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Loss Functions

1162 directly classified papers

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Papers

Stochastic Loss Function AAAI 2020
Deep Learning on Small Datasets without Pre-Training using Cosine Loss WACV 2020
Class-Weighted Classification: Trade-offs and Robust Approaches ICML 2020
Convex Calibrated Surrogates for the Multi-Label F-Measure ICML 2020
Using a Penalty-based Loss Re-estimation Method to Improve Implicit Discourse Relation Classification COLING 2020
Augmenting NLP models using Latent Feature Interpolations COLING 2020
Learn with Noisy Data via Unsupervised Loss Correction for Weakly Supervised Reading Comprehension COLING 2020
Exploring Question-Specific Rewards for Generating Deep Questions COLING 2020
StochasticRank: Global Optimization of Scale-Free Discrete Functions ICML 2020
Confidence-Aware Learning for Deep Neural Networks ICML 2020
Implicit Geometric Regularization for Learning Shapes ICML 2020
Loss Function Search for Face Recognition ICML 2020
Discount Factor as a Regularizer in Reinforcement Learning ICML 2020
Robust Learning with the Hilbert-Schmidt Independence Criterion ICML 2020
Parameterized Rate-Distortion Stochastic Encoder ICML 2020
Supervised learning: no loss no cry ICML 2020
Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels ICML 2020
Does label smoothing mitigate label noise? ICML 2020
Normalized Loss Functions for Deep Learning with Noisy Labels ICML 2020
Obtaining Adjustable Regularization for Free via Iterate Averaging ICML 2020
Individual Calibration with Randomized Forecasting ICML 2020
Aligned Cross Entropy for Non-Autoregressive Machine Translation ICML 2020
Curvature-corrected learning dynamics in deep neural networks ICML 2020
State Sequence Pooling Training of Acoustic Models for Keyword Spotting INTERSPEECH 2020
Re-Weighted Interval Loss for Handling Data Imbalance Problem of End-to-End Keyword Spotting INTERSPEECH 2020