Pooyan Jamshidi

research

∙ 04/21/2023

Reconciling High Accuracy, Cost-Efficiency, and Low Latency of Inference Serving Systems

The use of machine learning (ML) inference for various applications is g...

0 Mehran Salmani, et al. ∙

research

∙ 02/05/2023

On the Role of Contrastive Representation Learning in Adversarial Robustness: An Empirical Study

Self-supervised contrastive learning has solved one of the significant o...

2 Fatemeh Ghofrani, et al. ∙

research

∙ 01/18/2023

CaRE: Finding Root Causes of Configuration Issues in Highly-Configurable Robots

Robotic systems have several subsystems that possess a huge combinatoria...

5 Md Abir Hossen, et al. ∙

research

∙ 09/18/2022

Improving the Performance of DNN-based Software Services using Automated Layer Caching

Deep Neural Networks (DNNs) have become an essential component in many a...

5 Mohammadamin Abedi, et al. ∙

research

∙ 06/24/2022

Guidelines for Artifacts to Support Industry-Relevant Research on Self-Adaptation

Artifacts support evaluating new research results and help comparing the...

0 Danny Weyns, et al. ∙

research

∙ 03/19/2022

On Debugging the Performance of Configurable Software Systems: Developer Needs and Tailored Tool Support

Determining whether a configurable software system has a performance bug...

0 Miguel Velez, et al. ∙

research

∙ 01/25/2022

Pre-Trained Language Transformers are Universal Image Classifiers

Facial images disclose many hidden personal traits such as age, gender, ...

37 Rahul Goel, et al. ∙

research

∙ 01/20/2022

Unicorn: Reasoning about Configurable System Performance through the lens of Causality

Modern computer systems are highly configurable, with the total variabil...

8 Md Shahriar Iqbal, et al. ∙

research

∙ 10/07/2021

Pretrained Language Models are Symbolic Mathematics Solvers too!

Solving symbolic mathematics has always been of in the arena of human in...

51 Kimia, et al. ∙

research

∙ 02/27/2021

Scalable Causal Transfer Learning

One of the most important problems in transfer learning is the task of d...

13 Mohammad ali Javidian, et al. ∙

research

∙ 02/23/2021

Accelerating Recursive Partition-Based Causal Structure Learning

Causal structure discovery from observational data is fundamental to the...

15 Md. Musfiqur Rahman, et al. ∙

research

∙ 01/13/2021

White-Box Analysis over Machine Learning: Modeling Performance of Configurable Systems

Performance-influence models can help stakeholders understand how and wh...

0 Miguel Velez, et al. ∙

research

∙ 01/10/2021

Kuksa*: Self-Adaptive Microservices in Automotive Systems

In pervasive dynamic environments, vehicles connect to other objects to ...

0 Ahmad Banijamali, et al. ∙

research

∙ 10/12/2020

CADET: A Systematic Method For Debugging Misconfigurations using Counterfactual Reasoning

Modern computing platforms are highly-configurable with thousands of int...

0 Rahul Krishna, et al. ∙

research

∙ 05/29/2020

Learning LWF Chain Graphs: A Markov Blanket Discovery Approach

This paper provides a graphical characterization of Markov blankets in c...

13 Mohammad ali Javidian, et al. ∙

research

∙ 05/27/2020

Learning LWF Chain Graphs: an Order Independent Algorithm

LWF chain graphs combine directed acyclic graphs and undirected graphs. ...

21 Mohammad ali Javidian, et al. ∙

research

∙ 05/13/2020

Understanding the Nature of System-Related Issues in Machine Learning Frameworks: An Exploratory Study

Modern systems are built using development frameworks. These frameworks ...

0 Yang Ren, et al. ∙

research

∙ 04/17/2020

A Procedure for Extracting Software Development Process Patterns

Process patterns represent well-structured and successful recurring acti...

0 Mahdi Fahmideh, et al. ∙

research

∙ 04/17/2020

Process Patterns for Service Oriented Development

Software systems development nowadays has moved towards dynamic composit...

0 Mahdi Fahmideh, et al. ∙

research

∙ 04/17/2020

Toward a Methodological Knowledge for Service-Oriented Development Based on OPEN Meta Model

Situational method engineering uses a repository of reusable method frag...

0 Mahdi Fahmideh, et al. ∙

research

∙ 04/17/2020

Enhancing the OPEN Process Framework with Service-Oriented Method Fragments

Service-orientation is a promising paradigm that enables the engineering...

0 Mahdi Fahmideh, et al. ∙

research

∙ 02/24/2020

AMP Chain Graphs: Minimal Separators and Structure Learning Algorithms

We address the problem of finding a minimal separator in an Andersson-Ma...

7 Mohammad ali Javidian, et al. ∙

research

∙ 01/18/2020

FlexiBO: Cost-Aware Multi-Objective Optimization of Deep Neural Networks

One of the key challenges in designing machine learning systems is to de...

21 Md Shahriar Iqbal, et al. ∙

research

∙ 01/02/2020

Ensembles of Many Diverse Weak Defenses can be Strong: Defending Deep Neural Networks Against Adversarial Attacks

Despite achieving state-of-the-art performance across many domains, mach...

13 Ying Meng, et al. ∙

research

∙ 11/01/2019

Whence to Learn? Transferring Knowledge in Configurable Systems using BEETLE

As software systems grow in complexity and the space of possible configu...

0 Rahul Krishna, et al. ∙

research

∙ 10/24/2019

How Do Code Changes Evolve in Different Platforms? A Mining-based Investigation

Code changes are performed differently in the mobile and non-mobile plat...

0 Markos Viggiato, et al. ∙

research

∙ 10/22/2019

Kuksa: A Cloud-Native Architecture for Enabling Continuous Delivery in the Automotive Domain

Connecting vehicles to cloud platforms has enabled innovative business s...

0 Ahmad Banijamali, et al. ∙

research

∙ 10/17/2019

Developing Self-Adaptive Microservice Systems: Challenges and Directions

A self-adaptive system can dynamically monitor and adapt its behavior to...

0 Nabor C. Mendonca, et al. ∙

research

∙ 10/01/2019

Order-Independent Structure Learning of Multivariate Regression Chain Graphs

This paper deals with multivariate regression chain graphs (MVR CGs), wh...

0 Mohammad ali Javidian, et al. ∙

research

∙ 07/02/2019

Conservative Q-Improvement: Reinforcement Learning for an Interpretable Decision-Tree Policy

There is a growing desire in the field of reinforcement learning (and ma...

2 Aaron M. Roth, et al. ∙

research

∙ 05/06/2019

ConfigCrusher: White-Box Performance Analysis for Configurable Systems

In configurable software systems, stakeholders are often interested in k...

0 Miguel Velez, et al. ∙

research

∙ 04/04/2019

Transfer Learning for Performance Modeling of Deep Neural Network Systems

Modern deep neural network (DNN) systems are highly configurable with la...

0 Md Shahriar Iqbal, et al. ∙

research

∙ 03/10/2019

Machine Learning Meets Quantitative Planning: Enabling Self-Adaptation in Autonomous Robots

Modern cyber-physical systems (e.g., robotics systems) are typically com...

0 Pooyan Jamshidi, et al. ∙

research

∙ 02/26/2019

Transfer Learning for Performance Modeling of Configurable Systems: A Causal Analysis

Modern systems (e.g., deep neural networks, big data analytics, and comp...

0 Mohammad ali Javidian, et al. ∙

research

∙ 08/21/2018

How is Performance Addressed in DevOps? A Survey on Industrial Practices

DevOps is a modern software engineering paradigm that is gaining widespr...

0 Cor-Paul Bezemer, et al. ∙

research

∙ 03/11/2018

Transfer Learning with Bellwethers to find Good Configurations

As software systems grow in complexity, the space of possible configurat...

0 Vivek Nair, et al. ∙

research

∙ 01/15/2018

An Efficient Method for Uncertainty Propagation in Robust Software Performance Estimation

Software engineers often have to estimate the performance of a software ...

0 Aldeida Aleti, et al. ∙

research

∙ 09/26/2017

Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World

This report documents the program and the outcomes of GI-Dagstuhl Semina...

0 Andre van Hoorn, et al. ∙

research

∙ 09/07/2017

Transfer Learning for Performance Modeling of Configurable Systems: An Exploratory Analysis

Modern software systems provide many configuration options which signifi...

0 Pooyan Jamshidi, et al. ∙

research

∙ 05/19/2017

A Comparison of Reinforcement Learning Techniques for Fuzzy Cloud Auto-Scaling

A goal of cloud service management is to design self-adaptable auto-scal...

0 Hamid Arabnejad, et al. ∙

Pooyan Jamshidi

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