Measuring the Intrinsic Dimension of Objective Landscapes

24 April 2018

Papers citing "Measuring the Intrinsic Dimension of Objective Landscapes"

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Title
Efficient Methods for Natural Language Processing: A Survey Marcos Vinícius Treviso Ji-Ung Lee Tianchu Ji Betty van Aken Qingqing Cao ... Emma Strubell Niranjan Balasubramanian Leon Derczynski Iryna Gurevych Roy Schwartz 33 109 0 31 Aug 2022
LGV: Boosting Adversarial Example Transferability from Large Geometric Vicinity Martin Gubri Maxime Cordy Mike Papadakis Yves Le Traon Koushik Sen AAML 35 51 0 26 Jul 2022
Towards Semantic Communication Protocols: A Probabilistic Logic Perspective Sejin Seo Jihong Park Seung-Woo Ko Jinho Choi M. Bennis Seong-Lyun Kim 30 22 0 08 Jul 2022
When Does Differentially Private Learning Not Suffer in High Dimensions? Xuechen Li Daogao Liu Tatsunori Hashimoto Huseyin A. Inan Janardhan Kulkarni Y. Lee Abhradeep Thakurta 36 58 0 01 Jul 2022
LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood Piotr Tempczyk Rafał Michaluk Łukasz Garncarek Przemysław Spurek Jacek Tabor Adam Goliñski 35 26 0 29 Jun 2022
Few-Shot Learning by Dimensionality Reduction in Gradient Space M. Gauch M. Beck Thomas Adler D. Kotsur Stefan Fiel ... Markus Holzleitner Werner Zellinger D. Klotz Sepp Hochreiter Sebastian Lehner 48 9 0 07 Jun 2022
PERFECT: Prompt-free and Efficient Few-shot Learning with Language Models Rabeeh Karimi Mahabadi Luke Zettlemoyer James Henderson Marzieh Saeidi Lambert Mathias Ves Stoyanov Majid Yazdani VLM 34 70 0 03 Apr 2022
APG: Adaptive Parameter Generation Network for Click-Through Rate Prediction Bencheng Yan Pengjie Wang Kai Zhang Feng Li Hongbo Deng Jian Xu Bo Zheng 27 20 0 30 Mar 2022
Parameter-efficient Model Adaptation for Vision Transformers Xuehai He Chunyuan Li Pengchuan Zhang Jianwei Yang Junfeng Fang 30 84 0 29 Mar 2022
Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models Ning Ding Yujia Qin Guang Yang Fu Wei Zonghan Yang ... Jianfei Chen Yang Liu Jie Tang Juan Li Maosong Sun 34 197 0 14 Mar 2022
Low-Loss Subspace Compression for Clean Gains against Multi-Agent Backdoor Attacks Siddhartha Datta N. Shadbolt AAML 32 6 0 07 Mar 2022
Transferability in Deep Learning: A Survey Junguang Jiang Yang Shu Jianmin Wang Mingsheng Long OOD 34 101 0 15 Jan 2022
Model Stability with Continuous Data Updates Huiting Liu Avinesh P.V.S Siddharth Patwardhan Peter Grasch Sachin Agarwal 32 16 0 14 Jan 2022
Black-Box Tuning for Language-Model-as-a-Service Tianxiang Sun Yunfan Shao Hong Qian Xuanjing Huang Xipeng Qiu VLM 50 256 0 10 Jan 2022
Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks Tolga Birdal Aaron Lou Leonidas J. Guibas Umut cSimcsekli 32 61 0 25 Nov 2021
Subspace Adversarial Training Tao Li Yingwen Wu Sizhe Chen Kun Fang Xiaolin Huang AAML OOD 44 56 0 24 Nov 2021
Differentially Private Fine-tuning of Language Models Da Yu Saurabh Naik A. Backurs Sivakanth Gopi Huseyin A. Inan ... Y. Lee Andre Manoel Lukas Wutschitz Sergey Yekhanin Huishuai Zhang 134 351 0 13 Oct 2021
Robust fine-tuning of zero-shot models Mitchell Wortsman Gabriel Ilharco Jong Wook Kim Mike Li Simon Kornblith ... Raphael Gontijo-Lopes Hannaneh Hajishirzi Ali Farhadi Hongseok Namkoong Ludwig Schmidt VLM 66 695 0 04 Sep 2021
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 46 0 19 Aug 2021
Analytic Study of Families of Spurious Minima in Two-Layer ReLU Neural Networks: A Tale of Symmetry II Yossi Arjevani M. Field 28 18 0 21 Jul 2021
What can linear interpolation of neural network loss landscapes tell us? Tiffany J. Vlaar Jonathan Frankle MoMe 30 27 0 30 Jun 2021
BitFit: Simple Parameter-efficient Fine-tuning for Transformer-based Masked Language-models Elad Ben-Zaken Shauli Ravfogel Yoav Goldberg 97 1,157 0 18 Jun 2021
Compacter: Efficient Low-Rank Hypercomplex Adapter Layers Rabeeh Karimi Mahabadi James Henderson Sebastian Ruder MoE 67 469 0 08 Jun 2021
Privately Learning Subspaces Vikrant Singhal Thomas Steinke 27 20 0 28 May 2021
Analyzing Monotonic Linear Interpolation in Neural Network Loss Landscapes James Lucas Juhan Bae Michael Ruogu Zhang Stanislav Fort R. Zemel Roger C. Grosse MoMe 172 28 0 22 Apr 2021
Multiple Instance Captioning: Learning Representations from Histopathology Textbooks and Articles Jevgenij Gamper Nasir M. Rajpoot 27 62 0 08 Mar 2021
Learning Neural Network Subspaces Mitchell Wortsman Maxwell Horton Carlos Guestrin Ali Farhadi Mohammad Rastegari UQCV 27 85 0 20 Feb 2021
Policy Manifold Search for Improving Diversity-based Neuroevolution Nemanja Rakićević Antoine Cully Petar Kormushev 29 0 0 15 Dec 2020
Improving Neural Network Training in Low Dimensional Random Bases Frithjof Gressmann Zach Eaton-Rosen Carlo Luschi 30 28 0 09 Nov 2020
Procrustes: a Dataflow and Accelerator for Sparse Deep Neural Network Training Dingqing Yang Amin Ghasemazar X. Ren Maximilian Golub G. Lemieux Mieszko Lis 22 48 0 23 Sep 2020
It's Hard for Neural Networks To Learn the Game of Life Jacob Mitchell Springer Garrett Kenyon 27 21 0 03 Sep 2020
Graph Structure of Neural Networks Jiaxuan You J. Leskovec Kaiming He Saining Xie GNN 27 137 0 13 Jul 2020
GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding Dmitry Lepikhin HyoukJoong Lee Yuanzhong Xu Dehao Chen Orhan Firat Yanping Huang M. Krikun Noam M. Shazeer Zhehuai Chen MoE 43 1,116 0 30 Jun 2020
Measuring Dataset Granularity Huayu Chen Zeqi Gu D. Mahajan Laurens van der Maaten Serge J. Belongie Ser-Nam Lim 29 13 0 21 Dec 2019
Deep Ensembles: A Loss Landscape Perspective Stanislav Fort Huiyi Hu Balaji Lakshminarayanan OOD UQCV 29 619 0 05 Dec 2019
Emergent properties of the local geometry of neural loss landscapes Stanislav Fort Surya Ganguli 14 50 0 14 Oct 2019
Soft-Label Dataset Distillation and Text Dataset Distillation Ilia Sucholutsky Matthias Schonlau DD 33 132 0 06 Oct 2019
A deep-learning-based surrogate model for data assimilation in dynamic subsurface flow problems Meng Tang Yimin Liu L. Durlofsky AI4CE 32 257 0 16 Aug 2019
Multi-task Self-Supervised Learning for Human Activity Detection Aaqib Saeed T. Ozcelebi J. Lukkien SSL 23 270 0 27 Jul 2019
Subspace Inference for Bayesian Deep Learning Pavel Izmailov Wesley J. Maddox Polina Kirichenko T. Garipov Dmitry Vetrov A. Wilson UQCV BDL 38 143 0 17 Jul 2019
What does it mean to understand a neural network? Timothy Lillicrap Konrad Paul Kording 18 42 0 15 Jul 2019
Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks Ziang Yan Yiwen Guo Changshui Zhang AAML 30 110 0 11 Jun 2019
Weight Agnostic Neural Networks Adam Gaier David R Ha OOD 38 239 0 11 Jun 2019
Spectral Metric for Dataset Complexity Assessment Frederic Branchaud-Charron Andrew Achkar Pierre-Marc Jodoin 23 28 0 17 May 2019
On Scalable and Efficient Computation of Large Scale Optimal Transport Yujia Xie Minshuo Chen Haoming Jiang T. Zhao H. Zha OT 16 42 0 01 May 2019
Parameter Efficient Training of Deep Convolutional Neural Networks by Dynamic Sparse Reparameterization Hesham Mostafa Xin Wang 37 307 0 15 Feb 2019
An Investigation into Neural Net Optimization via Hessian Eigenvalue Density Behrooz Ghorbani Shankar Krishnan Ying Xiao ODL 18 317 0 29 Jan 2019
Stiffness: A New Perspective on Generalization in Neural Networks Stanislav Fort Pawel Krzysztof Nowak Stanislaw Jastrzebski S. Narayanan 24 94 0 28 Jan 2019
An Empirical Study of Example Forgetting during Deep Neural Network Learning Mariya Toneva Alessandro Sordoni Rémi Tachet des Combes Adam Trischler Yoshua Bengio Geoffrey J. Gordon 46 715 0 12 Dec 2018
Agent Embeddings: A Latent Representation for Pole-Balancing Networks Oscar Chang Robert Kwiatkowski Siyuan Chen Hod Lipson 27 6 0 12 Nov 2018