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Jiarong Jiang Contact: Email: jiarong AT umiacs DOT umd DOT edu |
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| I am currently a Ph.D. student at Department of Computer Science, University of Maryland, College Park. My advisor is Dr. Hal Daumé III. I am also associated with UMIACS (CLIP lab). My research interests are efficient approximate inference, graphical models, nonparametric methods, and structured prediction, particularly parsing. I got my Bachelor's degree in Mathematics(Information and Computing Science) and second Bachelor's degree in Computer Science from Fudan University, Shanghai, China. | |
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Publications Jiarong Jiang, Piyush Rai, Hal Daumé III, Message-Passing for Approximate MAP Inference with Latent Variables, NIPS 2011. [abstract] | [paper] We consider a general inference setting for discrete probabilistic graphical models where we seek maximum a posteriori (MAP) estimates for a subset of the random variables (max nodes), marginalizing over the rest (sum nodes). We present a hybrid message-passing algorithm to accomplish this. The hybrid algorithm passes a mix of sum and max messages depending on the type of source node (sum or max). We derive our algorithm by showing that it falls out as the solution of a particular relaxation of a variational framework. We further show that the Expectation Maximization algorithm can be seen as an approximation to our algorithm. Experimental results on synthetic and real-world datasets, against several baselines, demonstrate the efficacy of our proposed algorithm. Jiarong Jiang, Adam Teichert, Hal Daumé III, Faster, Better, or Both! Learning Priority Functions for Decoding, Mid-Atlantic Student Colloquium on Speech, Language and Learning, 2011. (talk) [abstract] | [slides] Amit Goyal, Jiarong Jiang, Hal Daumé III, Segmenting low-level instructions into high-level instructions, Learning Workshop, 2011. [abstract] Jiarong Jiang, Piyush Rai, Hal Daumé III, Message Passing Algorithm for Marginal-MAP Estimation, |
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Last update: Jan 20, 2012
Useful Links: [NLP Mtg Deadlines] |
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