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Classification

15,805 papers

Papers per year

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Papers

Confidence-Aware Learning for Deep Neural Networks ICML 2020
Consistent Estimators for Learning to Defer to an Expert ICML 2020
Graph Homomorphism Convolution ICML 2020
Robust Bayesian Classification Using An Optimistic Score Ratio ICML 2020
LP-SparseMAP: Differentiable Relaxed Optimization for Sparse Structured Prediction ICML 2020
Supervised learning: no loss no cry ICML 2020
Consistent Structured Prediction with Max-Min Margin Markov Networks ICML 2020
IPBoost – Non-Convex Boosting via Integer Programming ICML 2020
Transparency Promotion with Model-Agnostic Linear Competitors ICML 2020
Optimistic Bounds for Multi-output Learning ICML 2020
Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation ICML 2020
Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning ICML 2020
Predicting Choice with Set-Dependent Aggregation ICML 2020
Bounding the fairness and accuracy of classifiers from population statistics ICML 2020
The Performance Analysis of Generalized Margin Maximizers on Separable Data ICML 2020
Evaluating Machine Accuracy on ImageNet ICML 2020
Extreme Multi-label Classification from Aggregated Labels ICML 2020
Multiclass Neural Network Minimization via Tropical Newton Polytope Approximation ICML 2020
Which Tasks Should Be Learned Together in Multi-task Learning? ICML 2020
Task Understanding from Confusing Multi-task Data ICML 2020
Choice Set Optimization Under Discrete Choice Models of Group Decisions ICML 2020
From ImageNet to Image Classification: Contextualizing Progress on Benchmarks ICML 2020
Uncertainty Estimation Using a Single Deep Deterministic Neural Network ICML 2020
Born-Again Tree Ensembles ICML 2020
Logistic Regression for Massive Data with Rare Events ICML 2020