Training Deep Neural Networks via Direct Loss Minimization

19 November 2015

Papers citing "Training Deep Neural Networks via Direct Loss Minimization"

21 / 21 papers shown

Title
LPGD: A General Framework for Backpropagation through Embedded Optimization Layers Anselm Paulus Georg Martius Vít Musil AI4CE 55 1 0 08 Jul 2024
An Invitation to Deep Reinforcement Learning Bernhard Jaeger Andreas Geiger OffRL OOD 78 5 0 13 Dec 2023
Tuning computer vision models with task rewards André Susano Pinto Alexander Kolesnikov Yuge Shi Lucas Beyer Xiaohua Zhai VLM 27 40 0 16 Feb 2023
Teal: Learning-Accelerated Optimization of WAN Traffic Engineering Zhiying Xu Francis Y. Yan Rachee Singh Justin T. Chiu Alexander M. Rush Minlan Yu 23 44 0 25 Oct 2022
Exploring the Algorithm-Dependent Generalization of AUPRC Optimization with List Stability Peisong Wen Qianqian Xu Zhiyong Yang Yuan He Qingming Huang 53 10 0 27 Sep 2022
Theseus: A Library for Differentiable Nonlinear Optimization Luis Pineda Taosha Fan Maurizio Monge S. Venkataraman Paloma Sodhi ... Austin S. Wang Stuart Anderson Jing Dong Brandon Amos Mustafa Mukadam 34 76 0 19 Jul 2022
Momentum Accelerates the Convergence of Stochastic AUPRC Maximization Guanghui Wang Minghao Yang Lijun Zhang Tianbao Yang 41 22 0 02 Jul 2021
Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence Qi Qi Youzhi Luo Zhao Xu Shuiwang Ji Tianbao Yang 18 59 0 18 Apr 2021
AP-Loss for Accurate One-Stage Object Detection Kean Chen Weiyao Lin Jianguo Li John See Ji Wang Junni Zou ObjD 22 66 0 17 Aug 2020
A Unified Framework of Surrogate Loss by Refactoring and Interpolation Lanlan Liu Mingzhe Wang Jia Deng 22 8 0 27 Jul 2020
Weakly Supervised Instance Segmentation by Learning Annotation Consistent Instances Aditya Arun C. V. Jawahar M. P. Kumar ISeg 29 57 0 18 Jul 2020
Imbalance Problems in Object Detection: A Review Kemal Oksuz Baris Can Cam Sinan Kalkan Emre Akbas ObjD 25 458 0 31 Aug 2019
Learning with Average Precision: Training Image Retrieval with a Listwise Loss Jérôme Revaud Jon Almazán Rafael Sampaio de Rezende César Roberto de Souza VLM 31 368 0 18 Jun 2019
Learning Surrogate Losses Josif Grabocka Randolf Scholz Lars Schmidt-Thieme 27 41 0 24 May 2019
Deep Structured Prediction with Nonlinear Output Transformations Colin Graber Ofer Meshi A. Schwing BDL 23 25 0 01 Nov 2018
Learning Discriminators as Energy Networks in Adversarial Learning Pingbo Pan Yan Yan Tianbao Yang Yi Yang 11 1 0 02 Oct 2018
Optimizing Non-decomposable Measures with Deep Networks Amartya Sanyal Pawan Kumar Purushottam Kar Sanjay Chawla Fabrizio Sebastiani 28 26 0 31 Jan 2018
Hashing as Tie-Aware Learning to Rank Kun He Fatih Çakir Sarah Adel Bargal Stan Sclaroff FedML 24 84 0 23 May 2017
Deep Value Networks Learn to Evaluate and Iteratively Refine Structured Outputs Michael Gygli Mohammad Norouzi A. Angelova TDI 24 68 0 13 Mar 2017
End-to-end training of object class detectors for mean average precision Paul Henderson V. Ferrari ObjD 33 259 0 12 Jul 2016
Efficient Optimization for Rank-based Loss Functions Pritish Mohapatra Michal Rolínek C. V. Jawahar V. Kolmogorov M. P. Kumar 21 38 0 27 Apr 2016