conftrace_

Application Areas

34,437 papers (4 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Domain Adaptation (9,897) Efficient Computing (8,226) Data Augmentation (3,648) Fairness (3,574) Knowledge Distillation (3,219) Privacy (3,022) Domain Generalization (1,972) Model Compression (1,736) Risk Management (1,119) Model Merging (592) Recommender Systems (343) Information Retrieval (249) Text Classification (144) Text Processing (2)

Papers per year

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1,828

2,498

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3,854

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6,422

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1,666

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Papers (including subtopics)

Learned Video Compression via Joint Spatial-Temporal Correlation Exploration AAAI 2020 Learning Active Task-Oriented Exploration Policies for Bridging the Sim-to-Real Gap RSS 2020 Learning a Dynamic Map of Visual Appearance CVPR 2020 Learning Agent Communication under Limited Bandwidth by Message Pruning AAAI 2020 Learning a Multi-Domain Curriculum for Neural Machine Translation ACL 2020 Learning a Reinforced Agent for Flexible Exposure Bracketing Selection CVPR 2020 Learning Augmentation Network via Influence Functions CVPR 2020 Learning Augmented Energy Minimization via Speed Scaling NeurIPS 2020 Learning Better Lossless Compression Using Lossy Compression CVPR 2020 Learning Bounds for Risk-sensitive Learning NeurIPS 2020 Learning Certified Individually Fair Representations NeurIPS 2020 Learning Complex Spectral Mapping for Speech Enhancement with Improved Cross-Corpus Generalization Interspeech 2020 Learning Composable Energy Surrogates for PDE Order Reduction NeurIPS 2020 Learning Counterfactual Representations for Estimating Individual Dose-Response Curves AAAI 2020 Learning De-biased Representations with Biased Representations ICML 2020 Learning discrete distributions: user vs item-level privacy NeurIPS 2020 Learning Domain Terms - Empirical Methods to Enhance Enterprise Text Analytics Performance COLING 2020 Learning End-to-End Scene Flow by Distilling Single Tasks Knowledge AAAI 2020 Learning Fair Naive Bayes Classifiers by Discovering and Eliminating Discrimination Patterns AAAI 2020 Learning Fair Policies in Multi-Objective (Deep) Reinforcement Learning with Average and Discounted Rewards ICML 2020 Learning Fair Representations for Kernel Models AISTATS 2020 Learning Feature Interactions with Lorentzian Factorization Machine AAAI 2020 Learning Filter Pruning Criteria for Deep Convolutional Neural Networks Acceleration CVPR 2020 Learning for Dose Allocation in Adaptive Clinical Trials with Safety Constraints ICML 2020 Learning from Failure: De-biasing Classifier from Biased Classifier NeurIPS 2020