Mehryar Mohri Foundations of Machine Learning Courant Institute of Mathematical Sciences Homework Assignment 2 -solution A. Support Vector Machines

Mehryar Mohri Foundations of Machine Learning Courant Institute of Mathematical Sciences Solution Assignment 2 Solution of Section B Written by Cyril Allauzen

Mehryar Mohri Speech Recognition Courant Institute of Mathematical Sciences Homework Assignment 3 (solution) Part 2, 3 Written

For these questions, you can use the utility fsminfo of the FSM library. You should however explain how you determine the number of n-grams. The number of states, transitions, and -transitions are obtained directly using fsminfo. For the bigram models, by construction, the number of unigrams is the number of states minus one (back-off state), minus the initial and final state if one wishes to e...

Contents Message from the General Chair

We present a series of algorithms with theoretical guarantees for learning accurate ensembles of several structured prediction rules for which no prior knowledge is assumed. This includes a number of randomized and deterministic algorithms devised by converting on-line learning algorithms to batch ones, and a boosting-style algorithm applicable in the context of structured prediction with a lar...

Mining Biological Repetitive Sequences Using Support Vector Machines and Fuzzy SVM

Structural repetitive subsequences are most important portion of biological sequences, which play crucial roles on corresponding sequence’s fold and functionality. Biggest class of the repetitive subsequences is “Transposable Elements” which has its own sub-classes upon contexts’ structures. Many researches have been performed to criticality determine the structure and function of repetitiv...

Theoretical Foundations and Algorithms for Learning with Multiple Kernels

Kernel-based algorithms have been used with great success in a variety of machine learning applications. These include algorithms such as support vector machines for classification, kernel ridge regression, ranking algorithms, clustering algorithms, and virtually all popular dimensionality reduction algorithms. But, the choice of the kernel, which is crucial to the success of these algorithms, ...