v1v2 (latest)

Scalable Neural Network Kernels

20 October 2023

Arijit Sehanobish

Krzysztof Choromanski

Yunfan Zhao

Kumar Avinava Dubey

Valerii Likhosherstov

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Papers citing "Scalable Neural Network Kernels"

32 / 32 papers shown

Title
HealthQ: Unveiling Questioning Capabilities of LLM Chains in Healthcare Conversations Ziyu Wang Hao Li Di Huang Amir M. Rahmani Chae-Won Shin Amir M. Rahmani LM&MA 103 10 0 28 Sep 2024
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 71 3 0 01 Feb 2023
A Kernel-Based View of Language Model Fine-Tuning Sadhika Malladi Alexander Wettig Dingli Yu Danqi Chen Sanjeev Arora VLM 122 69 0 11 Oct 2022
Towards a Unified View on Visual Parameter-Efficient Transfer Learning Bruce X. B. Yu Jianlong Chang Lin Liu Qi Tian Changan Chen VPVLM VLM 102 36 0 03 Oct 2022
Chefs' Random Tables: Non-Trigonometric Random Features Valerii Likhosherstov K. Choromanski Kumar Avinava Dubey Frederick Liu Tamás Sarlós Adrian Weller 73 18 0 30 May 2022
AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition Shoufa Chen Chongjian Ge Zhan Tong Jiangliu Wang Yibing Song Jue Wang Ping Luo 205 690 0 26 May 2022
Adaptable Adapters N. Moosavi Quentin Delfosse Kristian Kersting Iryna Gurevych 86 21 0 03 May 2022
Parameter-efficient Model Adaptation for Vision Transformers Xuehai He Chunyuan Li Pengchuan Zhang Jianwei Yang Xinze Wang 62 90 0 29 Mar 2022
Visual Prompt Tuning Menglin Jia Luming Tang Bor-Chun Chen Claire Cardie Serge Belongie Bharath Hariharan Ser-Nam Lim VLM VPVLM 155 1,641 0 23 Mar 2022
Random Gegenbauer Features for Scalable Kernel Methods Insu Han A. Zandieh H. Avron 78 4 0 07 Feb 2022
Learning with Asymmetric Kernels: Least Squares and Feature Interpretation Ming-qian He Fan He Lei Shi Xiaolin Huang Johan A. K. Suykens 32 12 0 03 Feb 2022
Improved Random Features for Dot Product Kernels Jonas Wacker Motonobu Kanagawa Maurizio Filippone 50 8 0 21 Jan 2022
Towards a Unified View of Parameter-Efficient Transfer Learning Junxian He Chunting Zhou Xuezhe Ma Taylor Berg-Kirkpatrick Graham Neubig AAML 135 952 0 08 Oct 2021
BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models Elad Ben-Zaken Shauli Ravfogel Yoav Goldberg 181 1,240 0 18 Jun 2021
Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks Rabeeh Karimi Mahabadi Sebastian Ruder Mostafa Dehghani James Henderson MoE 78 313 0 08 Jun 2021
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 670 41,430 0 22 Oct 2020
AdapterDrop: On the Efficiency of Adapters in Transformers Andreas Rucklé Gregor Geigle Max Glockner Tilman Beck Jonas Pfeiffer Nils Reimers Iryna Gurevych 121 267 0 22 Oct 2020
Learning Potentials of Quantum Systems using Deep Neural Networks Arijit Sehanobish H. Corzo Onur Kara David van Dijk 36 12 0 23 Jun 2020
Implicit Neural Representations with Periodic Activation Functions Vincent Sitzmann Julien N. P. Martel Alexander W. Bergman David B. Lindell Gordon Wetzstein AI4TS 165 2,571 0 17 Jun 2020
Knowledge Distillation: A Survey Jianping Gou B. Yu Stephen J. Maybank Dacheng Tao VLM 125 2,982 0 09 Jun 2020
A Corrective View of Neural Networks: Representation, Memorization and Learning Guy Bresler Dheeraj M. Nagaraj MLT 65 18 0 01 Feb 2020
What Would Elsa Do? Freezing Layers During Transformer Fine-Tuning Jaejun Lee Raphael Tang Jimmy J. Lin 67 126 0 08 Nov 2019
Parameter-Efficient Transfer Learning for NLP N. Houlsby A. Giurgiu Stanislaw Jastrzebski Bruna Morrone Quentin de Laroussilhe Andrea Gesmundo Mona Attariyan Sylvain Gelly 221 4,514 0 02 Feb 2019
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.8K 95,175 0 11 Oct 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 273 3,219 0 20 Jun 2018
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 1.1K 7,196 0 20 Apr 2018
Orthogonal Recurrent Neural Networks with Scaled Cayley Transform Kyle E. Helfrich Devin Willmott Qiang Ye 91 131 0 29 Jul 2017
The Unreasonable Effectiveness of Structured Random Orthogonal Embeddings K. Choromanski Mark Rowland Adrian Weller 87 85 0 02 Mar 2017
Orthogonal Random Features Felix X. Yu A. Suresh K. Choromanski D. Holtmann-Rice Sanjiv Kumar 94 222 0 28 Oct 2016
Deep Learning in Neural Networks: An Overview Jürgen Schmidhuber HAI 246 16,377 0 30 Apr 2014
Random Feature Maps for Dot Product Kernels Purushottam Kar H. Karnick 85 257 0 31 Jan 2012
Analysis and Extension of Arc-Cosine Kernels for Large Margin Classification Youngmin Cho Lawrence K. Saul 94 28 0 16 Dec 2011