Braverman Readings in Machine Learning. Key Ideas from Inception to Current State |
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Contents
Potential Functions for Signals and Symbolic Sequences | 3 |
A Unified Framework for Clustering | 32 |
Compactness Hypothesis Potential Functions and Rectifying Linear Space in Machine Learning | 52 |
Conformal Predictive Distributions with Kernels | 103 |
On the Concept of Compositional Complexity | 122 |
On the Choice of a Kernel Function in Symmetric Spaces | 128 |
Causality Modeling and Statistical Generative Mechanisms | 148 |
Novel Developments | 187 |
Geometrical Insights for Implicit Generative Modeling | 229 |
Applications to Physics | 269 |
An Overview | 298 |
Personal and Beyond | 329 |
A Man of Unlimited Capabilities in Memory of E M Braverman | 331 |
Braverman and His Theory of Disequilibrium Economics | 333 |
My Mentor and My Model | 341 |
List of Bravermans Papers Published in the Avtomatika i telemekhanika Journal Moscow Russia and Translated to English as Automation and Remote... | 349 |
OneClass Semisupervised Learning | 188 |
Prediction of Drug Efficiency by Transferring Gene Expression Data from Cell Lines to Cancer Patients | 201 |
On One Approach to Robot Motion Planning | 213 |
Common terms and phrases
algorithm Alignment Kernel analysis antihydrogen application Automation and Remote Bayesian Braverman causal cell lines classification cluster coefficients complexity computed consider convergence convex dataset decision rule deep neural networks deep reinforcement learning defined depend detector distance function distance space elements embedding estimation Euclidean example ffiffiffiffiffiffiffi finite images inequality inner product K-Means KRRPM Lemma linear space linearly separable machine learning matrix measure methods metric space minimal geodesic Misha motion planning Muchnik neural networks observer optimal parameters particle pattern recognition Polish space positive definite potential functions predictive distributions probabilistic probability problem Proof properties proposed protein random real-world objects regression regularization function reinforcement learning Remote Control representation robot Rozonoer sample Sect similarity sorafenib Springer statistical structure subset support vector machines symbolic sequences symmetric Theorem theory training criterion variables zero
Bibliographic information
| Title | Braverman Readings in Machine Learning. Key Ideas from Inception to Current State |
| Author | Lev Rozonoer |
| Publisher | Springer |
| ISBN | 3319994921, 9783319994925 |
| Export Citation | BiBTeX EndNote RefMan |