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

Boosting with Multiple Sources NIPS 2021
Can Less be More? When Increasing-to-Balancing Label Noise Rates Considered Beneficial NIPS 2021
Handling Long-tailed Feature Distribution in AdderNets NIPS 2021
Structure learning in polynomial time: Greedy algorithms, Bregman information, and exponential families NIPS 2021
Revisiting Deep Learning Models for Tabular Data NIPS 2021
Label-Imbalanced and Group-Sensitive Classification under Overparameterization NIPS 2021
Formalizing Generalization and Adversarial Robustness of Neural Networks to Weight Perturbations NIPS 2021
Boost Neural Networks by Checkpoints NIPS 2021
Nonuniform Negative Sampling and Log Odds Correction with Rare Events Data NIPS 2021
Skipping the Frame-Level: Event-Based Piano Transcription With Neural Semi-CRFs NIPS 2021
Explanation-based Data Augmentation for Image Classification NIPS 2021
The Effect of the Intrinsic Dimension on the Generalization of Quadratic Classifiers NIPS 2021
An online passive-aggressive algorithm for difference-of-squares classification NIPS 2021
Improved Learning Rates of a Functional Lasso-type SVM with Sparse Multi-Kernel Representation NIPS 2021
Learning to Predict Trustworthiness with Steep Slope Loss NIPS 2021
Perceptual Score: What Data Modalities Does Your Model Perceive? NIPS 2021
Beyond the Signs: Nonparametric Tensor Completion via Sign Series NIPS 2021
Boosted CVaR Classification NIPS 2021
Unifying lower bounds on prediction dimension of convex surrogates NIPS 2021
Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits NIPS 2021
Calibrating Predictions to Decisions: A Novel Approach to Multi-Class Calibration NIPS 2021
Online Active Learning with Surrogate Loss Functions NIPS 2021
Probabilistic Margins for Instance Reweighting in Adversarial Training NIPS 2021
Active Learning of Convex Halfspaces on Graphs NIPS 2021
Interpolation can hurt robust generalization even when there is no noise NIPS 2021