We present an extensive study of surrogate losses for structured prediction supported by* $
H $-consistency bounds*. These are recently introduced guarantees that are more relevant …

A new edition of a graduate-level machine learning textbook that focuses on the analysis
and theory of algorithms. This book is a general introduction to machine learning that can …

This important text and reference for researchers and students in machine learning, game
theory, statistics and information theory offers a comprehensive treatment of the problem of …

We present a unified framework to study graph kernels, special cases of which include the
random walk (Gärtner et al., 2003; Borgwardt et al., 2005) and marginalized (Kashima et al …

The study of phonotactics is a central topic in phonology. We propose a theory of
phonotactic grammars and a learning algorithm that constructs such grammars from positive …

Weighted finite-state transducers are used in many applications such as text, speech and
image processing. This chapter gives an overview of several recent weighted transducer …

The image foresting transform (IFT) is a graph-based approach to the design of image
processing operators based on connectivity. It naturally leads to correct and efficient …

We describe OpenFst, an open-source library for weighted finite-state transducers (WFSTs).
OpenFst consists of a C++ template library with efficient WFST representations and over …

Within the realm of network security, we interpret the concept of trust as a relation among
entities that participate in various protocols. Trust relations are based on evidence created …

This chapter describes a general representation and algorithmic framework for speech
recognition based on weighted finite-state transducers. These transducers provide a …