Putting An End to End-to-End: Gradient-Isolated Learning of Representations

28 May 2019

Papers citing "Putting An End to End-to-End: Gradient-Isolated Learning of Representations"

44 / 44 papers shown

Title
Efficient Post-Hoc Uncertainty Calibration via Variance-Based Smoothing Fabian Denoodt José Oramas UQCV 76 0 0 19 Mar 2025
Smooth InfoMax -- Towards easier Post-Hoc interpretability Fabian Denoodt Bart de Boer José Oramas 21 2 0 23 Aug 2024
HPFF: Hierarchical Locally Supervised Learning with Patch Feature Fusion Junhao Su Chenghao He Feiyu Zhu Xiaojie Xu Dongzhi Guan Chenyang Si 56 2 0 08 Jul 2024
Masked Image Modeling as a Framework for Self-Supervised Learning across Eye Movements Robin Weiler Matthias Brucklacher C. Pennartz Sander M. Bohté 38 0 0 12 Apr 2024
FedImpro: Measuring and Improving Client Update in Federated Learning Zhenheng Tang Yonggang Zhang S. Shi Xinmei Tian Tongliang Liu Bo Han Xiaowen Chu FedML 26 13 0 10 Feb 2024
Go beyond End-to-End Training: Boosting Greedy Local Learning with Context Supply Chengting Yu Fengzhao Zhang Hanzhi Ma Aili Wang Er-ping Li 29 1 0 12 Dec 2023
Improving equilibrium propagation without weight symmetry through Jacobian homeostasis Axel Laborieux Friedemann Zenke 27 7 0 05 Sep 2023
MOLE: MOdular Learning FramEwork via Mutual Information Maximization Tianchao Li Yulong Pei 33 0 0 15 Aug 2023
Synaptic Plasticity Models and Bio-Inspired Unsupervised Deep Learning: A Survey Gabriele Lagani Fabrizio Falchi Claudio Gennaro Giuseppe Amato AAML 43 6 0 30 Jul 2023
Can Forward Gradient Match Backpropagation? Louis Fournier Stéphane Rivaud Eugene Belilovsky Michael Eickenberg Edouard Oyallon 19 16 0 12 Jun 2023
A General Framework for Interpretable Neural Learning based on Local Information-Theoretic Goal Functions Abdullah Makkeh Marcel Graetz Andreas C. Schneider David A. Ehrlich V. Priesemann Michael Wibral 44 1 0 03 Jun 2023
Aggregating Capacity in FL through Successive Layer Training for Computationally-Constrained Devices Kilian Pfeiffer R. Khalili J. Henkel FedML 50 5 0 26 May 2023
Block-local learning with probabilistic latent representations David Kappel Khaleelulla Khan Nazeer Cabrel Teguemne Fokam Christian Mayr Anand Subramoney 26 4 0 24 May 2023
The Forward-Forward Algorithm: Some Preliminary Investigations Geoffrey E. Hinton 27 260 0 27 Dec 2022
Homomorphic Self-Supervised Learning Thomas Anderson Keller Xavier Suau Luca Zappella SSL 19 2 0 15 Nov 2022
Scaling Forward Gradient With Local Losses Mengye Ren Simon Kornblith Renjie Liao Geoffrey E. Hinton 81 49 0 07 Oct 2022
Block-wise Training of Residual Networks via the Minimizing Movement Scheme Skander Karkar Ibrahim Ayed Emmanuel de Bézenac Patrick Gallinari 33 1 0 03 Oct 2022
Hebbian Deep Learning Without Feedback Adrien Journé Hector Garcia Rodriguez Qinghai Guo Timoleon Moraitis AAML 31 49 0 23 Sep 2022
Biologically Plausible Training of Deep Neural Networks Using a Top-down Credit Assignment Network Jian-Hui Chen Cheng-Lin Liu Zuoren Wang 26 0 0 01 Aug 2022
Short-Term Plasticity Neurons Learning to Learn and Forget Hector Garcia Rodriguez Qinghai Guo Timoleon Moraitis 18 12 0 28 Jun 2022
Automated Cancer Subtyping via Vector Quantization Mutual Information Maximization Zheng Chen Lingwei Zhu Ziwei Yang Takashi Matsubara 24 7 0 22 Jun 2022
Production federated keyword spotting via distillation, filtering, and joint federated-centralized training Andrew Straiton Hard Kurt Partridge Neng Chen S. Augenstein Aishanee Shah ... Sara Ng Jessica Nguyen Ignacio López Moreno Rajiv Mathews F. Beaufays FedML 24 14 0 11 Apr 2022
Deep Layer-wise Networks Have Closed-Form Weights Chieh-Tsai Wu A. Masoomi Arthur Gretton Jennifer Dy 29 3 0 01 Feb 2022
Progressive Stage-wise Learning for Unsupervised Feature Representation Enhancement Zefan Li Chenxi Liu Alan Yuille Bingbing Ni Wenjun Zhang Wen Gao SSL 16 5 0 10 Jun 2021
Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding S. Tonekaboni Danny Eytan Anna Goldenberg CML SSL AI4TS 25 284 0 01 Jun 2021
A Good Image Generator Is What You Need for High-Resolution Video Synthesis Yu Tian Jian Ren Menglei Chai Kyle Olszewski Xi Peng Dimitris N. Metaxas Sergey Tulyakov VGen 65 183 0 30 Apr 2021
Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction Bohan Wu Suraj Nair Roberto Martin-Martin Li Fei-Fei Chelsea Finn DRL 27 99 0 06 Mar 2021
Training Deep Architectures Without End-to-End Backpropagation: A Survey on the Provably Optimal Methods Shiyu Duan José C. Príncipe MQ 38 3 0 09 Jan 2021
Demystifying Deep Neural Networks Through Interpretation: A Survey Giang Dao Minwoo Lee FaML FAtt 22 1 0 13 Dec 2020
Self Normalizing Flows Thomas Anderson Keller Jorn W. T. Peters P. Jaini Emiel Hoogeboom Patrick Forré Max Welling 30 14 0 14 Nov 2020
ConFuse: Convolutional Transform Learning Fusion Framework For Multi-Channel Data Analysis Pooja Gupta Jyoti Maggu A. Majumdar Émilie Chouzenoux Giovanni Chierchia AI4TS 25 2 0 09 Nov 2020
Local plasticity rules can learn deep representations using self-supervised contrastive predictions Bernd Illing Jean-Paul Ventura G. Bellec W. Gerstner SSL DRL 59 69 0 16 Oct 2020
Why Layer-Wise Learning is Hard to Scale-up and a Possible Solution via Accelerated Downsampling Wenchi Ma Miao Yu Kaidong Li Guanghui Wang 14 5 0 15 Oct 2020
Contrastive Representation Learning: A Framework and Review Phúc H. Lê Khắc Graham Healy Alan F. Smeaton SSL AI4TS 184 687 0 10 Oct 2020
Hard Negative Mixing for Contrastive Learning Yannis Kalantidis Mert Bulent Sariyildiz Noé Pion Philippe Weinzaepfel Diane Larlus SSL 53 628 0 02 Oct 2020
Contrastive Learning for Unpaired Image-to-Image Translation Taesung Park Alexei A. Efros Richard Y. Zhang Jun-Yan Zhu SSL 36 1,192 0 30 Jul 2020
Data Augmenting Contrastive Learning of Speech Representations in the Time Domain Eugene Kharitonov M. Rivière Gabriel Synnaeve Lior Wolf Pierre-Emmanuel Mazaré Matthijs Douze Emmanuel Dupoux 28 117 0 02 Jul 2020
Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures Julien Launay Iacopo Poli Franccois Boniface Florent Krzakala 41 63 0 23 Jun 2020
Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks Roman Pogodin P. Latham 24 34 0 12 Jun 2020
Gaussian Gated Linear Networks David Budden Adam H. Marblestone Eren Sezener Tor Lattimore Greg Wayne J. Veness BDL AI4CE 24 12 0 10 Jun 2020
Modularizing Deep Learning via Pairwise Learning With Kernels Shiyu Duan Shujian Yu José C. Príncipe MoMe 27 20 0 12 May 2020
Convergence of End-to-End Training in Deep Unsupervised Contrastive Learning Zixin Wen SSL 21 2 0 17 Feb 2020
Discriminative Clustering with Representation Learning with any Ratio of Labeled to Unlabeled Data Corinne Jones Vincent Roulet Zaïd Harchaoui 36 1 0 30 Dec 2019
Gated Linear Networks William H. Guss Tor Lattimore David Budden Avishkar Bhoopchand Christopher Mattern ... Ruslan Salakhutdinov Jianan Wang Peter Toth Simon Schmitt Marcus Hutter AI4CE 18 40 0 30 Sep 2019