Programming Languages and Compilers Commons^™

Csci 49380/79526: Fundamentals Of Reactive Programming - Assignment 5, Raffi Khatchadourian

Open Educational Resources

No abstract provided.

Cross-Thought For Sentence Encoder Pre-Training, Shuohang Wang, Yuwei Fang, Siqi Sun, Zhe Gan, Yu Cheng, Jingjing Liu, Jing Jiang

Research Collection School Of Computing and Information Systems

In this paper, we propose Cross-Thought, a novel approach to pre-training sequence encoder, which is instrumental in building reusable sequence embeddings for large-scale NLP tasks such as question answering. Instead of using the original signals of full sentences, we train a Transformer-based sequence encoder over a large set of short sequences, which allows the model to automatically select the most useful information for predicting masked words. Experiments on question answering and textual entailment tasks demonstrate that our pre-trained encoder can outperform state-of-the-art encoders trained with continuous sentence signals as well as traditional masked language modeling baselines. Our proposed approach also …

Bist: Bi-Directional Spatio-Temporal Reasoning For Video-Grounded Dialogues, Hung Le, Doyen Sahoo, Nancy F. Chen, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Video-grounded dialogues are very challenging due to (i) the complexity of videos which contain both spatial and temporal variations, and (ii) the complexity of user utterances which query different segments and/or different objects in videos over multiple dialogue turns. However, existing approaches to video-grounded dialogues often focus on superficial temporal-level visual cues, but neglect more fine-grained spatial signals from videos. To address this drawback, we propose Bi-directional Spatio-Temporal Learning (BiST), a vision-language neural framework for high-resolution queries in videos based on textual cues. Specifically, our approach not only exploits both spatial and temporal-level information, but also learns dynamic information diffusion …

Uniconv: A Unified Conversational Neural Architecture For Multi-Domain Task-Oriented Dialogues, Hung Le, Doyen Sahoo, Chenghao Liu, Nancy F. Chen, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Building an end-to-end conversational agent for multi-domain task-oriented dialogues has been an open challenge for two main reasons. First, tracking dialogue states of multiple domains is non-trivial as the dialogue agent must obtain complete states from all relevant domains, some of which might have shared slots among domains as well as unique slots specifically for one domain only. Second, the dialogue agent must also process various types of information across domains, including dialogue context, dialogue states, and database, to generate natural responses to users. Unlike the existing approaches that are often designed to train each module separately, we propose “UniConv" …

Collections In Scala, Raffi Khatchadourian

Open Educational Resources

No abstract provided.

Espade: An Efficient And Semantically Secure Shortest Path Discovery For Outsourced Location-Based Services, Bharath K. Samanthula, Divyadharshini Karthikeyan, Boxiang Dong, K. Anitha Kumari

Department of Computer Science Faculty Scholarship and Creative Works

With the rapid growth of smart devices and technological advancements in tracking geospatial data, the demand for Location-Based Services (LBS) is facing a constant rise in several domains, including military, healthcare and transportation. It is a natural step to migrate LBS to a cloud environment to achieve on-demand scalability and increased resiliency. Nonetheless, outsourcing sensitive location data to a third-party cloud provider raises a host of privacy concerns as the data owners have reduced visibility and control over the outsourced data. In this paper, we consider outsourced LBS where users want to retrieve map directions without disclosing their location information. …

Csci 49380/79526: Fundamentals Of Reactive Programming - Assignment 4, Raffi Khatchadourian

Open Educational Resources

No abstract provided.

Csci 49380/79526: Fundamentals Of Reactive Programming - Assignment 3, Raffi Khatchadourian

Open Educational Resources

No abstract provided.

Csci 49380/79526: Fundamentals Of Reactive Programming- Assignment 1, Raffi Khatchadourian

Open Educational Resources

No abstract provided.

Csci 49380/79526: Fundamentals Of Reactive Programming- Syllabus, Raffi Khatchadourian

Open Educational Resources

No abstract provided.

Csci 49380/79526: Fundamentals Of Reactive Programming - Assignment 2, Raffi Khatchadourian

Open Educational Resources

No abstract provided.

Inheritance Details In Scala, Raffi Khatchadourian

Open Educational Resources

No abstract provided.

Evaluating Performance Of Openmp Tasks In A Seismic Stencil Application, Eric Raut, Jie Meng, Mauricio Araya-Polo, Barbara Chapman

Department of Applied Mathematics & Statistics Faculty Publications

Simulations based on stencil computations (widely used in geosciences) have been dominated by the MPI+OpenMP programming model paradigm. Little effort has been devoted to experimenting with task-based parallelism in this context. We address this by introducing OpenMP task parallelism into the kernel of an industrial seismic modeling code, Minimod. We observe that even for these highly regular stencil computations, taskified kernels are competitive with traditional OpenMP-augmented loops, and in some experiments tasks even outperform loop parallelism.

This promising result sets the stage for more complex computational patterns. Simulations involve more than just the stencil calculation: a collection of kernels is …

A Fortran-Keras Deep Learning Bridge For Scientific Computing, Jordan Ott, Mike Pritchard, Natalie Best, Erik Linstead, Milan Curcic, Pierre Baldi

Engineering Faculty Articles and Research

Implementing artificial neural networks is commonly achieved via high-level programming languages such as Python and easy-to-use deep learning libraries such as Keras. These software libraries come preloaded with a variety of network architectures, provide autodifferentiation, and support GPUs for fast and efficient computation. As a result, a deep learning practitioner will favor training a neural network model in Python, where these tools are readily available. However, many large-scale scientific computation projects are written in Fortran, making it difficult to integrate with modern deep learning methods. To alleviate this problem, we introduce a software library, the Fortran-Keras Bridge (FKB). This two-way …

An Empirical Study Of Refactorings And Technical Debt In Machine Learning Systems, Yiming Tang, Raffi Khatchadourian, Mehdi Bagherzadeh, Rhia Singh, Ajani Stewart, Anita Raja

Publications and Research

Machine Learning (ML), including Deep Learning (DL), systems, i.e., those with ML capabilities, are pervasive in today's data-driven society. Such systems are complex; they are comprised of ML models and many subsystems that support learning processes. As with other complex systems, ML systems are prone to classic technical debt issues, especially when such systems are long-lived, but they also exhibit debt specific to these systems. Unfortunately, there is a gap of knowledge in how ML systems actually evolve and are maintained. In this paper, we fill this gap by studying refactorings, i.e., source-to-source semantics-preserving program transformations, performed in real-world, open-source …

Visualocv: Refined Dataflow Programming Interface For Opencv, John Boggess

MS in Computer Science Project Reports

OpenCV is a popular tool for developing computer vision algorithms; however, prototyping OpenCV-based algorithms is a time consuming and iterative process. VisualOCV is an open source tool to help users better understand and create computer vision algorithms. A user can see how data is processed at each step in their algorithm, and the results of any changes to the algorithm will be displayed to the user immediately. This can allow the user to easily experiment with various computer vision methods and their parameters. EyeCalc 1.0 uses the Microsoft Foundation Class Library, an old GUI framework by Microsoft, and contains various …

Modified Surrogate Cutting Plane Algorithm (Mscpa) For Integer Linear Programming Problems, Israa Hasan

Emirates Journal for Engineering Research

This work concerned with introducing a new algorithm for solving integer linear programming problems. The improved algorithm can help by decreasing a calculation the complexity of these problems, an advantages of the proposed method are to reduce the solution time and to decrease algorithmic complexity. Some specific numerical examples are discussed to demonstrate the validity and applicability of the proposed method. The numerical results are compared with the solution of integer linear programming problems by using cutting plane method (Gomory method).

Snow-Albedo Feedback In Northern Alaska: How Vegetation Influences Snowmelt, Lucas C. Reckhaus

Theses and Dissertations

This paper investigates how the snow-albedo feedback mechanism of the arctic is changing in response to rising climate temperatures. Specifically, the interplay of vegetation and snowmelt, and how these two variables can be correlated. This has the potential to refine climate modelling of the spring transition season. Research was conducted at the ecoregion scale in northern Alaska from 2000 to 2020. Each ecoregion is defined by distinct topographic and ecological conditions, allowing for meaningful contrast between the patterns of spring albedo transition across surface conditions and vegetation types. The five most northerly ecoregions of Alaska are chosen as they encompass …

Novel Deep Learning Methods Combined With Static Analysis For Source Code Processing, Duy Quoc Nghi Bui

Dissertations and Theses Collection (Open Access)

It is desirable to combine machine learning and program analysis so that one can leverage the best of both to increase the performance of software analytics. On one side, machine learning can analyze the source code of thousands of well-written software projects that can uncover patterns that partially characterize software that is reliable, easy to read, and easy to maintain. On the other side, the program analysis can be used to define rigorous and unique rules that are only available in programming languages, which enrich the representation of source code and help the machine learning to capture the patterns better. …

Specialization: Do Your Job Well Helping Students Who Are Considering A Career In Programming Know How To Invest Their Time., Scott Pulley

Marriott Student Review

The article examines the effects of specialization on the hiring process for undergraduates studying programming whether in information systems or computer science.