Information & computer science publications
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Probabilistic Inference Modulo Theories
We present SGDPLL(T ), an algorithm that solves probabilistic inference modulo theories, that is, inference problems over probabilistic models defined via a logic theory provided as a parameter.
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Analyzing hyperspectral images into multiple subspaces using Gaussian mixture models
I argue that the spectra in a hyperspectral datacube will usually lie in several low-dimensional subspaces, and that these subspaces are more easily estimated from the data than the endmembers.
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Spatial and Temporal Patterns in Preterm Birth in the United States
In order to help generate new research hypotheses, this study explored spatial and temporal patterns of preterm birth in a large, total-population dataset.
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Anomaly Detection and Diagnosis for Automatic Radio Network Verification
This paper focuses on the verification problem, proposing a novel framework that uses anomaly detection and diagnosis techniques that operate within a specified spatial scope.
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Snap-N-Eat: Food Recognition and Nutrition Estimation on a Smartphone
We present snap-n-eat, a mobile food recognition system. The system can recognize food and estimate the calorific and nutrition content of foods automatically without any user intervention.
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A Cross-language Study on Automatic Speech Disfluency Detection
We investigate two systems for automatic disfluency detection on English and Mandarin conversational speech data.Ā The first system combines various lexical and prosodic features in a Conditional Random Field model for detecting edit disfluencies.Ā
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Conflict-Directed Graph Coverage
In this paper, we open the black box and devise a new algorithm for this problem domain that we call conflict-directed graph coverage.
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Semantically Secure Order-Revealing Encryption: Multi-Input Functional Encryption without Obfuscation
We construct the first implementable encryption system supporting greater-than comparisons on encrypted data that provides the ābest-possibleā semantic security.
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Channel and Noise Robustness of Articulatory Features in a Deep Neural Net Based Speech Recognition System
This work presents a deep neural network (DNN)āhiddenĀ MarkovĀ modelĀ (HMM) basedĀ acoustic modelĀ where articulatory features are used in addition to mel-frequency cepstral coefficients (MFCC) for theĀ Aurora-4Ā speech recognitionĀ task.
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Reasoning About Interruption of Biological Processes
Our work is motivated by the vision of automated asking and answering of questions related to a biology textbookāa capability which requires application of abstract reasoning patterns.
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AKI in Hospitalized Children: Comparing the pRIFLE, AKIN, and KDIGO Definitions
This study applied the Pediatric RIFLE, AKI Network, and Kidney Disease Improving Global Outcomes criteria to a cohort of hospitalizations to compare AKI incidence and outcomes in ICU and non-ICU pediatric populations.
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Beyond the PDP-11: Architectural Support for a Memory-Safe C Abstract Machine
We propose a new memory-safe interpretation of the C abstract machine that provides stronger protection to benefit security and debugging.