Faster Eigenvector Computation via Shift-and-Invert Preconditioning

26 May 2016

Dan Garber

Laurent Dinh

Chi Jin

Jascha Narain Sohl-Dickstein

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

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Title
RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit Feedback Ilya Shenbin Anton M. Alekseev E. Tutubalina Valentin Malykh Sergey I. Nikolenko BDL DRL 11 196 0 24 Dec 2019
Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax Andres Potapczynski G. Loaiza-Ganem John P. Cunningham 29 29 0 19 Dec 2019
C-Flow: Conditional Generative Flow Models for Images and 3D Point Clouds Albert Pumarola S. Popov Francesc Moreno-Noguer V. Ferrari 3DPC AI4CE 23 80 0 15 Dec 2019
InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers T. Nguyen Animesh Garg Richard G. Baraniuk Anima Anandkumar TPM 25 9 0 09 Dec 2019
Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference Erik Nijkamp Bo Pang Tian Han Linqi Zhou Song-Chun Zhu Ying Nian Wu BDL DRL 19 2 0 04 Dec 2019
Self-attention with Functional Time Representation Learning Da Xu Chuanwei Ruan Sushant Kumar Evren Körpeoglu Kannan Achan AI4TS 15 113 0 28 Nov 2019
Weight of Evidence as a Basis for Human-Oriented Explanations David Alvarez-Melis Hal Daumé Jennifer Wortman Vaughan Hanna M. Wallach XAI FAtt 13 20 0 29 Oct 2019
On Investigation of Unsupervised Speech Factorization Based on Normalization Flow Haoran Sun Yunqi Cai Lantian Li Dong Wang 16 1 0 29 Oct 2019
Target-Oriented Deformation of Visual-Semantic Embedding Space Takashi Matsubara 18 7 0 15 Oct 2019
FIS-GAN: GAN with Flow-based Importance Sampling Shiyu Yi Donglin Zhan Wenqing Zhang Zhengyang Geng Kang An Hao Wang GAN 22 3 0 06 Oct 2019
High Mutual Information in Representation Learning with Symmetric Variational Inference M. Livne Kevin Swersky David J. Fleet SSL DRL 28 0 0 04 Oct 2019
The Neural Moving Average Model for Scalable Variational Inference of State Space Models Tom Ryder D. Prangle Andrew Golightly Isaac Matthews BDL AI4TS 16 6 0 02 Oct 2019
Relaxing Bijectivity Constraints with Continuously Indexed Normalising Flows R. Cornish Anthony L. Caterini George Deligiannidis Arnaud Doucet 19 2 0 30 Sep 2019
Hamiltonian Generative Networks Peter Toth Danilo Jimenez Rezende Andrew Jaegle S. Racanière Aleksandar Botev I. Higgins BDL DRL AI4CE GAN 11 214 0 30 Sep 2019
Towards neural networks that provably know when they don't know Alexander Meinke Matthias Hein OODD 22 139 0 26 Sep 2019
Intensity-Free Learning of Temporal Point Processes Oleksandr Shchur Marin Bilos Stephan Günnemann AI4TS 14 167 0 26 Sep 2019
PixelVAE++: Improved PixelVAE with Discrete Prior Hossein Sadeghi Evgeny Andriyash W. Vinci L. Buffoni Mohammad H. Amin BDL DRL 19 33 0 26 Aug 2019
Conditional Flow Variational Autoencoders for Structured Sequence Prediction Apratim Bhattacharyya M. Hanselmann Mario Fritz Bernt Schiele C. Straehle BDL DRL AI4TS 16 83 0 24 Aug 2019
Modeling the Gaia Color-Magnitude Diagram with Bayesian Neural Flows to Constrain Distance Estimates M. Cranmer Richard Galvez L. Anderson D. Spergel S. Ho 16 7 0 21 Aug 2019
Survey on Deep Neural Networks in Speech and Vision Systems M. Alam Manar D. Samad Lasitha Vidyaratne Alexander M. Glandon Khan M. Iftekharuddin 3DV VLM AI4TS 31 205 0 16 Aug 2019
Transport Monte Carlo: High-Accuracy Posterior Approximation via Random Transport L. Duan OT 29 11 0 24 Jul 2019
Subspace Inference for Bayesian Deep Learning Pavel Izmailov Wesley J. Maddox Polina Kirichenko T. Garipov Dmitry Vetrov A. Wilson UQCV BDL 30 141 0 17 Jul 2019
Copula & Marginal Flows: Disentangling the Marginal from its Joint Magnus Wiese R. Knobloch R. Korn DRL 13 21 0 07 Jul 2019
PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows Guandao Yang Xun Huang Zekun Hao Ming-Yu Liu Serge J. Belongie Bharath Hariharan 3DPC 13 654 0 28 Jun 2019
Unsupervised State Representation Learning in Atari Ankesh Anand Evan Racah Sherjil Ozair Yoshua Bengio Marc-Alexandre Côté R. Devon Hjelm SSL 27 253 0 19 Jun 2019
Learning Symmetries of Classical Integrable Systems Roberto Bondesan A. Lamacraft 19 39 0 11 Jun 2019
Stochastic Neural Network with Kronecker Flow Chin-Wei Huang Ahmed Touati Pascal Vincent Gintare Karolina Dziugaite Alexandre Lacoste Aaron Courville BDL 24 8 0 10 Jun 2019
Cubic-Spline Flows Conor Durkan Artur Bekasov Iain Murray George Papamakarios TPM 45 57 0 05 Jun 2019
Effective LHC measurements with matrix elements and machine learning Johann Brehmer Kyle Cranmer Irina Espejo F. Kling Gilles Louppe J. Pavez 23 14 0 04 Jun 2019
Adversarial Robustness as a Prior for Learned Representations Logan Engstrom Andrew Ilyas Shibani Santurkar Dimitris Tsipras Brandon Tran A. Madry OOD AAML 11 63 0 03 Jun 2019
On the Necessity and Effectiveness of Learning the Prior of Variational Auto-Encoder Haowen Xu Wenxiao Chen Jinlin Lai Zhihan Li Youjian Zhao Dan Pei DRL BDL 18 14 0 31 May 2019
Structured Output Learning with Conditional Generative Flows You Lu Bert Huang BDL DRL 13 72 0 30 May 2019
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference Jakob Kruse Gianluca Detommaso Ullrich Kothe Robert Scheichl 13 45 0 25 May 2019
Discrete Flows: Invertible Generative Models of Discrete Data Dustin Tran Keyon Vafa Kumar Krishna Agrawal Laurent Dinh Ben Poole DRL 19 114 0 24 May 2019
Non-Autoregressive Neural Text-to-Speech Kainan Peng Wei Ping Z. Song Kexin Zhao 27 39 0 21 May 2019
Minimal Achievable Sufficient Statistic Learning Milan Cvitkovic Günther Koliander 17 12 0 19 May 2019
Similarity of Neural Network Representations Revisited Simon Kornblith Mohammad Norouzi Honglak Lee Geoffrey E. Hinton 15 1,355 0 01 May 2019
Learning Non-Convergent Non-Persistent Short-Run MCMC Toward Energy-Based Model Erik Nijkamp Mitch Hill Song-Chun Zhu Ying Nian Wu 29 208 0 22 Apr 2019
Effective Estimation of Deep Generative Language Models Tom Pelsmaeker Wilker Aziz BDL 22 27 0 17 Apr 2019
Learning Probabilistic Multi-Modal Actor Models for Vision-Based Robotic Grasping Mengyuan Yan A. Li Mrinal Kalakrishnan P. Pastor 11 18 0 15 Apr 2019
A Learned Representation for Scalable Vector Graphics Raphael Gontijo-Lopes David R Ha Douglas Eck Jonathon Shlens GAN OCL 30 113 0 04 Apr 2019
Nonparametric Density Estimation for High-Dimensional Data - Algorithms and Applications Zhipeng Wang D. W. Scott 22 69 0 30 Mar 2019
High Fidelity Face Manipulation with Extreme Poses and Expressions Chaoyou Fu Yibo Hu Xiang Wu Guoli Wang Qian Zhang R. He CVBM 24 25 0 28 Mar 2019
Wasserstein Dependency Measure for Representation Learning Sherjil Ozair Corey Lynch Yoshua Bengio Aaron van den Oord Sergey Levine P. Sermanet SSL DRL 22 115 0 28 Mar 2019
Embarrassingly parallel MCMC using deep invertible transformations Diego Mesquita P. Blomstedt Samuel Kaski 9 18 0 11 Mar 2019
Likelihood-free MCMC with Amortized Approximate Ratio Estimators Joeri Hermans Volodimir Begy Gilles Louppe 29 20 0 10 Mar 2019
High-Fidelity Image Generation With Fewer Labels Mario Lucic Michael Tschannen Marvin Ritter Xiaohua Zhai Olivier Bachem Sylvain Gelly GAN OOD 31 157 0 06 Mar 2019
VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation Manoj Kumar Mohammad Babaeizadeh D. Erhan Chelsea Finn Sergey Levine Laurent Dinh Durk Kingma VGen 25 131 0 04 Mar 2019
Conditional Density Estimation with Neural Networks: Best Practices and Benchmarks Jonas Rothfuss Fabio Ferreira Simon Walther Maxim Ulrich TPM 19 73 0 03 Mar 2019
Improving Evolutionary Strategies with Generative Neural Networks Louis Faury Clément Calauzènes Olivier Fercoq Syrine Krichene 11 12 0 31 Jan 2019