Download 30 papers on Machine Learning

Published June 25, 2014   |   
Baiju NT

Are you looking for some serious research papers on Machine Learning? Here you go…!

1. Optimized projections for compressed sensing
2. Multiscale sparse image representation with learned dictionaries
3. Robust face recognition via sparse representation
4. Feature selection in face recognition: A sparse representation perspective
5. Random projections for manifold learning
6.  Sparse bayesian learning for basis selection
7. Learning to sense sparse signals: Simultaneous sensing matrix and sparsifying dictionary optimization
8. Noise reduction through compressed sensing
9. Using sparse representations for missing data imputation in noise robust speech recognition
10. Noise robust digit recognition using sparse representations
11. Discriminative learned dictionaries for local image analysis
12. Sparse representations for image classification: Learning discriminative and reconstructive non-parametric dictionaries
13. Compressed learning: Universal sparse dimensionality reduction and learning in the measurement domain
14. Compressed Least Squares Regression
15. Utilizing Compressibility in Reconstructing Spectrographic Data, with Applications to Noise Robust ASR
16. Learning Sparse Gaussian Markov Networks using a Greedy Coordinate Ascent Approach
17. Online Group-Structured Dictionary Learning
18. Facial Action Unit Recognition with Sparse Representation
19. Collaborative Filtering via Group-Structured Dictionary Learning
20. Automated Word Puzzle Generation via Topic Dictionaries
21. Performance Limits of Dictionary Learning for Sparse Coding
22. Efficient machine learning using random projections
23. Machine Learning in Automated Text Categorization
24. Pattern Recognition and Machine Learning
25. Large-Scale Machine Learning at Twitter
26. Practical Bayesian Optimization of Machine Learning Algorithms
27. Learning Deep Architectures for AI
28. The Computational Complexity of Machine Learning
29. Using Machine Learning To Design And Interpret Gene-Expression Microarrays
30. Reproducing Kernel Banach Spaces for Machine Learning