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LightGBM: A Highly Efficient Gradient Boosting Decision Tree
TLDR
It is proved that, since the data instances with larger gradients play a more important role in the computation of information gain, GOSS can obtain quite accurate estimation of the information gain with a much smaller data size, and is called LightGBM. Expand
Cutting-plane training of structural SVMs
TLDR
This paper explores how cutting-plane methods can provide fast training not only for classification SVMs, but also for structural SVMs and presents an extensive empirical evaluation of the method applied to binary classification, multi-class classification, HMM sequence tagging, and CFG parsing. Expand
A support vector method for optimizing average precision
TLDR
This work presents a general SVM learning algorithm that efficiently finds a globally optimal solution to a straightforward relaxation of MAP, and shows its method to produce statistically significant improvements in MAP scores. Expand
Training structural SVMs when exact inference is intractable
TLDR
This work provides a theoretical and empirical analysis of both types of approximate trained structural SVMs, focusing on fully connected pairwise Markov random fields, and finds that models trained with overgenerating methods have theoretic advantages over undergeneration methods, are empirically robust relative to their undergenerating brethren, and relaxed trained models favor non-fractional predictions from relaxed predictors. Expand
Supervised clustering with support vector machines
TLDR
This paper presents an SVM algorithm that trains a clustering algorithm by adapting the item-pair similarity measure, and empirically evaluates the algorithm for noun-phrase and news article clustering. Expand
A visual and interactive automata theory course with JFLAP 4.0
TLDR
JFLAP 4.0 has easier interactive approaches to previous topics and covers many new topics including three parsing algorithms, multi-tape Turing machines, L-systems, and grammar transformations. Expand
JAWAA: easy web-based animation from CS 0 to advanced CS courses
TLDR
JAWAA 2.0 is presented, a scripting language for creating animations easily over the web, and how to use JAWAA in a range of computer science courses including CS 0, CS 1, CS 2 and advanced courses is shown. Expand
Turning automata theory into a hands-on course
TLDR
A hands-on approach to problem solving in the formal languages and automata theory course, and a new feature in JFLAP, Turing machine building blocks, where one can now build complex Turing machines by using other Turing machines as components or building blocks. Expand
Supervised k-Means Clustering
This work was supported under NSF Award IIS-0713483 ``Learning Structure to Structure Mapping,'' and through a gift from Yahoo! Inc.
A visual and interactive automata theory course with JFLAP 4.0
We describe the instructional software JFLAP 4.0 and how it can be used to provide a hands-on formal languages and automata theory course. JFLAP 4.0 doubles the number of chapters worth of materialExpand
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