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Application Areas

31,658 papers (3 classified directly here)

Subtopics

Domain Adaptation (8,962) Efficient Computing (6,898) Data Augmentation (3,720) Fairness (3,511) Knowledge Distillation (3,086) Privacy (2,847) Domain Generalization (1,834) Model Compression (1,718) Risk Management (1,064) Model Merging (558) Recommender Systems (315) Information Retrieval (244) Text Classification (139) Text Processing (5)

Papers per year

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Papers (including subtopics)

Multi-Task Supervised Pretraining for Neural Domain Adaptation ACL 2020
A One-step Approach to Covariate Shift Adaptation ACML 2020
Deep-n-Cheap: An Automated Search Framework for Low Complexity Deep Learning ACML 2020
DFQF: Data Free Quantization-aware Fine-tuning ACML 2020
FIREPruning: Learning-based Filter Pruning for Convolutional Neural Network Compression ACML 2020
Inferring Continuous Treatment Doses from Historical Data via Model-Based Entropy-Regularized Reinforcement Learning ACML 2020
Run2Survive: A Decision-theoretic Approach to Algorithm Selection based on Survival Analysis ACML 2020
PSForest: Improving Deep Forest via Feature Pooling and Error Screening ACML 2020
Tight Analysis of Privacy and Utility Tradeoff in Approximate Differential Privacy AISTATS 2020
A Double Residual Compression Algorithm for Efficient Distributed Learning AISTATS 2020
Learning Fair Representations for Kernel Models AISTATS 2020
Fair Decisions Despite Imperfect Predictions AISTATS 2020
Sketching Transformed Matrices with Applications to Natural Language Processing AISTATS 2020
Unconditional Coresets for Regularized Loss Minimization AISTATS 2020
ASAP: Architecture Search, Anneal and Prune AISTATS 2020
Utility/Privacy Trade-off through the lens of Optimal Transport AISTATS 2020
Identifying and Correcting Label Bias in Machine Learning AISTATS 2020
Scalable Feature Selection for (Multitask) Gradient Boosted Trees AISTATS 2020
Model-Agnostic Counterfactual Explanations for Consequential Decisions AISTATS 2020
Learning Overlapping Representations for the Estimation of Individualized Treatment Effects AISTATS 2020
Additive Tree-Structured Covariance Function for Conditional Parameter Spaces in Bayesian Optimization AISTATS 2020
Mitigating Overfitting in Supervised Classification from Two Unlabeled Datasets: A Consistent Risk Correction Approach AISTATS 2020
Regularity as Regularization: Smooth and Strongly Convex Brenier Potentials in Optimal Transport AISTATS 2020
Simulator Calibration under Covariate Shift with Kernels AISTATS 2020
Regularization via Structural Label Smoothing AISTATS 2020