Andi Han

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All published works
Action Title Year Authors
+ PDF Chat On the Comparison between Multi-modal and Single-modal Contrastive Learning 2024 Wei Huang
Andi Han
Yongqiang Chen
Yuan Cao
Zhiqiang Xu
Taiji Suzuki
+ PDF Chat Provably Transformers Harness Multi-Concept Word Semantics for Efficient In-Context Learning 2024 Dake Bu
Wei Huang
Andi Han
Atsushi Nitanda
Taiji Suzuki
Qingfu Zhang
Hau−San Wong
+ PDF Chat Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning 2024 Lequan Lin
Shi Dai
Andi Han
Zhiyong Wang
Junbin Gao
+ PDF Chat When Graph Neural Networks Meet Dynamic Mode Decomposition 2024 Dai Shi
Lequan Lin
Andi Han
Zhiyong Wang
Yi Guo
Junbin Gao
+ PDF Chat On the Optimization and Generalization of Two-layer Transformers with Sign Gradient Descent 2024 Bingrui Li
Wei Huang
Andi Han
Zhenjun Zhou
Taiji Suzuki
Jun Zhu
Chen Jian-fei
+ PDF Chat Secondary Structure-Guided Novel Protein Sequence Generation with Latent Graph Diffusion 2024 Yutong Hu
Yang Tan
Andi Han
Lirong Zheng
Liang Hong
Bingxin Zhou
+ PDF Chat SLTrain: a sparse plus low-rank approach for parameter and memory efficient pretraining 2024 Andi Han
Jiaxiang Li
Wei Huang
Mingyi Hong
Akiko Takeda
Pratik Jawanpuria
Bamdev Mishra
+ PDF Chat Riemannian coordinate descent algorithms on matrix manifolds 2024 Andi Han
Pratik Jawanpuria
Bamdev Mishra
+ PDF Chat Unleash Graph Neural Networks from Heavy Tuning 2024 Lequan Lin
Shi Dai
Andi Han
Zhiyong Wang
Junbin Gao
+ PDF Chat A Framework for Bilevel Optimization on Riemannian Manifolds 2024 Andi Han
Bamdev Mishra
Pratik Jawanpuria
Akiko Takeda
+ PDF Chat Design Your Own Universe: A Physics-Informed Agnostic Method for Enhancing Graph Neural Networks 2024 Shi Dai
Andi Han
Lequan Lin
Yi Guo
Zhiyong Wang
Junbin Gao
+ SpecSTG: A Fast Spectral Diffusion Framework for Probabilistic Spatio-Temporal Traffic Forecasting 2024 Lequan Lin
Dai Shi
Andi Han
Junbin Gao
+ Riemannian Optimization 2024 Andi Han
Pratik Jawanpuria
Bamdev Mishra
+ PDF Chat Riemannian Hamiltonian Methods for Min-Max Optimization on Manifolds 2023 Andi Han
Bamdev Mishra
Pratik Jawanpuria
Pawan Kumar
Junbin Gao
+ PDF Chat Learning with Symmetric Positive Definite Matrices via Generalized Bures-Wasserstein Geometry 2023 Andi Han
Bamdev Mishra
Pratik Jawanpuria
Junbin Gao
+ Unifying over-smoothing and over-squashing in graph neural networks: A physics informed approach and beyond 2023 Zhiqi Shao
Dai Shi
Andi Han
Yi Guo
Qibin Zhao
Junbin Gao
+ From Continuous Dynamics to Graph Neural Networks: Neural Diffusion and Beyond 2023 Andi Han
Dai Shi
Lequan Lin
Junbin Gao
+ Exposition on over-squashing problem on GNNs: Current Methods, Benchmarks and Challenges 2023 Dai Shi
Andi Han
Lequan Lin
Yi Guo
Junbin Gao
+ PDF Chat Riemannian block SPD coupling manifold and its application to optimal transport 2022 Andi Han
Bamdev Mishra
Pratik Jawanpuria
Junbin Gao
+ Riemannian block SPD coupling manifold and its application to optimal transport 2022 Andi Han
Bamdev Mishra
Pratik Jawanpuria
Junbin Gao
+ Riemannian Hamiltonian methods for min-max optimization on manifolds 2022 Andi Han
Bamdev Mishra
Pratik Jawanpuria
Pawan Kumar
Junbin Gao
+ A Simple Yet Effective SVD-GCN for Directed Graphs 2022 Chunya Zou
Andi Han
Lequan Lin
Junbin Gao
+ Differentially private Riemannian optimization 2022 Andi Han
Bamdev Mishra
Pratik Jawanpuria
Junbin Gao
+ Riemannian accelerated gradient methods via extrapolation 2022 Andi Han
Bamdev Mishra
Pratik Jawanpuria
Junbin Gao
+ Generalized energy and gradient flow via graph framelets 2022 Andi Han
Shi Dai
Zhiqi Shao
Junbin Gao
+ Rieoptax: Riemannian Optimization in JAX 2022 Saiteja Utpala
Andi Han
Pratik Jawanpuria
Bamdev Mishra
+ Generalized Laplacian Regularized Framelet Graph Neural Networks 2022 Zhiqi Shao
Andi Han
Shi Dai
Andrey L. Vasnev
Junbin Gao
+ On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry 2021 Andi Han
Bamdev Mishra
Pratik Jawanpuria
Junbin Gao
+ Riemannian Stochastic Recursive Momentum Method for non-Convex Optimization 2021 Andi Han
Junbin Gao
+ A Discussion On the Validity of Manifold Learning 2021 Dai Shi
Andi Han
Yi Guo
Junbin Gao
+ On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry 2021 Andi Han
Bamdev Mishra
Pratik Jawanpuria
Junbin Gao
+ Learning with symmetric positive definite matrices via generalized Bures-Wasserstein geometry 2021 Andi Han
Bamdev Mishra
Pratik Jawanpuria
Junbin Gao
+ Variance reduction for Riemannian non-convex optimization with batch size adaptation 2020 Andi Han
Junbin Gao
+ Riemannian stochastic recursive momentum method for non-convex optimization 2020 Andi Han
Junbin Gao
+ Escape saddle points faster on manifolds via perturbed Riemannian stochastic recursive gradient 2020 Andi Han
Junbin Gao
Common Coauthors
Commonly Cited References
Action Title Year Authors # of times referenced
+ PDF Chat Stochastic Gradient Descent on Riemannian Manifolds 2013 Silvère Bonnabel
8
+ Positive Definite Matrices 2009 Rajendra Bhatia
6
+ PDF Chat An alternative to EM for Gaussian mixture models: batch and stochastic Riemannian optimization 2019 Reshad Hosseini
Suvrit Sra
5
+ Riemannian Stochastic Recursive Gradient Algorithm 2018 Hiroyuki Kasai
Hiroyuki Sato
Bamdev Mishra
5
+ PDF Chat Conic Geometric Optimization on the Manifold of Positive Definite Matrices 2015 Suvrit Sra
Reshad Hosseini
5
+ PDF Chat Riemannian Stochastic Variance Reduced Gradient Algorithm with Retraction and Vector Transport 2019 Hiroyuki Sato
Hiroyuki Kasai
Bamdev Mishra
4
+ Riemannian adaptive stochastic gradient algorithms on matrix manifolds 2019 Hiroyuki Kasai
Pratik Jawanpuria
Bamdev Mishra
4
+ On the Bures–Wasserstein distance between positive definite matrices 2018 Rajendra Bhatia
Tanvi Jain
Yongdo Lim
4
+ Variance reduction for Riemannian non-convex optimization with batch size adaptation 2020 Andi Han
Junbin Gao
3
+ PDF Chat Faster First-Order Methods for Stochastic Non-Convex Optimization on Riemannian Manifolds 2019 Pan Zhou
Xiao‐Tong Yuan
Shuicheng Yan
Jiashi Feng
3
+ PDF Chat Adaptive regularization with cubics on manifolds 2020 Naman Agarwal
Nicolas Boumal
Brian Bullins
Coralia Cartis
3
+ PDF Chat A Broyden Class of Quasi-Newton Methods for Riemannian Optimization 2015 Wen Huang
Kyle A. Gallivan
Pierre-Antoine Absil
3
+ Wasserstein Riemannian geometry of Gaussian densities 2018 Luigi Malagò
Luigi Montrucchio
Giovanni Pistone
3
+ First-order Methods for Geodesically Convex Optimization 2016 Hongyi Zhang
Suvrit Sra
3
+ Optimization Algorithms on Matrix Manifolds 2007 P.-A. Absil
Robert Mahony
Rodolphe Sepulchre
3
+ PDF Chat A Riemannian Framework for Tensor Computing 2005 Xavier Pennec
Pierre Fillard
Nicholas Ayache
3
+ Manopt, a Matlab toolbox for optimization on manifolds 2013 Nicolas Boumal
Bamdev Mishra
Pierre-Antoine Absil
Rodolphe Sepulchre
3
+ PDF Chat Global rates of convergence for nonconvex optimization on manifolds 2018 Nicolas Boumal
P-A Absil
Coralia Cartis
3
+ PDF Chat A Unified Framework for Domain Adaptation Using Metric Learning on Manifolds 2019 Sridhar Mahadevan
Bamdev Mishra
Shalini Ghosh
3
+ PDF Chat Riemannian Preconditioning 2016 Bamdev Mishra
Rodolphe Sepulchre
2
+ Computational Optimal Transport: With Applications to Data Science 2019 Gabriel Peyré
Marco Cuturi
2
+ PDF Chat Riemannian Geometry of Symmetric Positive Definite Matrices via Cholesky Decomposition 2019 Zhenhua Lin
2
+ Riemannian Adaptive Optimization Methods. 2018 Gary Bécigneul
Octavian-Eugen Ganea
2
+ Stochastic Variance Reduction for Nonconvex Optimization 2016 Sashank J. Reddi
Ahmed Hefny
Suvrit Sra
Barnabás Póczos
Alex Smola
2
+ Curvature of the Manifold of Fixed-Rank Positive-Semidefinite Matrices Endowed with the Bures–Wasserstein Metric 2019 Estelle Massart
Julien M. Hendrickx
P.-A. Absil
2
+ PDF Chat Is Affine-Invariance Well Defined on SPD Matrices? A Principled Continuum of Metrics 2019 Yann Thanwerdas
Xavier Pennec
2
+ From Nesterov's Estimate Sequence to Riemannian Acceleration 2020 Kwangjun Ahn
Suvrit Sra
2
+ Bures-Wasserstein Geometry 2020 Jesse van Oostrum
2
+ PDF Chat Lower bounds for non-convex stochastic optimization 2022 Yossi Arjevani
Yair Carmon
John C. Duchi
Dylan J. Foster
Nathan Srebro
Blake Woodworth
2
+ An Introduction to Optimization on Smooth Manifolds 2023 Nicolas Boumal
2
+ Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds 2016 Hongyi Zhang
Sashank J. Reddi
Suvrit Sra
2
+ Exploring Complex Time-series Representations for Riemannian Machine Learning of Radar Data 2019 Daniel Brooks
Olivier Schwander
Frédéric Barbaresco
Jean-Yves Schneider
Matthieu Cord
2
+ PDF Chat From Manifold to Manifold: Geometry-Aware Dimensionality Reduction for SPD Matrices 2014 Mehrtash Harandi
Mathieu Salzmann
Richard Hartley
2
+ McTorch, a manifold optimization library for deep learning 2018 Mayank Meghwanshi
Pratik Jawanpuria
Anoop Kunchukuttan
Hiroyuki Kasai
Bamdev Mishra
2
+ R-SPIDER: A Fast Riemannian Stochastic Optimization Algorithm with Curvature Independent Rate 2018 Jingzhao Zhang
Hongyi Zhang
Suvrit Sra
2
+ Riemannian Adaptive Optimization Methods 2018 Gary Bécigneul
Octavian-Eugen Ganea
2
+ PDF Chat Manifold Optimization Over the Set of Doubly Stochastic Matrices: A Second-Order Geometry 2019 Ahmed Douik
Babak Hassibi
2
+ Geometry-Aware Similarity Learning on SPD Manifolds for Visual Recognition 2017 Zhiwu Huang
Ruiping Wang
Xianqiu Li
Wenxian Liu
Shiguang Shan
Luc Van Gool
Xilin Chen
2
+ A Riemannian symmetric rank-one trust-region method 2014 Wen Huang
Pierre-Antoine Absil
Kyle A. Gallivan
2
+ Stochastic Recursive Gradient Algorithm for Nonconvex Optimization 2017 Lam M. Nguyen
Jie Liu
Katya Scheinberg
Martin Takáč
2
+ PDF Chat The Riemannian Barzilai–Borwein method with nonmonotone line search and the matrix geometric mean computation 2017 Bruno Iannazzo
Margherita Porcelli
2
+ RTRMC: A Riemannian trust-region method for low-rank matrix completion 2011 Nicolas Boumal
Pierre-Antoine Absil
2
+ Fast Optimal Transport Averaging of Neuroimaging Data 2015 Alexandre Gramfort
Gabriel Peyré
Marco Cuturi
2
+ PDF Chat Efficient Recursive Algorithms for Computing the Mean Diffusion Tensor and Applications to DTI Segmentation 2012 Guang Cheng
Hesamoddin Salehian
Baba C. Vemuri
2
+ PDF Chat Log‐Euclidean metrics for fast and simple calculus on diffusion tensors 2006 Vincent Arsigny
Pierre Fillard
Xavier Pennec
Nicholas Ayache
2
+ Escaping Saddle Points with Adaptive Gradient Methods 2019 Matthew Staib
Sashank J. Reddi
Satyen Kale
Sanjiv Kumar
Suvrit Sra
2
+ Trust-Region Methods on Riemannian Manifolds 2006 Pierre-Antoine Absil
Christopher G. Baker
Kyle A. Gallivan
2
+ A new metric on the manifold of kernel matrices with application to matrix geometric means 2012 Suvrit Sra
2
+ Towards Riemannian Accelerated Gradient Methods 2018 Hongyi Zhang
Suvrit Sra
2
+ Positive definite matrices and the S-divergence 2015 Suvrit Sra
2