Instruct: Given a paper title, retrieve paper titles that are cited by the given paper
Query: Understanding Machine Learning: From Theory to Algorithms
Machine Learning: A Probabilistic Perspective
Proximal Algorithms in Statistics and Machine Learning
Bayesian Reasoning and Machine Learning
an overview of statistical learning theory .
Information Theory, Inference, and Learning Algorithms
Private Empirical Risk Minimization: Efficient Algorithms and Tight Error Bounds
A Learning Machine: Part I
Machine Learning that Matters
handbook of research on machine learning applications and trends : algorithms , methods , and techniques .
Support vector machines: Theory and applications
From machine learning to machine reasoning
Extreme learning machine: Theory and applications
Distributed Machine Learning: Foundations, Trends, and Practices
Interpretability in Machine Learning – Principles and Practice
Argumentation for machine learning: a survey
Taxonomy of Machine Learning Algorithms to classify real- time Interactive applications
Optimization, Learning and Natural Algorithms
Genetic Algorithms and Machine Learning
Big data algorithms beyond machine learning
Machine Learning for Big Data : A New Perspective
Person reidentification by support vector ranking
Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
Using kNN Model for Automatic Feature Selection
Krimping texts for better summarization
Faster-Than-Nyquist Signaling: An Overview