Papers in machine learning
- "Why Should I Trust You?" Explaining the Predictions of Any Classifier
- A Few Useful Things to Know About Machine Learning
- Adam: A Method for Stochastic Optimization
- All You Need is Ears: A Multi-Sensory Embodied Agent
- Cooperative sequential adsorption
- Discourse Complements Lexical Semantics for Non-factoid Answer Reranking
- General Self-Similarity: An Overview
- ImageNet Classification with Deep Convolutional Neural Networks
- On compact sets in horn logic
- Random Forests
- Real-time Speech Emotion Recognition by ANN
- S-MAC: An energy-efficient MAC protocol for wireless sensor networks
- Self-organized criticality: An explanation of the 1/f noise
- The Fast Johnson-Lindenstrauss Transform and Approximate Nearest Neighbors
- Top 10 algorithms in data mining
- Understanding Deep Convolutional Networks