Application Areas

Learning Smooth and Fair Representations AISTATS 2021 Learning Student-Friendly Teacher Networks for Knowledge Distillation NeurIPS 2021 Learning Student Networks in the Wild CVPR 2021 Learning the Best Pooling Strategy for Visual Semantic Embedding CVPR 2021 Learning to Adapt via Latent Domains for Adaptive Semantic Segmentation NeurIPS 2021 Learning to Augment for Data-scarce Domain BERT Knowledge Distillation AAAI 2021 Learning to Cascade: Confidence Calibration for Improving the Accuracy and Computational Cost of Cascade Inference Systems AAAI 2021 Learning to Distill Convolutional Features Into Compact Local Descriptors WACV 2021 Learning To Diversify for Single Domain Generalization ICCV 2021 Learning to Explain: Generating Stable Explanations Fast ACL 2021 Learning to Generalize Unseen Domains via Memory-based Multi-Source Meta-Learning for Person Re-Identification CVPR 2021 Learning to Generate Noise for Multi-Attack Robustness ICML 2021 Learning to Perturb Word Embeddings for Out-of-distribution QA ACL 2021 Learning to Rank in the Age of Muppets: Effectiveness–Efficiency Tradeoffs in Multi-Stage Ranking EMNLP 2021 Learning to Rank Microphones for Distant Speech Recognition Interspeech 2021 Learning to Rank Question Answer Pairs with Bilateral Contrastive Data Augmentation EMNLP 2021 Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model AISTATS 2021 Learning to Recognize Dialect Features NAACL 2021 Learning to Recommend from Sparse Data via Generative User Feedback AAAI 2021 Learning To Relate Depth and Semantics for Unsupervised Domain Adaptation CVPR 2021 Learning To Restore Hazy Video: A New Real-World Dataset and a New Method CVPR 2021 Learning to Reweight with Deep Interactions AAAI 2021 Learning To Scale Mixed-Integer Programs AAAI 2021 Learning to Schedule Heuristics in Branch and Bound NeurIPS 2021 Learning Transferable Features for Point Cloud Detection via 3D Contrastive Co-training NeurIPS 2021