Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: On the Consistency of Top-k Surrogate Losses
Smooth Loss Functions for Deep Top-k Classification
Reconstruction of training samples from loss functions
Functional Frank-Wolfe Boosting for General Loss Functions
Exploring loss function topology with cyclical learning rates
Bias Reduction and Metric Learning for Nearest-Neighbor Estimation of Kullback-Leibler Divergence
Communication Efficient Coresets for Empirical Loss Minimization
Analyzing and Improving Representations with the Soft Nearest Neighbor Loss
Surrogate-Based Methods
Online regularized learning with pairwise loss functions
Optimal Binary Classifier Aggregation for General Losses
The Loss Surfaces of Multilayer Networks
A General and Adaptive Robust Loss Function
DiSCO: Distributed Optimization for Self-Concordant Empirical Loss
A New Smooth Approximation to the Zero One Loss with a Probabilistic Interpretation
Improving top-N recommendation with heterogeneous loss
Loss-Sensitive Generative Adversarial Networks on Lipschitz Densities
A Survey of Discretization Techniques: Taxonomy and Empirical Analysis in Supervised Learning
Online pairwise learning algorithms with convex loss functions
Bias plus variance decomposition for zero-one loss functions
Impact of Surrogate Assessments on High-Recall Retrieval
AppFusion: Interactive Appearance Acquisition Using a Kinect Sensor
Classification of ECoG motor imagery tasks based on CSP and SVM
A Hybrid model of Neural Network Approach for Speaker independent Word Recognition
Dry electrodes for electrocardiography.
Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers