Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning)

Learning with Kernels: Support Vector Ma

📁 Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning)

✍ Bernhard Schlkopf, Alexander J. Smola 📂 Library 📅 2001 🏛 The MIT Press 🌐 English

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of

Learning with kernels: support vector ma

📁 Learning with kernels: support vector machines, regularization, optimization, and beyond

✍ Bernhard Schölkopf, Alexander J. Smola 📂 Library 📅 2002 🏛 The MIT Press 🌐 English

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of

Learning with Kernels: Support Vector Ma

📁 Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond

✍ Bernhard Schlkopf, Alexander J. Smola 📂 Library 📅 2001 🏛 The MIT Press 🌐 English

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs -- -kernels--for a number of learning tasks.

Learning with kernels : support vector m

📁 Learning with kernels : support vector machines, regularization, optimization, and beyond

✍ Bernhard Schölkopf; Alexander J Smola 📂 Library 📅 2002 🏛 MIT Press 🌐 English

Learning with Kernels: Support Vector Ma

📁 Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond

✍ Bernhard Schlkopf, Alexander J. Smola 📂 Library 📅 2002 🏛 MIT Press 🌐 English

A comprehensive introduction to Support Vector Machines and related kernel methods.In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegan

Learning with Kernels: Support Vector Ma

📁 Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond

✍ Bernhard Schölkopf, Alexander J. Smola 📂 Library 📅 2001 🏛 The MIT Press 🌐 English

A comprehensive introduction to Support Vector Machines and related kernel methods.In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegan