Transformers are Deep Infinite-Dimensional Non-Mercer Binary Kernel Machines

2 June 2021

Papers citing "Transformers are Deep Infinite-Dimensional Non-Mercer Binary Kernel Machines"

7 / 7 papers shown

Title
Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method Qinghua Tao F. Tonin Alex Lambert Yingyi Chen Panagiotis Patrinos Johan A. K. Suykens 35 1 0 13 Jun 2024
Learning Functional Transduction Mathieu Chalvidal Thomas Serre Rufin VanRullen AI4CE 35 2 0 01 Feb 2023
Random Fourier Features for Asymmetric Kernels Ming-qian He Fan He Fanghui Liu Xiaolin Huang 20 3 0 18 Sep 2022
Choose a Transformer: Fourier or Galerkin Shuhao Cao 42 221 0 31 May 2021
Dropout: Explicit Forms and Capacity Control R. Arora Peter L. Bartlett Poorya Mianjy Nathan Srebro 64 37 0 06 Mar 2020
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 297 6,959 0 20 Apr 2018
Effective Approaches to Attention-based Neural Machine Translation Thang Luong Hieu H. Pham Christopher D. Manning 218 7,926 0 17 Aug 2015