Papers in this area
Showing 1–10 of 10 papers
| Task | Papers | Results |
|---|---|---|
| Dataset Distillation Dataset distillation is the task of synthesizing a small dat… | 216 | 0 |
| Authorship Attribution Authorship attribution, also known as authorship identificat… | 212 | 0 |
| Neural Network Compression | 193 | 0 |
| Second-order methods Use second-order statistics to process data. | 181 | 0 |
| Low-Rank Matrix Completion Low-Rank Matrix Completion is an important problem with seve… | 158 | 0 |
| Riemannian optimization Optimization methods on Riemannian manifolds. | 153 | 0 |
| Deep Hashing | 149 | 0 |
| Missing Labels The challenge in multi-label learning with missing labels is… | 139 | 0 |
| backdoor defense | 131 | 0 |
| Explainable Models | 128 | 0 |
| L2 Regularization See [Weight Decay](https://paperswithcode.com/method/weight-… | 128 | 0 |
| Linear evaluation | 128 | 0 |
| Systematic Generalization | 126 | 0 |
| channel selection | 119 | 0 |
| Data Valuation Data valuation in machine learning tries to determine the wo… | 119 | 0 |
| Avg | 117 | 0 |
| Adversarial Text Adversarial Text refers to a specialised text sequence that … | 114 | 0 |
| Model Poisoning | 108 | 0 |
| Discrete Choice Models | 104 | 0 |
| Hard Attention | 100 | 0 |
| Feature Compression Compress data for machine interpretability to perform downst… | 96 | 0 |
| High-Level Synthesis | 96 | 0 |
| Long-range modeling A new task for testing the long-sequence modeling capabiliti… | 95 | 0 |
| Miscellaneous | 93 | 0 |
| scoring rule | 90 | 0 |
| Model Discovery discovering PDEs from spatiotemporal data | 87 | 0 |
| Online Clustering Models that learn to label each image (i.e. cluster the data… | 86 | 0 |
| One-class classifier | 82 | 0 |
| Extreme Multi-Label Classification Extreme Multi-Label Classification is a supervised learning … | 75 | 0 |
| Constrained Clustering Split data into groups, taking into account knowledge in the… | 72 | 0 |
| Metaheuristic Optimization In computer science and mathematical optimization, a metaheu… | 69 | 0 |
| Self-Knowledge Distillation | 68 | 0 |
| Program induction Generating program code for domain-specific tasks | 67 | 0 |
| Adversarial Purification A class of adversarial defense methods that remove adversari… | 65 | 0 |
| Few-shot NER Few-Shot Named Entity Recognition (NER) is the task of recog… | 63 | 0 |
| Supervised dimensionality reduction | 57 | 0 |
| Dataset Condensation Condense the full dataset into a tiny set of synthetic data. | 56 | 0 |
| Variational Monte Carlo Variational methods for quantum physics | 55 | 0 |
| Problem Decomposition | 54 | 0 |
| Normalising Flows | 49 | 0 |
| subspace methods | 49 | 0 |
| Causal Identification | 48 | 0 |
| Automated Feature Engineering Automated feature engineering improves upon the traditional … | 46 | 0 |
| Missing Elements | 46 | 0 |
| Multi-view Subspace Clustering | 46 | 0 |
| Compiler Optimization Machine learning guided compiler optimization | 45 | 0 |
| Service Composition Let T be the task that the service composition needs to acco… | 45 | 0 |
| Pathfinder | 43 | 0 |
| Data Free Quantization Data Free Quantization is a technique to achieve a highly ac… | 37 | 0 |
| Dynamic neural networks Dynamic neural networks are adaptable models that can change… | 37 | 0 |