Analyzing and Improving Representations with the Soft Nearest Neighbor Loss

5 February 2019

Papers citing "Analyzing and Improving Representations with the Soft Nearest Neighbor Loss"

46 / 96 papers shown

Title
On the Difficulty of Defending Self-Supervised Learning against Model Extraction Adam Dziedzic Nikita Dhawan Muhammad Ahmad Kaleem Jonas Guan Nicolas Papernot MIACV 110 26 0 16 May 2022
Real-centric Consistency Learning for Deepfake Detection Ruiqi Zha Z. Lian Qianmu Li Siqi Gu 46 1 0 15 May 2022
Supervised Contrastive CSI Representation Learning for Massive MIMO Positioning Junquan Deng Wei Shi Jianzhao Zhang Xianyu Zhang Chuan Zhang SSL 15 12 0 27 Apr 2022
Empirical Evaluation and Theoretical Analysis for Representation Learning: A Survey Kento Nozawa Issei Sato AI4TS 139 5 0 18 Apr 2022
Examining the Proximity of Adversarial Examples to Class Manifolds in Deep Networks Stefan Pócos Iveta Becková Igor Farkas AAML 39 2 0 12 Apr 2022
AutoProtoNet: Interpretability for Prototypical Networks Pedro Sandoval Segura W. Lawson 35 2 0 02 Apr 2022
Logit Normalization for Long-tail Object Detection Liang Zhao Yao Teng Limin Wang 82 11 0 31 Mar 2022
Incremental Few-Shot Learning via Implanting and Compressing Yiting Li H. Zhu Xijia Feng Zilong Cheng Jun Ma Cheng Xiang P. Vadakkepat T. Lee CLL VLM 85 2 0 19 Mar 2022
Contrastive Boundary Learning for Point Cloud Segmentation Liyao Tang Yibing Zhan Zhe Chen Baosheng Yu Dacheng Tao 3DPC 96 105 0 10 Mar 2022
Learning Debiased and Disentangled Representations for Semantic Segmentation Sanghyeok Chu Dongwan Kim Bohyung Han 70 22 0 31 Oct 2021
A Closer Look at Few-Shot Video Classification: A New Baseline and Benchmark Zhenxi Zhu Limin Wang Sheng Guo Gangshan Wu 145 32 0 24 Oct 2021
ReMeDi: Resources for Multi-domain, Multi-service, Medical Dialogues Guojun Yan Jiahuan Pei Pengjie Ren Zhaochun Ren Xin Xin Huasheng Liang Maarten de Rijke Zhumin Chen 93 22 0 01 Sep 2021
Text Classification and Clustering with Annealing Soft Nearest Neighbor Loss Abien Fred Agarap DRL 20 0 0 23 Jul 2021
On the Challenges of Open World Recognitionunder Shifting Visual Domains Dario Fontanel Fabio Cermelli Massimiliano Mancini Barbara Caputo 66 1 0 09 Jul 2021
ASK: Adversarial Soft k-Nearest Neighbor Attack and Defense Ren Wang Tianqi Chen Philip Yao Sijia Liu I. Rajapakse Alfred Hero AAML OOD 59 5 0 27 Jun 2021
Privacy Inference Attacks and Defenses in Cloud-based Deep Neural Network: A Survey Xiaoyu Zhang Chao Chen Yi Xie Xiaofeng Chen Jun Zhang Yang Xiang FedML 58 7 0 13 May 2021
With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual Representations Debidatta Dwibedi Y. Aytar Jonathan Tompson P. Sermanet Andrew Zisserman SSL 265 467 0 29 Apr 2021
Back to Square One: Superhuman Performance in Chutes and Ladders Through Deep Neural Networks and Tree Search Dylan R. Ashley Anssi Kanervisto Brendan Bennett 70 2 0 01 Apr 2021
SoundCLR: Contrastive Learning of Representations For Improved Environmental Sound Classification Alireza Nasiri Jianjun Hu 56 18 0 02 Mar 2021
Fool Me Once: Robust Selective Segmentation via Out-of-Distribution Detection with Contrastive Learning David S. W. Williams Matthew Gadd D. Martini Paul Newman OODD 57 13 0 01 Mar 2021
Dissecting Supervised Contrastive Learning Florian Graf Christoph Hofer Marc Niethammer Roland Kwitt SSL 164 77 0 17 Feb 2021
Adversarial Poisoning Attacks and Defense for General Multi-Class Models Based On Synthetic Reduced Nearest Neighbors Pooya Tavallali Vahid Behzadan P. Tavallali Mukesh Singhal AAML 38 3 0 11 Feb 2021
Neural-based Modeling for Performance Tuning of Spark Data Analytics Khaled Zaouk Fei Song Chenghao Lyu Y. Diao 19 2 0 20 Jan 2021
On Episodes, Prototypical Networks, and Few-shot Learning Steinar Laenen Luca Bertinetto 99 99 0 17 Dec 2020
Towards Recognizing New Semantic Concepts in New Visual Domains Massimiliano Mancini OOD 141 0 0 16 Dec 2020
Discovering alignment relations with Graph Convolutional Networks: a biomedical case study Pierre Monnin Chedy Raïssi A. Napoli Adrien Coulet GNN 75 12 0 11 Nov 2020
Why Do Better Loss Functions Lead to Less Transferable Features? Simon Kornblith Ting-Li Chen Honglak Lee Mohammad Norouzi FaML 121 92 0 30 Oct 2020
A Systematic Review on Model Watermarking for Neural Networks Franziska Boenisch AAML 87 70 0 25 Sep 2020
$σ^2$ R Loss: a Weighted Loss by Multiplicative Factors using Sigmoidal Functions Riccardo La Grassa I. Gallo Nicola Landro 27 0 0 18 Sep 2020
Adversarial Training Reduces Information and Improves Transferability M. Terzi Alessandro Achille Marco Maggipinto Gian Antonio Susto AAML 106 23 0 22 Jul 2020
Hierarchical nucleation in deep neural networks Diego Doimo Aldo Glielmo A. Ansuini Alessandro Laio BDL AI4CE 57 32 0 07 Jul 2020
Depth Uncertainty in Neural Networks Javier Antorán J. Allingham José Miguel Hernández-Lobato UQCV OOD BDL 112 103 0 15 Jun 2020
Calibrated neighborhood aware confidence measure for deep metric learning Maryna Karpusha Sunghee Yun István Fehérvári UQCV FedML 126 2 0 08 Jun 2020
Improving k-Means Clustering Performance with Disentangled Internal Representations Abien Fred Agarap A. Azcarraga DRL 41 10 0 05 Jun 2020
Transferable Perturbations of Deep Feature Distributions Nathan Inkawhich Kevin J. Liang Lawrence Carin Yiran Chen AAML 73 87 0 27 Apr 2020
Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers Loc Truong Chace Jones Brian Hutchinson Andrew August Brenda Praggastis Robert J. Jasper Nicole Nichols Aaron Tuor AAML 68 52 0 24 Apr 2020
Supervised Contrastive Learning Prannay Khosla Piotr Teterwak Chen Wang Aaron Sarna Yonglong Tian Phillip Isola Aaron Maschinot Ce Liu Dilip Krishnan SSL 214 4,604 0 23 Apr 2020
Boosting Deep Open World Recognition by Clustering Dario Fontanel Fabio Cermelli Massimiliano Mancini Samuel Rota Buló Elisa Ricci Barbara Caputo 81 21 0 20 Apr 2020
Entangled Watermarks as a Defense against Model Extraction Hengrui Jia Christopher A. Choquette-Choo Varun Chandrasekaran Nicolas Papernot WaLM AAML 96 222 0 27 Feb 2020
Unraveling Meta-Learning: Understanding Feature Representations for Few-Shot Tasks Micah Goldblum Steven Reich Liam H. Fowl Renkun Ni Valeriia Cherepanova Tom Goldstein SSL OffRL 109 75 0 17 Feb 2020
Analysing Deep Reinforcement Learning Agents Trained with Domain Randomisation Tianhong Dai Kai Arulkumaran Tamara Gerbert Samyakh Tukra Feryal M. P. Behbahani Anil Anthony Bharath 87 28 0 18 Dec 2019
Deep k-NN Defense against Clean-label Data Poisoning Attacks Neehar Peri Neal Gupta Wenjie Huang Liam H. Fowl Chen Zhu Soheil Feizi Tom Goldstein John P. Dickerson AAML 59 6 0 29 Sep 2019
A Closer Look at Domain Shift for Deep Learning in Histopathology Karin Stacke Gabriel Eilertsen Jonas Unger Claes Lundström OOD 66 62 0 25 Sep 2019
A Baseline for Few-Shot Image Classification Guneet Singh Dhillon Pratik Chaudhari Avinash Ravichandran Stefano Soatto 134 584 0 06 Sep 2019
Defending Against Adversarial Examples with K-Nearest Neighbor Chawin Sitawarin David Wagner AAML 91 29 0 23 Jun 2019
Introducing Graph Smoothness Loss for Training Deep Learning Architectures Myriam Bontonou Carlos Lassance G. B. Hacene Vincent Gripon Jian Tang Antonio Ortega 59 18 0 01 May 2019