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Gradient Boosting Decision Tree (GBDT) is a popular machine learning algorithm, and has quite a few effective implementations such as XGBoost and pGBRT. Although many engineering optimizations have… Expand
Discriminative training approaches like structural SVMs have shown much promise for building highly complex and accurate models in areas like natural language processing, protein structure… Expand
Machine learning is commonly used to improve ranked retrieval systems. Due to computational difficulties, few learning techniques have been developed to directly optimize for mean average precision… Expand
While discriminative training (e.g., CRF, structural SVM) holds much promise for machine translation, image segmentation, and clustering, the complex inference these applications require make exact… Expand
Supervised clustering is the problem of training a clustering algorithm to produce desirable clusterings: given sets of items and complete clusterings over these sets, we learn how to cluster future… Expand
We present JAWAA 2.0, a scripting language for creating animations easily over the web. JAWAA includes primitives, easy creation of data structures and operations on these structures, and an editor… Expand
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 material… Expand
Stochastic Dual Coordinate Ascent (SDCA) has recently emerged as a state-of-the-art method for solving large-scale supervised learning problems formulated as minimization of convex loss functions. It… Expand
We present a hands-on approach to problem solving in the formal languages and automata theory course. Using the tool JFLAP, students can solve a wide range of problems that are tedious to solve using… Expand
This work was supported under NSF Award IIS-0713483 ``Learning Structure to Structure Mapping,'' and through a gift from Yahoo! Inc.