Learning with Average Top-k Loss

24 May 2017

Papers citing "Learning with Average Top-k Loss"

50 / 61 papers shown

Title
TopoFR: A Closer Look at Topology Alignment on Face Recognition Jun Dan Lingjuan Lyu Jiankang Deng Haoyu Xie Siyuan Li Baigui Sun Shan Luo CVBM 42 4 0 14 Oct 2024
Communication-Efficient Federated Group Distributionally Robust Optimization Zhishuai Guo Tianbao Yang FedML 35 0 0 08 Oct 2024
Improved Diversity-Promoting Collaborative Metric Learning for Recommendation Shilong Bao Qianqian Xu Zhiyong Yang Yuan He Xiaochun Cao Qingming Huang 55 5 0 02 Sep 2024
SOREL: A Stochastic Algorithm for Spectral Risks Minimization Yuze Ge Rujun Jiang 40 0 0 19 Jul 2024
A Survey of Deep Long-Tail Classification Advancements Charika De Alvis Suranga Seneviratne 39 1 0 24 Apr 2024
Lower-Left Partial AUC: An Effective and Efficient Optimization Metric for Recommendation Wentao Shi Chenxu Wang Fuli Feng Yang Zhang Wenjie Wang Junkang Wu Xiangnan He 54 1 0 29 Feb 2024
Understanding the Training Speedup from Sampling with Approximate Losses Rudrajit Das Xi Chen Bertram Ieong Parikshit Bansal Sujay Sanghavi 24 0 0 10 Feb 2024
A Simple Yet Effective Strategy to Robustify the Meta Learning Paradigm Qi Wang Yiqin Lv Yanghe Feng Zheng Xie Jincai Huang 27 9 0 01 Oct 2023
TransFace: Calibrating Transformer Training for Face Recognition from a Data-Centric Perspective Jun Dan Yang Liu Haoyu Xie Jiankang Deng H. Xie Xuansong Xie Baigui Sun ViT 28 21 0 20 Aug 2023
When Measures are Unreliable: Imperceptible Adversarial Perturbations toward Top- $k$ Multi-Label Learning Yuchen Sun Qianqian Xu Zitai Wang Qingming Huang AAML 30 1 0 27 Jul 2023
Stepdown SLOPE for Controlled Feature Selection Jingxuan Liang Hao Chen Xuelin Zhang Weifu Li Xin Tang 90 0 0 21 Feb 2023
Revisiting adversarial training for the worst-performing class Thomas Pethick Grigorios G. Chrysos V. Cevher 29 6 0 17 Feb 2023
Multi-site Organ Segmentation with Federated Partial Supervision and Site Adaptation Peng Liu Mengke Sun S. Kevin Zhou OOD 29 5 0 08 Feb 2023
Stochastic Optimization for Spectral Risk Measures Ronak R. Mehta Vincent Roulet Krishna Pillutla Lang Liu Zaïd Harchaoui 32 6 0 10 Dec 2022
An Efficient Stochastic Algorithm for Decentralized Nonconvex-Strongly-Concave Minimax Optimization Le‐Yu Chen Haishan Ye Luo Luo 73 5 0 05 Dec 2022
Minority-Oriented Vicinity Expansion with Attentive Aggregation for Video Long-Tailed Recognition WonJun Moon Hyun Seok Seong Jae-Pil Heo VLM 17 5 0 24 Nov 2022
MAPPING: Model Average with Post-processing for Stroke Lesion Segmentation Jiayu Huo Liyun Chen Yang Liu Maxence Boels Alejandro Granados Sebastien Ourselin Rachel Sparks 25 11 0 11 Nov 2022
K-SAM: Sharpness-Aware Minimization at the Speed of SGD Renkun Ni Ping Yeh-Chiang Jonas Geiping Micah Goldblum A. Wilson Tom Goldstein 26 8 0 23 Oct 2022
Asymptotically Unbiased Instance-wise Regularized Partial AUC Optimization: Theory and Algorithm Huiyang Shao Qianqian Xu Zhiyong Yang Shilong Bao Qingming Huang 21 4 0 08 Oct 2022
Adaptive Ranking-based Sample Selection for Weakly Supervised Class-imbalanced Text Classification Linxin Song Jieyu Zhang Tianxiang Yang M. Goto 23 3 0 06 Oct 2022
Class-Level Logit Perturbation Mengyang Li Fengguang Su O. Wu Tianjin University AAML 39 4 0 13 Sep 2022
Tailoring to the Tails: Risk Measures for Fine-Grained Tail Sensitivity Christian Frohlich Robert C. Williamson 22 5 0 05 Aug 2022
Rank-based Decomposable Losses in Machine Learning: A Survey Shu Hu Xin Wang Siwei Lyu 40 32 0 18 Jul 2022
Differentiable Top-k Classification Learning Felix Petersen Hilde Kuehne Christian Borgelt Oliver Deussen 61 28 0 15 Jun 2022
Solving The Long-Tailed Problem via Intra- and Inter-Category Balance Renhui Zhang Tiancheng Lin Rui Zhang Yi Xu 27 4 0 20 Apr 2022
Distributionally Robust Models with Parametric Likelihood Ratios Paul Michel Tatsunori Hashimoto Graham Neubig OOD 30 15 0 13 Apr 2022
Bayesian Nonparametric Submodular Video Partition for Robust Anomaly Detection Hitesh Sapkota Qi Yu 16 39 0 24 Mar 2022
Large-scale Optimization of Partial AUC in a Range of False Positive Rates Yao Yao Qihang Lin Tianbao Yang 38 16 0 03 Mar 2022
Improve Deep Image Inpainting by Emphasizing the Complexity of Missing Regions Yufeng Wang Dan Li Cong Xu Min Yang 27 0 0 13 Feb 2022
How Important is Importance Sampling for Deep Budgeted Training? Eric Arazo Diego Ortego Paul Albert Noel E. O'Connor Kevin McGuinness 23 7 0 27 Oct 2021
Deep Metric Learning with Locality Sensitive Angular Loss for Self-Correcting Source Separation of Neural Spiking Signals A. Clarke Dario Farina 11 1 0 13 Oct 2021
A Survey of Learning Criteria Going Beyond the Usual Risk Matthew J. Holland Kazuki Tanabe FaML 24 4 0 11 Oct 2021
Are Negative Samples Necessary in Entity Alignment? An Approach with High Performance, Scalability and Robustness Xin Mao Wenting Wang Yuanbin Wu Man Lan 32 26 0 11 Aug 2021
T $_k$ ML-AP: Adversarial Attacks to Top- $k$ Multi-Label Learning Shu Hu Lipeng Ke Xin Wang Siwei Lyu VLM AAML 31 34 0 31 Jul 2021
Implicit Rate-Constrained Optimization of Non-decomposable Objectives Abhishek Kumar Harikrishna Narasimhan Andrew Cotter 21 10 0 23 Jul 2021
Sum of Ranked Range Loss for Supervised Learning Shu Hu Yiming Ying Xin Wang Siwei Lyu 29 23 0 07 Jun 2021
Efficient Online-Bandit Strategies for Minimax Learning Problems Christophe Roux Elias Wirth Sebastian Pokutta Thomas Kerdreux 28 1 0 28 May 2021
Spectral risk-based learning using unbounded losses Matthew J. Holland El Mehdi Haress 24 10 0 11 May 2021
Distributionally Robust Federated Averaging Yuyang Deng Mohammad Mahdi Kamani M. Mahdavi FedML 13 140 0 25 Feb 2021
When Do Curricula Work? Xiaoxia Wu Ethan Dyer Behnam Neyshabur 33 114 0 05 Dec 2020
Coping with Label Shift via Distributionally Robust Optimisation Jiaming Zhang A. Menon Andreas Veit Srinadh Bhojanapalli Sanjiv Kumar S. Sra OOD 24 70 0 23 Oct 2020
Large-Scale Methods for Distributionally Robust Optimization Daniel Levy Y. Carmon John C. Duchi Aaron Sidford 37 204 0 12 Oct 2020
Learning by Minimizing the Sum of Ranked Range Shu Hu Yiming Ying Xin Wang Siwei Lyu 17 28 0 05 Oct 2020
Long-tail learning via logit adjustment A. Menon Sadeep Jayasumana A. S. Rawat Himanshu Jain Andreas Veit Sanjiv Kumar 65 686 0 14 Jul 2020
Geometry-Inspired Top-k Adversarial Perturbations Nurislam Tursynbek Aleksandr Petiushko Ivan Oseledets AAML 17 10 0 28 Jun 2020
Learning Bounds for Risk-sensitive Learning Jaeho Lee Sejun Park Jinwoo Shin 25 46 0 15 Jun 2020
PrimA6D: Rotational Primitive Reconstruction for Enhanced and Robust 6D Pose Estimation Myung-Hwan Jeon Ayoung Kim 13 10 0 14 Jun 2020
Doubly-stochastic mining for heterogeneous retrieval A. S. Rawat A. Menon Andreas Veit Felix X. Yu Sashank J. Reddi Sanjiv Kumar 19 5 0 23 Apr 2020
A Simple and Effective Framework for Pairwise Deep Metric Learning Qi Qi Yan Yan Xiaoyu Wang Tianbao Yang 25 26 0 24 Dec 2019
Adaptive Sampling for Stochastic Risk-Averse Learning Sebastian Curi Kfir Y. Levy Stefanie Jegelka Andreas Krause 24 52 0 28 Oct 2019