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Learning Types

32,670 papers (1 classified directly here)

Representation Learning (5,307) Multimodal Learning (3,969) Self-Supervised Learning (3,492) Transfer Learning (2,890) Adversarial Learning (2,199) Deep Learning (1,883) Contrastive Learning (1,730) Reinforcement Learning (1,500) Knowledge Distillation (1,494) Fine-Tuning (1,117) Multi-Task Learning (1,069) Domain Adaptation (977) Zero-Shot Learning (758) Unsupervised Learning (734) Few-Shot Learning (694) Classification (621) Retrieval-Augmented Generation (606) Data Augmentation (583) Semi-Supervised Learning (450) Weakly Supervised Learning (429) Continual Learning (408) In-Context Learning (387) Sequence Modeling (375) Meta-Learning (252) Metric Learning (232) Ensemble Learning (223) Federated Learning (215) Multi-Lingual Learning (199) Robustness (197) Parameter-Efficient Fine-Tuning (190) Imitation Learning (180) Prompt Engineering (170) Chain-of-Thought Reasoning (153) Curriculum Learning (146) Synthetic Data Generation (143) Reinforcement Learning from Human Feedback (141) Multi-Label Classification (123) Regression (117) Generative Model (109) Semantic Segmentation (106) Domain Generalization (105) Uncertainty Quantification (98) Controllable Generation (93) Text Generation (86) Neural Architecture Search (80) Object Detection (80) Image Generation (79) Multi-Agent Systems (76) Feature Learning (74) Preference Learning (73) Machine Translation (71) Out-of-Distribution Detection (68) Machine Unlearning (63) Generation (61) Reasoning (54) Multi-View Learning (53) Time Series (52) Instruction Tuning (50) Distributed Learning (50) Image Restoration (49) Chain-of-Thought (48) Active Learning (47) Text Classification (43) Distribution Shift (43) Structured Prediction (42) Clustering (41) Image Classification (40) Model Merging (37) Sparse Learning (36) Sequence Labeling (36) Multi-Instance Learning (35) Anomaly Detection (33) Image Processing (33) Code Generation (31) Fairness (30) Robust Learning (28) Multi-Domain Learning (27) Supervised Learning (26) Model-Based RL (25) Natural Language Generation (24) Privacy (21) Multi-Objective Optimization (19) Multi-Scale Learning (19) Neural Machine Translation (18) Causal Inference (14) Instance Segmentation (9) Interactive Learning (9) Multi-Label Learning (9) Multi-Source Learning (9) Multi-Class Classification (8)
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Papers (including subtopics)

Decorate the Newcomers: Visual Domain Prompt for Continual Test Time Adaptation AAAI 2023 Decoupled Multimodal Distilling for Emotion Recognition CVPR 2023 Decoupled Semantic Prototypes Enable Learning From Diverse Annotation Types for Semi-Weakly Segmentation in Expert-Driven Domains CVPR 2023 Decoupled Training for Long-Tailed Classification With Stochastic Representations ICLR 2023 Decouple then Combine: A Simple and Effective Framework for Fraud Transaction Detection ACML 2023 Decoupling MaxLogit for Out-of-Distribution Detection CVPR 2023 Decoupling Pseudo Label Disambiguation and Representation Learning for Generalized Intent Discovery ACL 2023 DeCrisisMB: Debiased Semi-Supervised Learning for Crisis Tweet Classification via Memory Bank EMNLP 2023 DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization NeurIPS 2023 Deep Active Learning for Morphophonological Processing ACL 2023 Deep Attentive Model for Knowledge Tracing AAAI 2023 Deep Clustering with Incomplete Noisy Pairwise Annotations: A Geometric Regularization Approach ICML 2023 Deep Declarative Dynamic Time Warping for End-to-End Learning of Alignment Paths ICLR 2023 Deep Deterministic Uncertainty: A New Simple Baseline CVPR 2023 Deep Digging into the Generalization of Self-Supervised Monocular Depth Estimation AAAI 2023 Deep Equilibrium Models for Snapshot Compressive Imaging AAAI 2023 Deep Generative Symbolic Regression ICLR 2023 Deep Generative Symbolic Regression with Monte-Carlo-Tree-Search ICML 2023 Deep Graph Representation Learning and Optimization for Influence Maximization ICML 2023 Deep Hashing With Minimal-Distance-Separated Hash Centers CVPR 2023 Deep Image Harmonization with Globally Guided Feature Transformation and Relation Distillation ICCV 2023 Deep Kernel Regression with Finite Learnable Kernels ACML 2023 Deep Latent Regularity Network for Modeling Stochastic Partial Differential Equations AAAI 2023 Deep learning and low-resource languages: How much data is enough? A case study of three linguistically distinct South African languages EACL 2023 Deep Learning of Partial Graph Matching via Differentiable Top-K CVPR 2023