Similarity search finds application in database systems handling complex data such as
images or videos, which are typically represented by high-dimensional features and require …

We demonstrate that a state-of-the-art parser can be built using only a lexical tagging model
and a deterministic grammar, with no explicit model of bi-lexical dependencies. Instead, all …

We introduce a method to reduce constituent parsing to sequence labeling. For each word
w_t, it generates a label that encodes:(1) the number of ancestors in the tree that the words …

Matrix factorization (MF) is used by many popular algorithms such as collaborative filtering.
GPU with massive cores and high memory bandwidth sheds light on accelerating MF much …

Opportunity and Curiosity find similar rocks on Mars. One can generally understand this
statement if one knows that Opportunity and Curiosity are instances of the class of Mars …

Hidden Markov Models (HMMs) and Probabilistic Context-Free Grammars (PCFGs) are
widely used structured models, both of which can be represented as factor graph grammars …

There have been several recent attempts to improve the accuracy of grammar induction
systems by bounding the recursive complexity of the induction model (Ponvert et al., 2011; …

Due to their origin in computer graphics, graphics processing units (GPUs) are highly
optimized for dense problems, where the exact same operation is applied repeatedly to all …

This book aims to achieve the following goals:(1) to provide a high-level survey of key
analytics models and algorithms without going into mathematical details;(2) to analyze the …

Weighted finite automata and transducers (including hidden Markov models and conditional
random fields) are widely used in natural language processing (NLP) to perform tasks such …