Si Si

According to our database1, Si Si authored at least 50 papers between 2009 and 2024.

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Bibliography

2024
Large Language Models are Interpretable Learners.
CoRR, 2024

Two-stage LLM Fine-tuning with Less Specialization and More Generalization.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Automatic Engineering of Long Prompts.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
Active contour model based on hybrid signed pressure force function.
IET Image Process., 2023

Automatic Engineering of Long Prompts.
CoRR, 2023

Scaling Up Dataset Distillation to ImageNet-1K with Constant Memory.
Proceedings of the International Conference on Machine Learning, 2023

Serving Graph Compression for Graph Neural Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Preserving In-Context Learning ability in Large Language Model Fine-tuning.
CoRR, 2022

DC-BENCH: Dataset Condensation Benchmark.
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.
NeuroImage, 2021

Learnable Fourier Features for Multi-dimensional Spatial Positional Encoding.
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.
NeuroImage, 2020

How much progress have we made in neural network training? A New Evaluation Protocol for Benchmarking Optimizers.
CoRR, 2020

Auto Completion of User Interface Layout Design Using Transformer-Based Tree Decoders.
CoRR, 2020

Multi-Stage Influence Function.
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.
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.
CoRR, 2019

Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise.
CoRR, 2019

A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning.
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.
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.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

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

Learning to Screen for Fast Softmax Inference on Large Vocabulary Neural Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

You Look Twice: GaterNet for Dynamic Filter Selection in CNNs.
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.
CoRR, 2018

Nonlinear Online Learning with Adaptive Nyström Approximation.
CoRR, 2018

GroupReduce: Block-Wise Low-Rank Approximation for Neural Language Model Shrinking.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
Memory Efficient Kernel Approximation.
J. Mach. Learn. Res., 2017

GPU-acceleration for Large-scale Tree Boosting.
CoRR, 2017

Communication-Efficient Distributed Block Minimization for Nonlinear Kernel Machines.
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.
Proceedings of the 34th International Conference on Machine Learning, 2017

2016
Kernel Ridge Regression via Partitioning.
CoRR, 2016

Communication-Efficient Parallel Block Minimization for Kernel Machines.
CoRR, 2016

Goal-Directed Inductive Matrix Completion.
Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Computationally Efficient Nyström Approximation using Fast Transforms.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2014
Parallel matrix factorization for recommender systems.
Knowl. Inf. Syst., 2014

Beyond modeling private actions: predicting social shares.
Proceedings of the 23rd International World Wide Web Conference, 2014

The "expression gap": do you like what you share?
Proceedings of the 23rd International World Wide Web Conference, 2014

Multi-Scale Spectral Decomposition of Massive Graphs.
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.
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.
Proceedings of the 31th International Conference on Machine Learning, 2014

2012
Social image annotation via cross-domain subspace learning.
Multim. Tools Appl., 2012

Scalable Coordinate Descent Approaches to Parallel Matrix Factorization for Recommender Systems.
Proceedings of the 12th IEEE International Conference on Data Mining, 2012

Multi-scale link prediction.
Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

2011
Distribution Calibration in Riemannian Symmetric Space.
IEEE Trans. Syst. Man Cybern. Part B, 2011

2010
Bregman Divergence-Based Regularization for Transfer Subspace Learning.
IEEE Trans. Knowl. Data Eng., 2010

Evolutionary Cross-Domain Discriminative Hessian Eigenmaps.
IEEE Trans. Image Process., 2010

Discriminative Hessian Eigenmaps for face recognition.
Proceedings of the IEEE International Conference on Acoustics, 2010

2009
Transfer Discriminative Logmaps.
Proceedings of the Advances in Multimedia Information Processing, 2009

Cross-Domain Web Image Annotation.
Proceedings of the ICDM Workshops 2009, 2009


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