conftrace_

loss function

462 papers

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Co-occurring keywords

neural network (6616) deep neural network (1803) object detection (2762) neural network optimization (1293) class imbalance (555) convolutional neural network (4226) semantic segmentation (3186) multi-label classification (1009) deep learning (2118) gradient descent (1144)

Papers

L4: Practical loss-based stepsize adaptation for deep learning NIPS 2018
Convex Elicitation of Continuous Properties NIPS 2018
Dimensionality-Driven Learning with Noisy Labels ICML 2018
Mean-Variance Loss for Deep Age Estimation From a Face CVPR 2018
Token-level and sequence-level loss smoothing for RNN language models ACL 2018
Essentially No Barriers in Neural Network Energy Landscape ICML 2018
Improving Pairwise Ranking for Multi-Label Image Classification CVPR 2017
Sharp Minima Can Generalize For Deep Nets ICML 2017
Soft-DTW: a Differentiable Loss Function for Time-Series ICML 2017
Don’t understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures ACL 2017
Learning from Complementary Labels NIPS 2017
Top-Rank Enhanced Listwise Optimization for Statistical Machine Translation CONLL 2017
Noise-Blind Image Deblurring CVPR 2017
Value-Aware Loss Function for Model-based Reinforcement Learning AISTATS 2017
On Separability of Loss Functions, and Revisiting Discriminative Vs Generative Models NIPS 2017
Improving RANSAC-Based Segmentation Through CNN Encapsulation CVPR 2017
Loss Max-Pooling for Semantic Image Segmentation CVPR 2017
Composite Multiclass Losses JMLR 2016
On the Characterization of a Class of Fisher-Consistent Loss Functions and its Application to Boosting JMLR 2016
Feature-Level Domain Adaptation JMLR 2016
Optimal Black-Box Reductions Between Optimization Objectives NIPS 2016
Open Problem: Property Elicitation and Elicitation Complexity COLT 2016
Loss Functions for Top-k Error: Analysis and Insights CVPR 2016
End-To-End Saliency Mapping via Probability Distribution Prediction CVPR 2016
Optimal Binary Classifier Aggregation for General Losses NIPS 2016