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← Core Methods
Machine Learning
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Core Methods
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Feature Learning
817 directly classified papers
Papers per year
2001: 1
2003: 3
2005: 2
2006: 15
2007: 12
2008: 18
2009: 6
2010: 16
2011: 20
2012: 32
2013: 76
2014: 34
2015: 23
2016: 34
2017: 47
2018: 31
2019: 46
2020: 57
2021: 43
2022: 58
2023: 70
2024: 93
2025: 79
2026: 1
Papers
Universal Novelty Detection Through Adaptive Contrastive Learning
CVPR 2024
The Unreasonable Effectiveness of Pre-Trained Features for Camera Pose Refinement
CVPR 2024
Get rich quick: exact solutions reveal how unbalanced initializations promote rapid feature learning
NIPS 2024
RPCANet: Deep Unfolding RPCA Based Infrared Small Target Detection
WACV 2024
Stochastic Amortization: A Unified Approach to Accelerate Feature and Data Attribution
NIPS 2024
A Concise Report of the 7th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text
EACL 2024
Segment, Shuffle, and Stitch: A Simple Layer for Improving Time-Series Representations
NIPS 2024
Exploring hybrid approaches to readability: experiments on the complementarity between linguistic features and transformers
EACL 2024
RACAI at ClimateActivism 2024: Improving Detection of Hate Speech by Extending LLM Predictions with Handcrafted Features
EACL 2024
Pruning is Optimal for Learning Sparse Features in High-Dimensions
COLT 2024
Optimized Feature Generation for Tabular Data via LLMs with Decision Tree Reasoning
NIPS 2024
Testing Semantic Importance via Betting
NIPS 2024
Interpretable Mesomorphic Networks for Tabular Data
NIPS 2024
Collaborative Refining for Learning from Inaccurate Labels
NIPS 2024
An LLM Feature-based Framework for Dialogue Constructiveness Assessment
EMNLP 2024
DNNLasso: Scalable Graph Learning for Matrix-Variate Data
AISTATS 2024
Wavelet Dynamic Selection Network for Inertial Sensor Signal Enhancement
AAAI 2024
Data Distribution Valuation
NIPS 2024
A Simple Remedy for Dataset Bias via Self-Influence: A Mislabeled Sample Perspective
NIPS 2024
Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate
NIPS 2024
Benchmarking Out-of-Distribution Generalization Capabilities of DNN-based Encoding Models for the Ventral Visual Cortex.
NIPS 2024
Exploiting Representation Curvature for Boundary Detection in Time Series
NIPS 2024
Length-aware Byte Pair Encoding for Mitigating Over-segmentation in Korean Machine Translation
ACL 2024
Sparse Maximum Margin Learning from Multimodal Human Behavioral Patterns
AAAI 2023
A Benchmark and Asymmetrical-Similarity Learning for Practical Image Copy Detection
AAAI 2023
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