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Methodology
← Core Methods
Machine Learning
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Core Methods
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Representation Learning
18863 directly classified papers
Papers per year
2000: 2
2001: 4
2002: 2
2003: 18
2004: 4
2005: 9
2006: 62
2007: 61
2008: 74
2009: 73
2010: 96
2011: 103
2012: 131
2013: 283
2014: 255
2015: 295
2016: 426
2017: 691
2018: 1066
2019: 1798
2020: 1830
2021: 2207
2022: 2109
2023: 2560
2024: 2177
2025: 1926
2026: 601
Papers
Time-Mapping Using Space-Time Saliency
CVPR 2014
Collective Matrix Factorization Hashing for Multimodal Data
CVPR 2014
Discriminative Unsupervised Feature Learning with Convolutional Neural Networks
NIPS 2014
Encoding High Dimensional Local Features by Sparse Coding Based Fisher Vectors
NIPS 2014
Expectation Backpropagation: Parameter-Free Training of Multilayer Neural Networks with Continuous or Discrete Weights
NIPS 2014
Simultaneous Model Selection and Optimization through Parameter-free Stochastic Learning
NIPS 2014
Reducing the Rank in Relational Factorization Models by Including Observable Patterns
NIPS 2014
Divide-and-Conquer Learning by Anchoring a Conical Hull
NIPS 2014
Extracting Latent Structure From Multiple Interacting Neural Populations
NIPS 2014
Clustered factor analysis of multineuronal spike data
NIPS 2014
Convolutional Neural Network Architectures for Matching Natural Language Sentences
NIPS 2014
Modeling Deep Temporal Dependencies with Recurrent Grammar Cells""
NIPS 2014
On the Number of Linear Regions of Deep Neural Networks
NIPS 2014
Non-rigid Segmentation using Sparse Low Dimensional Manifolds and Deep Belief Networks
CVPR 2014
Multimodal Learning in Loosely-organized Web Images
CVPR 2014
Scalable Multitask Representation Learning for Scene Classification
CVPR 2014
Recognition of Complex Events: Exploiting Temporal Dynamics between Underlying Concepts
CVPR 2014
Kernel-PCA Analysis of Surface Normals for Shape-from-Shading
CVPR 2014
Asymmetrical Gauss Mixture Models for Point Sets Matching
CVPR 2014
Large Scale Multi-view Stereopsis Evaluation
CVPR 2014
Relative Parts: Distinctive Parts for Learning Relative Attributes
CVPR 2014
Multi-scale Graphical Models for Spatio-Temporal Processes
NIPS 2014
Conditional Random Field Autoencoders for Unsupervised Structured Prediction
NIPS 2014
Learning Distributed Representations for Structured Output Prediction
NIPS 2014
Quality Dynamic Human Body Modeling Using a Single Low-cost Depth Camera
CVPR 2014
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