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A Stochastic Approach to Eulerian NumbersFeb 08 2019We examine the aggregate behavior of one-dimensional random walks in a model known as (one-dimensional) Internal Diffusion Limited Aggregation. In this model, a sequence of $n$ particles perform random walks on the integers, beginning at the origin. Each ... More

Characterizations of Projective Spaces and Hyperquadrics via Positivity Properties of the Tangent BundleDec 09 2010Dec 18 2010Let $X$ be a smooth complex projective variety. A recent conjecture of S. Kov\'acs states that if t\ he $p^{\text{th}}$-exterior power of the tangent bundle $T_X$ contains the $p^{\text{th}}$-exterior power of an ample vector bundle, then $X$ is either ... More

Stopping Rules for Bag-of-Words Image Search and Its Application in Appearance-Based LocalizationDec 28 2013We propose a technique to improve the search efficiency of the bag-of-words (BoW) method for image retrieval. We introduce a notion of difficulty for the image matching problems and propose methods that reduce the amount of computations required for the ... More

An Efficient Index for Visual Search in Appearance-based SLAMSep 27 2013Vector-quantization can be a computationally expensive step in visual bag-of-words (BoW) search when the vocabulary is large. A BoW-based appearance SLAM needs to tackle this problem for an efficient real-time operation. We propose an effective method ... More

SeGAN: Segmenting and Generating the InvisibleMar 29 2017May 07 2018Objects often occlude each other in scenes; Inferring their appearance beyond their visible parts plays an important role in scene understanding, depth estimation, object interaction and manipulation. In this paper, we study the challenging problem of ... More

Learning to Learn How to Learn: Self-Adaptive Visual Navigation Using Meta-LearningDec 03 2018Learning is an inherently continuous phenomenon. When humans learn a new task there is no explicit distinction between training and inference. After we learn a task, we keep learning about it while performing the task. What we learn and how we learn it ... More

Learning to Learn How to Learn: Self-Adaptive Visual Navigation Using Meta-LearningDec 03 2018Mar 26 2019Learning is an inherently continuous phenomenon. When humans learn a new task there is no explicit distinction between training and inference. As we learn a task, we keep learning about it while performing the task. What we learn and how we learn it varies ... More

Who Let The Dogs Out? Modeling Dog Behavior From Visual DataMar 28 2018May 17 2018We introduce the task of directly modeling a visually intelligent agent. Computer vision typically focuses on solving various subtasks related to visual intelligence. We depart from this standard approach to computer vision; instead we directly model ... More

Text Classification Algorithms: A SurveyApr 17 2019Apr 23 2019In recent years, there has been an exponential growth in the number of complex documents and texts that require a deeper understanding of machine learning methods to be able to accurately classify texts in many applications. Many machine learning approaches ... More

Text Classification Algorithms: A SurveyApr 17 2019Jun 25 2019In recent years, there has been an exponential growth in the number of complex documents and texts that require a deeper understanding of machine learning methods to be able to accurately classify texts in many applications. Many machine learning approaches ... More

Comparative Analysis of User Behavior of Dock-Based vs. Dockless Bikeshare and Scootershare in Washington, D.CJul 25 2019In 2017, dockless bikeshare systems were introduced in the United States, followed by dockless scootershare in early 2018. These new mobility options are expected to complement the existing station-based bikeshare systems, which are bound to static origin ... More

Excited states of $^{39}$Ca and their significance in nova nucleosynthesisNov 01 2018Background: Discrepancies exist between the observed abundances of argon and calcium in oxygen-neon nova ejecta and those predicted by nova models. An improved characterization of the $^{38}$K($p, \gamma$)$^{39}$Ca reaction rate over the nova temperature ... More

An Improvement of Data Classification Using Random Multimodel Deep Learning (RMDL)Aug 23 2018The exponential growth in the number of complex datasets every year requires more enhancement in machine learning methods to provide robust and accurate data classification. Lately, deep learning approaches have achieved surpassing results in comparison ... More

A study of $^{35}$Cl excited states via $^{32}$S($α, p$)May 21 2019Presolar grains originating in oxygen-neon novae may be identified by their sulfur isotopic ratios compared with theoretical estimates. These ratios depend on reliable $^{33}$S($p, \gamma$)$^{34}$Cl and $^{34}$S($p, \gamma$)$^{35}$Cl reaction rates. The ... More

Text Classification Algorithms: A SurveyApr 17 2019In recent years, there has been an exponential growth in the number of complex documents and texts that require a deeper understanding of machine learning methods to be able to accurately classify texts in many applications. Many machine learning approaches ... More

HDLTex: Hierarchical Deep Learning for Text ClassificationSep 24 2017Oct 06 2017The continually increasing number of documents produced each year necessitates ever improving information processing methods for searching, retrieving, and organizing text. Central to these information processing methods is document classification, which ... More

Text Classification Algorithms: A SurveyApr 17 2019Apr 25 2019In recent years, there has been an exponential growth in the number of complex documents and texts that require a deeper understanding of machine learning methods to be able to accurately classify texts in many applications. Many machine learning approaches ... More

RMDL: Random Multimodel Deep Learning for ClassificationMay 03 2018May 31 2018The continually increasing number of complex datasets each year necessitates ever improving machine learning methods for robust and accurate categorization of these data. This paper introduces Random Multimodel Deep Learning (RMDL): a new ensemble, deep ... More

The Focal plane Detector Package on the TUNL Split-pole SpectrographJun 06 2018A focal plane detector for the Enge Split-pole Spectrograph at Triangle Universities Nuclear Laboratory has been designed. The detector package consists of two position sensitive gas avalanche counters, a gas proportionality energy loss section, and a ... More

MESA and NuGrid simulations of classical novae: CO and ONe nova nucleosynthesisMar 25 2013May 20 2014Classical novae are the result of thermonuclear flashes of hydrogen accreted by CO or ONe white dwarfs, leading eventually to the dynamic ejection of the surface layers. These are observationally known to be enriched in heavy elements, such as C, O and ... More

30S RI Beam Production and X-ray BurstsApr 14 2009The present work reports the results of 30S radioactive beam development for a future experiment directly measuring data to extrapolate the 30S(alpha,p) stellar reaction rate in Type I X-ray bursts, a phenomena where nuclear explosions occur repeatedly ... More

Particle identification studies with a full-size 4-GEM prototype for the ALICE TPC upgradeMay 08 2018Jun 17 2018A large Time Projection Chamber is the main device for tracking and charged-particle identification in the ALICE experiment at the CERN LHC. After the second long shutdown in 2019/20, the LHC will deliver Pb beams colliding at an interaction rate of about ... More