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Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels

29 December 2014

Papers citing "Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels"

50 / 82 papers shown

Title
Randomized Quasi-Monte Carlo Features for Kernel Approximation Yuanmin Huang Zhen Huang 112 0 0 08 Mar 2025
Decentralized Online Ensembles of Gaussian Processes for Multi-Agent Systems Fernando Llorente Daniel Waxman Petar M. Djurić 76 0 0 07 Feb 2025
Kernel Approximation using Analog In-Memory Computing Julian Büchel Giacomo Camposampiero A. Vasilopoulos Corey Lammie Manuel Le Gallo Abbas Rahimi Abu Sebastian 78 0 0 05 Nov 2024
Fast Summation of Radial Kernels via QMC Slicing Johannes Hertrich Tim Jahn Michael Quellmalz 109 5 0 02 Oct 2024
On the design of scalable, high-precision spherical-radial Fourier features Ayoub Belhadji Qianyu Julie Zhu Youssef Marzouk 71 1 0 23 Aug 2024
Variance-Reducing Couplings for Random Features: Perspectives from Optimal Transport Isaac Reid Stratis Markou Krzysztof Choromanski Richard E. Turner Adrian Weller 54 1 0 26 May 2024
Spectraformer: A Unified Random Feature Framework for Transformer Duke Nguyen Du Yin Aditya Joshi Flora D. Salim 67 1 0 24 May 2024
DiJiang: Efficient Large Language Models through Compact Kernelization Hanting Chen Zhicheng Liu Xutao Wang Yuchuan Tian Yunhe Wang VLM 92 5 0 29 Mar 2024
Trigonometric Quadrature Fourier Features for Scalable Gaussian Process Regression Kevin Li Max Balakirsky Simon Mak 81 3 0 23 Oct 2023
Quasi-Monte Carlo Graph Random Features Isaac Reid K. Choromanski Adrian Weller 72 10 0 21 May 2023
Taming graph kernels with random features K. Choromanski 66 14 0 29 Apr 2023
FAVOR#: Sharp Attention Kernel Approximations via New Classes of Positive Random Features Valerii Likhosherstov K. Choromanski Kumar Avinava Dubey Frederick Liu Tamás Sarlós Adrian Weller 84 3 0 01 Feb 2023
Simplex Random Features Isaac Reid K. Choromanski Valerii Likhosherstov Adrian Weller 73 7 0 31 Jan 2023
Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models Luke Vilnis Yury Zemlyanskiy Patrick C. Murray Alexandre Passos Sumit Sanghai 105 10 0 18 Oct 2022
On The Relative Error of Random Fourier Features for Preserving Kernel Distance Kuan Cheng S. Jiang Luojian Wei Zhide Wei 95 1 0 01 Oct 2022
Quantum Adaptive Fourier Features for Neural Density Estimation Joseph A. Gallego-Mejia Fabio A. González 69 9 0 01 Aug 2022
Visual Attention Methods in Deep Learning: An In-Depth Survey Mohammed Hassanin Saeed Anwar Ibrahim Radwan Fahad Shahbaz Khan Ajmal Mian 136 166 0 16 Apr 2022
A Call for Clarity in Beam Search: How It Works and When It Stops Jungo Kasai Keisuke Sakaguchi Ronan Le Bras Dragomir R. Radev Yejin Choi Noah A. Smith 88 9 0 11 Apr 2022
HD-cos Networks: Efficient Neural Architectures for Secure Multi-Party Computation Wittawat Jitkrittum Michal Lukasik A. Suresh Felix X. Yu Gang Wang 18 0 0 28 Oct 2021
On Learning the Transformer Kernel Sankalan Pal Chowdhury Adamos Solomou Kumar Avinava Dubey Mrinmaya Sachan ViT 131 14 0 15 Oct 2021
Hybrid Random Features K. Choromanski Haoxian Chen Han Lin Yuanzhe Ma Arijit Sehanobish ... Andy Zeng Valerii Likhosherstov Dmitry Kalashnikov Vikas Sindhwani Adrian Weller 82 21 0 08 Oct 2021
Exponential Error Convergence in Data Classification with Optimized Random Features: Acceleration by Quantum Machine Learning H. Yamasaki Sho Sonoda 73 6 0 16 Jun 2021
Hermite Polynomial Features for Private Data Generation Margarita Vinaroz Mohammad-Amin Charusaie Frederik Harder Kamil Adamczewski Mijung Park 97 25 0 09 Jun 2021
Learnable Fourier Features for Multi-Dimensional Spatial Positional Encoding Yang Li Si Si Gang Li Cho-Jui Hsieh Samy Bengio 87 96 0 05 Jun 2021
MetaKernel: Learning Variational Random Features with Limited Labels Yingjun Du Haoliang Sun Xiantong Zhen Jun Xu Yilong Yin Ling Shao Cees G. M. Snoek VLM BDL 37 5 0 08 May 2021
Towards Unbiased Random Features with Lower Variance For Stationary Indefinite Kernels Qin Luo Kun Fang Jie Yang Xiaolin Huang 40 1 0 13 Apr 2021
Random Feature Attention Hao Peng Nikolaos Pappas Dani Yogatama Roy Schwartz Noah A. Smith Lingpeng Kong 133 362 0 03 Mar 2021
Learning with Density Matrices and Random Features Fabio A. González Joseph A. Gallego-Mejia Santiago Toledo-Cortés Vladimir Vargas-Calderón 60 29 0 08 Feb 2021
Discrepancy Bounds for a Class of Negatively Dependent Random Points Including Latin Hypercube Samples M. Gnewuch Nils Hebbinghaus 43 24 0 06 Feb 2021
Gauss-Legendre Features for Gaussian Process Regression Paz Fink Shustin H. Avron GP 59 11 0 04 Jan 2021
Towards a Unified Quadrature Framework for Large-Scale Kernel Machines Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens 88 4 0 03 Nov 2020
Subgroup-based Rank-1 Lattice Quasi-Monte Carlo Yueming Lyu Yuan. Yuan Ivor W. Tsang 55 4 0 29 Oct 2020
Low-dimensional Interpretable Kernels with Conic Discriminant Functions for Classification Gurhan Ceylan ¸S. ˙Ilker Birbil FAtt 26 0 0 17 Jul 2020
Learning to Learn Kernels with Variational Random Features Xiantong Zhen Hao Sun Yingjun Du Jun Xu Yilong Yin Ling Shao Cees G. M. Snoek DRL 72 34 0 11 Jun 2020
Demystifying Orthogonal Monte Carlo and Beyond Han Lin Haoxian Chen Tianyi Zhang Clément Laroche K. Choromanski 47 9 0 27 May 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 126 176 0 23 Apr 2020
Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions H. Yamasaki Sathyawageeswar Subramanian Sho Sonoda M. Koashi 134 17 0 22 Apr 2020
Intrinsic Exploration as Multi-Objective RL Philippe Morere F. Ramos 20 1 0 06 Apr 2020
Generalization Guarantees for Sparse Kernel Approximation with Entropic Optimal Features Liang Ding Rui Tuo Shahin Shahrampour 41 8 0 11 Feb 2020
Large-scale Kernel Methods and Applications to Lifelong Robot Learning Raffaello Camoriano 82 1 0 11 Dec 2019
Random Fourier Features via Fast Surrogate Leverage Weighted Sampling Fanghui Liu Xiaolin Huang Yudong Chen Jie Yang Johan A. K. Suykens 68 21 0 20 Nov 2019
ORCCA: Optimal Randomized Canonical Correlation Analysis Yinsong Wang Shahin Shahrampour 103 5 0 11 Oct 2019
Automated Spectral Kernel Learning Jian Li Yong Liu Weiping Wang 71 14 0 11 Sep 2019
Learning Stabilizable Nonlinear Dynamics with Contraction-Based Regularization Sumeet Singh Spencer M. Richards Vikas Sindhwani Jean-Jacques E. Slotine Marco Pavone 92 76 0 29 Jul 2019
Sampled Softmax with Random Fourier Features A. S. Rawat Jiecao Chen Felix X. Yu A. Suresh Sanjiv Kumar 93 55 0 24 Jul 2019
BayesSim: adaptive domain randomization via probabilistic inference for robotics simulators F. Ramos Rafael Possas Dieter Fox 60 158 0 04 Jun 2019
Kernel Mean Embedding Based Hypothesis Tests for Comparing Spatial Point Patterns Raif M. Rustamov James T. Klosowski 58 7 0 31 May 2019
Structured Monte Carlo Sampling for Nonisotropic Distributions via Determinantal Point Processes K. Choromanski Aldo Pacchiano Jack Parker-Holder Yunhao Tang 69 3 0 29 May 2019
On Sampling Random Features From Empirical Leverage Scores: Implementation and Theoretical Guarantees Shahin Shahrampour Soheil Kolouri 51 10 0 20 Mar 2019
Low-Precision Random Fourier Features for Memory-Constrained Kernel Approximation Jian Zhang Avner May Tri Dao Christopher Ré 80 29 0 31 Oct 2018