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Faster Eigenvector Computation via Shift-and-Invert Preconditioning

Faster Eigenvector Computation via Shift-and-Invert Preconditioning

26 May 2016
Dan Garber
Laurent Dinh
Chi Jin
Jascha Narain Sohl-Dickstein
Samy Bengio
Praneeth Netrapalli
Aaron Sidford
ArXivPDFHTML

Papers citing "Faster Eigenvector Computation via Shift-and-Invert Preconditioning"

50 / 786 papers shown
Title
Do Users Benefit From Interpretable Vision? A User Study, Baseline, And
  Dataset
Do Users Benefit From Interpretable Vision? A User Study, Baseline, And Dataset
Leon Sixt
M. Schuessler
Oana-Iuliana Popescu
Philipp Weiß
Tim Landgraf
FAtt
32
14
0
25 Apr 2022
Training and Evaluation of Deep Policies using Reinforcement Learning
  and Generative Models
Training and Evaluation of Deep Policies using Reinforcement Learning and Generative Models
Ali Ghadirzadeh
Petra Poklukar
Karol Arndt
Chelsea Finn
Ville Kyrki
Danica Kragic
Marten Bjorkman
OffRL
22
1
0
18 Apr 2022
A Variational Approach to Bayesian Phylogenetic Inference
A Variational Approach to Bayesian Phylogenetic Inference
Cheng Zhang
IV FrederickA.Matsen
BDL
24
17
0
16 Apr 2022
Conditional Injective Flows for Bayesian Imaging
Conditional Injective Flows for Bayesian Imaging
AmirEhsan Khorashadizadeh
K. Kothari
Leonardo Salsi
Ali Aghababaei Harandi
Maarten V. de Hoop
Ivan Dokmanić
MedIm
26
16
0
15 Apr 2022
Normalizing Flow-based Day-Ahead Wind Power Scenario Generation for
  Profitable and Reliable Delivery Commitments by Wind Farm Operators
Normalizing Flow-based Day-Ahead Wind Power Scenario Generation for Profitable and Reliable Delivery Commitments by Wind Farm Operators
Eike Cramer
Leonard Paeleke
Alexander Mitsos
Manuel Dahmen
24
11
0
05 Apr 2022
HiT-DVAE: Human Motion Generation via Hierarchical Transformer Dynamical
  VAE
HiT-DVAE: Human Motion Generation via Hierarchical Transformer Dynamical VAE
Xiaoyu Bie
Wen Guo
Simon Leglaive
Laurent Girin
Francesc Moreno-Noguer
Xavier Alameda-Pineda
VGen
3DH
35
13
0
04 Apr 2022
Learnable latent embeddings for joint behavioral and neural analysis
Learnable latent embeddings for joint behavioral and neural analysis
Steffen Schneider
Jin Hwa Lee
Mackenzie W. Mathis
19
209
0
01 Apr 2022
CaDeX: Learning Canonical Deformation Coordinate Space for Dynamic
  Surface Representation via Neural Homeomorphism
CaDeX: Learning Canonical Deformation Coordinate Space for Dynamic Surface Representation via Neural Homeomorphism
Jiahui Lei
Kostas Daniilidis
36
53
0
30 Mar 2022
MolGenSurvey: A Systematic Survey in Machine Learning Models for
  Molecule Design
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design
Yuanqi Du
Tianfan Fu
Jimeng Sun
Shengchao Liu
AI4CE
31
86
0
28 Mar 2022
BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality
  Speech Synthesis
BDDM: Bilateral Denoising Diffusion Models for Fast and High-Quality Speech Synthesis
Max W. Y. Lam
Jun Wang
Dan Su
Dong Yu
DiffM
36
92
0
25 Mar 2022
TO-FLOW: Efficient Continuous Normalizing Flows with Temporal
  Optimization adjoint with Moving Speed
TO-FLOW: Efficient Continuous Normalizing Flows with Temporal Optimization adjoint with Moving Speed
Shian Du
Yihong Luo
Wei Chen
Jian Xu
Delu Zeng
32
7
0
19 Mar 2022
Conditional Measurement Density Estimation in Sequential Monte Carlo via
  Normalizing Flow
Conditional Measurement Density Estimation in Sequential Monte Carlo via Normalizing Flow
Xiongjie Chen
Yunpeng Li
21
6
0
16 Mar 2022
Non-isotropy Regularization for Proxy-based Deep Metric Learning
Non-isotropy Regularization for Proxy-based Deep Metric Learning
Karsten Roth
Oriol Vinyals
Zeynep Akata
24
36
0
16 Mar 2022
Semi-Discrete Normalizing Flows through Differentiable Tessellation
Semi-Discrete Normalizing Flows through Differentiable Tessellation
Ricky T. Q. Chen
Brandon Amos
Maximilian Nickel
32
10
0
14 Mar 2022
A Survey on Deep Graph Generation: Methods and Applications
A Survey on Deep Graph Generation: Methods and Applications
Yanqiao Zhu
Yuanqi Du
Yinkai Wang
Yichen Xu
Jieyu Zhang
Qiang Liu
Shu Wu
3DV
GNN
31
67
0
13 Mar 2022
The Role of ImageNet Classes in Fréchet Inception Distance
The Role of ImageNet Classes in Fréchet Inception Distance
Tuomas Kynkaanniemi
Tero Karras
M. Aittala
Timo Aila
J. Lehtinen
EGVM
VLM
41
200
0
11 Mar 2022
FLAG: Flow-based 3D Avatar Generation from Sparse Observations
FLAG: Flow-based 3D Avatar Generation from Sparse Observations
S. Aliakbarian
Pashmina Cameron
Federica Bogo
Andrew Fitzgibbon
T. Cashman
3DH
20
55
0
11 Mar 2022
Conditional Synthetic Data Generation for Personal Thermal Comfort
  Models
Conditional Synthetic Data Generation for Personal Thermal Comfort Models
Hari Prasanna Das
C. Spanos
SyDa
AI4CE
18
2
0
10 Mar 2022
Variational methods for simulation-based inference
Variational methods for simulation-based inference
Manuel Glöckler
Michael Deistler
Jakob H. Macke
30
46
0
08 Mar 2022
GeoDiff: a Geometric Diffusion Model for Molecular Conformation
  Generation
GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation
Minkai Xu
Lantao Yu
Yang Song
Chence Shi
Stefano Ermon
Jian Tang
BDL
DiffM
50
496
0
06 Mar 2022
Off-Policy Evaluation in Embedded Spaces
Off-Policy Evaluation in Embedded Spaces
Jaron J. R. Lee
David Arbour
Georgios Theocharous
OffRL
22
3
0
05 Mar 2022
Self-Supervised Learning for Real-World Super-Resolution from Dual
  Zoomed Observations
Self-Supervised Learning for Real-World Super-Resolution from Dual Zoomed Observations
Zhilu Zhang
Ruohao Wang
Hongzhi Zhang
Yunjin Chen
W. Zuo
MDE
SupR
22
21
0
02 Mar 2022
Point Set Self-Embedding
Point Set Self-Embedding
Ruihui Li
Xianzhi Li
T. Wong
Chi-Wing Fu
3DPC
33
3
0
28 Feb 2022
Time Efficient Training of Progressive Generative Adversarial Network
  using Depthwise Separable Convolution and Super Resolution Generative
  Adversarial Network
Time Efficient Training of Progressive Generative Adversarial Network using Depthwise Separable Convolution and Super Resolution Generative Adversarial Network
Atharva Karwande
Pranesh Shridhar Kulkarni
Tejas Kolhe
Akshay Joshi
S. Kamble
GAN
22
2
0
24 Feb 2022
Multiple Importance Sampling ELBO and Deep Ensembles of Variational
  Approximations
Multiple Importance Sampling ELBO and Deep Ensembles of Variational Approximations
Oskar Kviman
Harald Melin
Hazal Koptagel
Victor Elvira
J. Lagergren
DRL
75
17
0
22 Feb 2022
Stochastic Causal Programming for Bounding Treatment Effects
Stochastic Causal Programming for Bounding Treatment Effects
Kirtan Padh
Jakob Zeitler
David S. Watson
Matt J. Kusner
Ricardo M. A. Silva
Niki Kilbertus
CML
32
26
0
22 Feb 2022
Continual Learning with Invertible Generative Models
Continual Learning with Invertible Generative Models
Jary Pomponi
Simone Scardapane
A. Uncini
BDL
48
4
0
11 Feb 2022
SAFER: Data-Efficient and Safe Reinforcement Learning via Skill
  Acquisition
SAFER: Data-Efficient and Safe Reinforcement Learning via Skill Acquisition
Dylan Slack
Yinlam Chow
Bo Dai
Nevan Wichers
OffRL
27
7
0
10 Feb 2022
Fair Interpretable Representation Learning with Correction Vectors
Fair Interpretable Representation Learning with Correction Vectors
Mattia Cerrato
A. Coronel
Marius Köppel
A. Segner
Roberto Esposito
Stefan Kramer
FaML
14
5
0
07 Feb 2022
Beyond Black Box Densities: Parameter Learning for the Deviated
  Components
Beyond Black Box Densities: Parameter Learning for the Deviated Components
Dat Do
Nhat Ho
X. Nguyen
16
2
0
05 Feb 2022
A Survey on Safety-Critical Driving Scenario Generation -- A
  Methodological Perspective
A Survey on Safety-Critical Driving Scenario Generation -- A Methodological Perspective
Wenhao Ding
Chejian Xu
Mansur Arief
Hao-ming Lin
Bo-wen Li
Ding Zhao
32
146
0
04 Feb 2022
Transport Score Climbing: Variational Inference Using Forward KL and
  Adaptive Neural Transport
Transport Score Climbing: Variational Inference Using Forward KL and Adaptive Neural Transport
Liyi Zhang
David M. Blei
C. A. Naesseth
27
6
0
03 Feb 2022
Gradient estimators for normalising flows
Gradient estimators for normalising flows
P. Białas
P. Korcyl
T. Stebel
BDL
19
3
0
02 Feb 2022
AdaAnn: Adaptive Annealing Scheduler for Probability Density
  Approximation
AdaAnn: Adaptive Annealing Scheduler for Probability Density Approximation
Emma R. Cobian
J. Hauenstein
Fang Liu
Daniele E. Schiavazzi
19
4
0
01 Feb 2022
Stay Positive: Non-Negative Image Synthesis for Augmented Reality
Stay Positive: Non-Negative Image Synthesis for Augmented Reality
Katie Z Luo
Guandao Yang
Wenqi Xian
Harald Haraldsson
B. Hariharan
Serge Belongie
DiffM
23
5
0
01 Feb 2022
Continual Repeated Annealed Flow Transport Monte Carlo
Continual Repeated Annealed Flow Transport Monte Carlo
A. G. Matthews
Michael Arbel
Danilo Jimenez Rezende
Arnaud Doucet
OT
37
46
0
31 Jan 2022
FastFlows: Flow-Based Models for Molecular Graph Generation
FastFlows: Flow-Based Models for Molecular Graph Generation
Nathan C. Frey
V. Gadepally
Bharath Ramsundar
19
12
0
28 Jan 2022
Learning Proximal Operators to Discover Multiple Optima
Learning Proximal Operators to Discover Multiple Optima
Lingxiao Li
Noam Aigerman
Vladimir G. Kim
Jiajin Li
Kristjan Greenewald
Mikhail Yurochkin
Justin Solomon
47
1
0
28 Jan 2022
Towards Data-driven LQR with Koopmanizing Flows
Towards Data-driven LQR with Koopmanizing Flows
Petar Bevanda
Maximilian Beier
Shahab Heshmati-alamdari
Stefan Sosnowski
Sandra Hirche
13
4
0
27 Jan 2022
Variational Model Inversion Attacks
Variational Model Inversion Attacks
Kuan-Chieh Jackson Wang
Yanzhe Fu
Ke Li
Ashish Khisti
R. Zemel
Alireza Makhzani
MIACV
25
95
0
26 Jan 2022
Invertible Voice Conversion
Invertible Voice Conversion
Zexin Cai
Ming Li
BDL
27
1
0
26 Jan 2022
Neural Information Squeezer for Causal Emergence
Neural Information Squeezer for Causal Emergence
Jiang Zhang
Kaiwei Liu
CML
30
14
0
25 Jan 2022
Stochastic normalizing flows as non-equilibrium transformations
Stochastic normalizing flows as non-equilibrium transformations
M. Caselle
E. Cellini
A. Nada
M. Panero
36
34
0
21 Jan 2022
WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for
  Superresolution
WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for Superresolution
Fabian Altekrüger
J. Hertrich
27
15
0
20 Jan 2022
Poseur: Direct Human Pose Regression with Transformers
Poseur: Direct Human Pose Regression with Transformers
Wei Mao
Yongtao Ge
Chunhua Shen
Zhi Tian
Xinlong Wang
Zhibin Wang
Anton Van Den Hengel
ViT
29
81
0
19 Jan 2022
Triangular Flows for Generative Modeling: Statistical Consistency,
  Smoothness Classes, and Fast Rates
Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates
N. J. Irons
M. Scetbon
Soumik Pal
Zaïd Harchaoui
33
17
0
31 Dec 2021
Machine Learning Trivializing Maps: A First Step Towards Understanding
  How Flow-Based Samplers Scale Up
Machine Learning Trivializing Maps: A First Step Towards Understanding How Flow-Based Samplers Scale Up
L. Debbio
Joe Marsh Rossney
Michael Wilson
16
6
0
31 Dec 2021
Uniform-in-Phase-Space Data Selection with Iterative Normalizing Flows
Uniform-in-Phase-Space Data Selection with Iterative Normalizing Flows
M. Hassanaly
Bruce A. Perry
M. Mueller
S. Yellapantula
40
5
0
28 Dec 2021
Solving time dependent Fokker-Planck equations via temporal normalizing
  flow
Solving time dependent Fokker-Planck equations via temporal normalizing flow
Xiaodong Feng
Li Zeng
Tao Zhou
AI4CE
36
25
0
28 Dec 2021
Multimodal Image Synthesis and Editing: The Generative AI Era
Multimodal Image Synthesis and Editing: The Generative AI Era
Fangneng Zhan
Yingchen Yu
Rongliang Wu
Jiahui Zhang
Shijian Lu
Lingjie Liu
Adam Kortylewski
Christian Theobalt
Eric Xing
EGVM
29
48
0
27 Dec 2021
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