Completion of User Interface Layout Design Using Transformer-Based Tree Decoders.

Yang Li, Julien Amelot, Xin Zhou, Samy Bengio, Si Si

CoRR, 2020

Multi-Stage Influence Function.

Hongge Chen, Si Si, Yang Li, Ciprian Chelba, Sanjiv Kumar, Duane S. Boning, Cho-Jui Hsieh

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

How Does Noise Help Robustness? Explanation and Exploration under the Neural SDE Framework.

Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning.

Xuanqing Liu, Si Si, Xiaojin Zhu, Yang Li, Cho-Jui Hsieh

CoRR, 2019

Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise.

Xuanqing Liu, Tesi Xiao, Si Si, Qin Cao, Sanjiv Kumar, Cho-Jui Hsieh

CoRR, 2019

A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning.

Xuanqing Liu, Si Si, Jerry Zhu, Yang Li, Cho-Jui Hsieh

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Robustness Verification of Tree-based Models.

Hongge Chen, Huan Zhang, Si Si, Yang Li, Duane S. Boning, Cho-Jui Hsieh

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks.

Wei-Lin Chiang, Xuanqing Liu, Si Si, Yang Li, Samy Bengio, Cho-Jui Hsieh

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Area Attention.

Yang Li, Lukasz Kaiser, Samy Bengio, Si Si

Proceedings of the 36th International Conference on Machine Learning, 2019

Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Networks.

Patrick H. Chen, Si Si, Sanjiv Kumar, Yang Li, Cho-Jui Hsieh

Proceedings of the 7th International Conference on Learning Representations, 2019

You Look Twice: GaterNet for Dynamic Filter Selection in CNNs.

Zhourong Chen, Yang Li, Samy Bengio, Si Si

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

GaterNet: Dynamic Filter Selection in Convolutional Neural Network via a Dedicated Global Gating Network.

Zhourong Chen, Yang Li, Samy Bengio, Si Si

CoRR, 2018

Nonlinear Online Learning with Adaptive Nyström Approximation.

Si Si, Sanjiv Kumar, Yang Li

CoRR, 2018

GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking.

Patrick H. Chen, Si Si, Yang Li, Ciprian Chelba, Cho-Jui Hsieh

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Memory Efficient Kernel Approximation.

Si Si, Cho-Jui Hsieh, Inderjit S. Dhillon

J. Mach. Learn. Res., 2017

GPU-acceleration for Large-scale Tree Boosting.

Huan Zhang, Si Si, Cho-Jui Hsieh

CoRR, 2017

Communication-Efficient Distributed Block Minimization for Nonlinear Kernel Machines.

Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon

Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Halifax, NS, Canada, August 13, 2017

Gradient Boosted Decision Trees for High Dimensional Sparse Output.

Si Si, Huan Zhang, S. Sathiya Keerthi, Dhruv Mahajan, Inderjit S. Dhillon, Cho-Jui Hsieh

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

Kernel Ridge Regression via Partitioning.

Rashish Tandon, Si Si, Pradeep Ravikumar, Inderjit S. Dhillon

CoRR, 2016

Communication-Efficient Parallel Block Minimization for Kernel Machines.

Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon

CoRR, 2016

Goal-Directed Inductive Matrix Completion.

Si Si, Kai-Yang Chiang, Cho-Jui Hsieh, Nikhil Rao, Inderjit S. Dhillon

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Computationally Efficient Nyström Approximation using Fast Transforms.

Si Si, Cho-Jui Hsieh, Inderjit S. Dhillon

Proceedings of the 33nd International Conference on Machine Learning, 2016

2014

Parallel matrix factorization for recommender systems.

Hsiang-Fu Yu, Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon

Knowl. Inf. Syst., 2014

Beyond modeling private actions: predicting social shares.

Si Si, Atish Das Sarma, Elizabeth F. Churchill, Neel Sundaresan

Proceedings of the 23rd International World Wide Web Conference, 2014

The "expression gap": do you like what you share?

Atish Das Sarma, Si Si, Elizabeth F. Churchill, Neel Sundaresan

Proceedings of the 23rd International World Wide Web Conference, 2014

Multi-Scale Spectral Decomposition of Massive Graphs.

Si Si, Donghyuk Shin, Inderjit S. Dhillon, Beresford N. Parlett

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Fast Prediction for Large-Scale Kernel Machines.

Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

A Divide-and-Conquer Solver for Kernel Support Vector Machines.

Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon

Proceedings of the 31th International Conference on Machine Learning, 2014

2012

Social image annotation via cross-domain subspace learning.

Si Si, Dacheng Tao, Meng Wang, Kwok-Ping Chan

Multim. Tools Appl., 2012

Scalable Coordinate Descent Approaches to Parallel Matrix Factorization for Recommender Systems.

Hsiang-Fu Yu, Cho-Jui Hsieh, Si Si, Inderjit S. Dhillon

Proceedings of the 12th IEEE International Conference on Data Mining, 2012

Multi-scale link prediction.

Donghyuk Shin, Si Si, Inderjit S. Dhillon

Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

2011

Distribution Calibration in Riemannian Symmetric Space.

Si Si, Wei Liu, Dacheng Tao, Kwok-Ping Chan

IEEE Trans. Syst. Man Cybern. Part B, 2011

2010

Bregman Divergence-Based Regularization for Transfer Subspace Learning.

Si Si, Dacheng Tao, Bo Geng

IEEE Trans. Knowl. Data Eng., 2010

Evolutionary Cross-Domain Discriminative Hessian Eigenmaps.

Si Si, Dacheng Tao, Kwok-Ping Chan

IEEE Trans. Image Process., 2010

Discriminative Hessian Eigenmaps for face recognition.

Si Si, Dacheng Tao, Kwok-Ping Chan

Proceedings of the IEEE International Conference on Acoustics, 2010

2009

Transfer Discriminative Logmaps.

Si Si, Dacheng Tao, Kwok-Ping Chan

Proceedings of the Advances in Multimedia Information Processing, 2009

Cross-Domain Web Image Annotation.

Si Si, Dacheng Tao, Kwok-Ping Chan

Proceedings of the ICDM Workshops 2009, 2009