conftrace_
← Core Methods
Machine Learning › Core Methods ›

Classification

15,805 papers

Papers per year

2
26
134
262
1678
1390
'00
'05
'10
'15
'20
'25

Papers

Exploiting the Surrogate Gap in Online Multiclass Classification NIPS 2020
Coherent Hierarchical Multi-Label Classification Networks NIPS 2020
Field-wise Learning for Multi-field Categorical Data NIPS 2020
Unsupervised Semantic Aggregation and Deformable Template Matching for Semi-Supervised Learning NIPS 2020
Optimal Best-arm Identification in Linear Bandits NIPS 2020
An Unbiased Risk Estimator for Learning with Augmented Classes NIPS 2020
Provably Consistent Partial-Label Learning NIPS 2020
Fair Performance Metric Elicitation NIPS 2020
SnapBoost: A Heterogeneous Boosting Machine NIPS 2020
Fairness constraints can help exact inference in structured prediction NIPS 2020
Joints in Random Forests NIPS 2020
Coresets for Robust Training of Deep Neural Networks against Noisy Labels NIPS 2020
Hierarchical Granularity Transfer Learning NIPS 2020
Adaptive Learned Bloom Filter (Ada-BF): Efficient Utilization of the Classifier with Application to Real-Time Information Filtering on the Web NIPS 2020
Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization NIPS 2020
On Convergence of Nearest Neighbor Classifiers over Feature Transformations NIPS 2020
Learning from Positive and Unlabeled Data with Arbitrary Positive Shift NIPS 2020
Exemplar Guided Active Learning NIPS 2020
Steering Distortions to Preserve Classes and Neighbors in Supervised Dimensionality Reduction NIPS 2020
Instance-wise Feature Grouping NIPS 2020
Intra Order-preserving Functions for Calibration of Multi-Class Neural Networks NIPS 2020
Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs under Gaussian Marginals NIPS 2020
Fast Adversarial Robustness Certification of Nearest Prototype Classifiers for Arbitrary Seminorms NIPS 2020
The Potts-Ising model for discrete multivariate data NIPS 2020
Private Learning of Halfspaces: Simplifying the Construction and Reducing the Sample Complexity NIPS 2020