Orthogonal Random Features

28 October 2016

Sanjiv Kumar

Papers citing "Orthogonal Random Features"

34 / 34 papers shown

Title
ProKeR: A Kernel Perspective on Few-Shot Adaptation of Large Vision-Language Models Yassir Bendou Amine Ouasfi Vincent Gripon A. Boukhayma VLM 51 0 0 19 Jan 2025
Fast Summation of Radial Kernels via QMC Slicing Johannes Hertrich Tim Jahn Michael Quellmalz 26 5 0 02 Oct 2024
Scalable Neural Network Kernels Arijit Sehanobish Krzysztof Choromanski Yunfan Zhao Kumar Avinava Dubey Valerii Likhosherstov 41 4 0 20 Oct 2023
Improved Regret Bounds for Online Kernel Selection under Bandit Feedback Junfan Li Shizhong Liao 17 1 0 09 Mar 2023
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning Zhijie Deng Feng Zhou Jun Zhu BDL 47 19 0 23 Oct 2022
Pure Transformers are Powerful Graph Learners Jinwoo Kim Tien Dat Nguyen Seonwoo Min Sungjun Cho Moontae Lee Honglak Lee Seunghoon Hong 43 189 0 06 Jul 2022
A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness J. Liu Shreyas Padhy Jie Jessie Ren Zi Lin Yeming Wen Ghassen Jerfel Zachary Nado Jasper Snoek Dustin Tran Balaji Lakshminarayanan UQCV BDL 26 48 0 01 May 2022
NeuralEF: Deconstructing Kernels by Deep Neural Networks Zhijie Deng Jiaxin Shi Jun Zhu 27 18 0 30 Apr 2022
Local Random Feature Approximations of the Gaussian Kernel Jonas Wacker Maurizio Filippone 22 3 0 12 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 26 6 0 11 Apr 2022
Monarch: Expressive Structured Matrices for Efficient and Accurate Training Tri Dao Beidi Chen N. Sohoni Arjun D Desai Michael Poli Jessica Grogan Alexander Liu Aniruddh Rao Atri Rudra Christopher Ré 22 87 0 01 Apr 2022
Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation Chao Chen Haoyu Geng Nianzu Yang Junchi Yan Daiyue Xue Jianping Yu Xiaokang Yang HAI AI4TS 27 11 0 30 Mar 2022
Linearizing Transformer with Key-Value Memory Yizhe Zhang Deng Cai 20 5 0 23 Mar 2022
Uniform Approximations for Randomized Hadamard Transforms with Applications Yeshwanth Cherapanamjeri Jelani Nelson 38 11 0 03 Mar 2022
EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning S. Vargaftik Ran Ben-Basat Amit Portnoy Gal Mendelson Y. Ben-Itzhak Michael Mitzenmacher FedML 46 45 0 19 Aug 2021
Towards Unbiased Random Features with Lower Variance For Stationary Indefinite Kernels Qin Luo Kun Fang Jie-jin Yang Xiaolin Huang 13 1 0 13 Apr 2021
Denoising Score Matching with Random Fourier Features Olga Tsymboi Yermek Kapushev Evgeny Burnaev Ivan V. Oseledets 31 1 0 13 Jan 2021
Rethinking Attention with Performers K. Choromanski Valerii Likhosherstov David Dohan Xingyou Song Andreea Gane ... Afroz Mohiuddin Lukasz Kaiser David Belanger Lucy J. Colwell Adrian Weller 31 1,521 0 30 Sep 2020
Probabilistic Neighbourhood Component Analysis: Sample Efficient Uncertainty Estimation in Deep Learning Ankur Mallick Chaitanya Dwivedi B. Kailkhura Gauri Joshi T. Y. Han UQCV BDL 42 6 0 18 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 27 34 0 11 Jun 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 44 172 0 23 Apr 2020
Implicit Regularization of Random Feature Models Arthur Jacot Berfin Simsek Francesco Spadaro Clément Hongler Franck Gabriel 31 82 0 19 Feb 2020
COKE: Communication-Censored Decentralized Kernel Learning Ping Xu Yue Wang Xiang Chen Z. Tian 15 20 0 28 Jan 2020
Graph Random Neural Features for Distance-Preserving Graph Representations Daniele Zambon Cesare Alippi L. Livi 21 1 0 09 Sep 2019
Sampled Softmax with Random Fourier Features A. S. Rawat Jiecao Chen Felix X. Yu A. Suresh Sanjiv Kumar 33 55 0 24 Jul 2019
Frontal Low-rank Random Tensors for Fine-grained Action Segmentation Yan Zhang Krikamol Muandet Qianli Ma Heiko Neumann Siyu Tang 28 3 0 03 Jun 2019
Walsh-Hadamard Variational Inference for Bayesian Deep Learning Simone Rossi Sébastien Marmin Maurizio Filippone BDL 32 14 0 27 May 2019
Spatial Analysis Made Easy with Linear Regression and Kernels Philip Milton E. Giorgi Samir Bhatt 27 16 0 22 Feb 2019
Manifold Regularization for Kernelized LSTD Xinyan Yan K. Choromanski Byron Boots Vikas Sindhwani OffRL 13 1 0 15 Oct 2017
Online Learning for Distribution-Free Prediction Dave Zachariah Petre Stoica Thomas B. Schon 16 8 0 15 Mar 2017
The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings K. Choromanski Mark Rowland Adrian Weller 10 85 0 02 Mar 2017
Distributed Mean Estimation with Limited Communication A. Suresh Felix X. Yu Sanjiv Kumar H. B. McMahan FedML 22 360 0 02 Nov 2016
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 34 4,588 0 18 Oct 2016
Sketching for Large-Scale Learning of Mixture Models Nicolas Keriven Anthony Bourrier Rémi Gribonval Patrick Pérez 25 75 0 09 Jun 2016