| On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition | 0 | 0.34 | 2021 |
| Adaptive and Generative Zero-Shot Learning | 0 | 0.34 | 2021 |
| SERIL: Noise Adaptive Speech Enhancement using Regularization-based Incremental Learning | 1 | 0.36 | 2020 |
| Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels | 0 | 0.34 | 2020 |
| Learning from Label Proportions with Consistency Regularization | 0 | 0.34 | 2020 |
| Cold-start Active Learning through Self-supervised Language Modeling. | 0 | 0.34 | 2020 |
| Annotation cost-sensitive active learning by tree sampling | 1 | 0.35 | 2019 |
| Attention-based Deep Tropical Cyclone Rapid Intensification Prediction | 0 | 0.34 | 2019 |
| Advances in Cost-sensitive Multiclass and Multilabel Classification | 0 | 0.34 | 2019 |
| REFUEL - Exploring Sparse Features in Deep Reinforcement Learning for Fast Disease Diagnosis. | 0 | 0.34 | 2018 |
| Compatibility Family Learning for Item Recommendation and Generation | 7 | 0.42 | 2018 |
| Active Deep Q-learning with Demonstration. | 2 | 0.43 | 2018 |
| Cost-Sensitive Reference Pair Encoding for Multi-Label Learning. | 0 | 0.34 | 2018 |
| A Deep Model With Local Surrogate Loss for General Cost-Sensitive Multi-Label Learning. | 0 | 0.34 | 2018 |
| Multi-Label Classification with Feature-Aware Cost-Sensitive Label Embedding | 0 | 0.34 | 2018 |
| Deep Learning with a Rethinking Structure for Multi-label Classification. | 0 | 0.34 | 2018 |
| Rotation-blended CNNs on a New Open Dataset for Tropical Cyclone Image-to-intensity Regression. | 0 | 0.34 | 2018 |
| libact: Pool-based Active Learning in Python. | 1 | 0.37 | 2017 |
| Dynamic Principal Projection for Cost-Sensitive Online Multi-Label Classification. | 2 | 0.35 | 2017 |
| Cost-sensitive Label Embedding for Multi-label Classification. | 5 | 0.43 | 2017 |
| Cyclic Classifier Chain for Cost-Sensitive Multilabel Classification | 0 | 0.34 | 2017 |
| Progressive random k-labelsets for cost-sensitive multi-label classification. | 2 | 0.36 | 2017 |
| Soft Methodology for Cost-and-error Sensitive Classification. | 0 | 0.34 | 2017 |
| Cost-Sensitive Deep Learning with Layer-Wise Cost Estimation. | 0 | 0.34 | 2016 |
| Can Active Learning Experience Be Transferred? | 4 | 0.42 | 2016 |
| Cost-Sensitive Random Pair Encoding for Multi-Label Classification. | 0 | 0.34 | 2016 |
| Automatic Bridge Bidding Using Deep Reinforcement Learning. | 2 | 0.39 | 2016 |
| Linear Upper Confidence Bound Algorithm for Contextual Bandit Problem with Piled Rewards. | 0 | 0.34 | 2016 |
| A Simple Unlearning Framework for Online Learning Under Concept Drifts. | 0 | 0.34 | 2016 |
| A Novel Uncertainty Sampling Algorithm For Cost-Sensitive Multiclass Active Learning | 0 | 0.34 | 2016 |
| Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA | 6 | 0.48 | 2015 |
| Active Learning By Learning | 1 | 0.35 | 2015 |
| Contract Bridge Bidding by Learning. | 3 | 0.41 | 2015 |
| A practical divide-and-conquer approach for preference-based learning to rank | 0 | 0.34 | 2015 |
| Cost-Aware Pre-Training for Multiclass Cost-Sensitive Deep Learning. | 0 | 0.34 | 2015 |
| Active Learning Using Hint Information | 6 | 0.44 | 2015 |
| Condensed Filter Tree for Cost-Sensitive Multi-Label Classification. | 12 | 0.58 | 2014 |
| Effective string processing and matching for author disambiguation | 8 | 0.59 | 2014 |
| Boosting with Online Binary Learners for the Multiclass Bandit Problem. | 5 | 0.52 | 2014 |
| Machine Learning Approaches for Interactive Verification. | 0 | 0.34 | 2014 |
| Reduction from Cost-Sensitive Multiclass Classification to One-versus-One Binary Classification. | 2 | 0.41 | 2014 |
| Improving ranking performance with cost-sensitive ordinal classification via regression | 3 | 0.42 | 2014 |
| Pseudo-reward Algorithms for Contextual Bandits with Linear Payoff Functions. | 1 | 0.35 | 2014 |
| Multilabel classification using error-correcting codes of hard or soft bits. | 7 | 0.50 | 2013 |
| Active Sampling of Pairs and Points for Large-scale Linear Bipartite Ranking. | 1 | 0.35 | 2013 |
| Pairwise Regression with Upper Confidence Bound for Contextual Bandit with Multiple Actions | 0 | 0.34 | 2013 |
| Combination of feature engineering and ranking models for paper-author identification in KDD Cup 2013 | 6 | 0.43 | 2013 |
| Active Learning for Multiclass Cost-Sensitive Classification Using Probabilistic Models | 2 | 0.36 | 2013 |
| Data Selection Techniques for Large-Scale Rank SVM | 3 | 0.43 | 2013 |
| A Linear Ensemble of Individual and Blended Models for Music Rating Prediction. | 0 | 0.34 | 2012 |
