18 citations · 31 across the 13 of their papers we have counts for
14 papers
Android App Feature Extraction: A review of approaches for malware and app similarity detection
Simon Torka, Sahin Albayrak
This paper reviews work published between 2002 and 2022 in the fields of Android malware, clone, and similarity detection. It examines the data sources, tools, and features used in…
Optimizing AI-Assisted Code Generation
Simon Torka, Sahin Albayrak
In recent years, the rise of AI-assisted code-generation tools has significantly transformed software development. While code generators have mainly been used to support convention…
ALPACA -- Adaptive Learning Pipeline for Comprehensive AI
Simon Torka, Sahin Albayrak
The advancement of AI technologies has greatly increased the complexity of AI pipelines as they include many stages such as data collection, pre-processing, training, evaluation an…
LaFAM: Unsupervised Feature Attribution with Label-free Activation Maps
Aray Karjauv, Sahin Albayrak
Convolutional Neural Networks (CNNs) are known for their ability to learn hierarchical structures, naturally developing detectors for objects, and semantic concepts within their de…
Predictive Prescription of Unit Commitment Decisions Under Net Load Uncertainty
Ogun Yurdakul, Feng Qiu, Sahin Albayrak
To take unit commitment (UC) decisions under uncertain net load, most studies utilize a stochastic UC (SUC) model that adopts a one-size-fits-all representation of uncertainty. Dis…
Adaptive Stochastic Optimisation of Nonconvex Composite Objectives
Weijia Shao, Fikret Sivrikaya, Sahin Albayrak
In this paper, we propose and analyse a family of generalised stochastic composite mirror descent algorithms. With adaptive step sizes, the proposed algorithms converge without req…
Adaptive Zeroth-Order Optimisation of Nonconvex Composite Objectives
Weijia Shao, Sahin Albayrak
In this paper, we propose and analyze algorithms for zeroth-order optimization of non-convex composite objectives, focusing on reducing the complexity dependence on dimensionality.…
Optimistic Optimisation of Composite Objective with Exponentiated Update
Weijia Shao, Fikret Sivrikaya, Sahin Albayrak
This paper proposes a new family of algorithms for the online optimisation of composite objectives. The algorithms can be interpreted as the combination of the exponentiated gradie…
FABRIC: A Framework for the Design and Evaluation of Collaborative Robots with Extended Human Adaptation
O. Can Görür, Benjamin Rosman, Fikret Sivrikaya +1
A limitation for collaborative robots (cobots) is their lack of ability to adapt to human partners, who typically exhibit an immense diversity of behaviors. We present an autonomou…
Quantification of the Impact of GHG Emissions on Unit Commitment in Microgrids
Ogun Yurdakul, Fikret Sivrikaya, Sahin Albayrak
The global climate change creates a dire need to mitigate greenhouse gas (GHG) emissions from thermal generation resources (TGRs). While microgrids are instrumental in enabling the…
Forecasting Daily Primary Three-Hour Net Load Ramps in the CAISO System
Ogun Yurdakul, Andreas Meyer, Fikret Sivrikaya +1
The deepening penetration of variable energy resources creates unprecedented challenges for system operators (SOs). An issue that merits special attention is the precipitous net lo…
Kullback-Leibler Divergence-Based Distributionally Robust Unit Commitment Under Net Load Uncertainty
Ogun Yurdakul, Fikret Sivrikaya, Sahin Albayrak
The deepening penetration of renewable resources into power systems entails great difficulties that have not been surmounted satisfactorily. An issue that merits special attention…
A Distributionally Robust Optimization Approach for Unit Commitment in Microgrids
Ogun Yurdakul, Fikret Sivrikaya, Sahin Albayrak
This paper proposes a distributionally robust unit commitment approach for microgrids under net load and electricity market price uncertainty. The key thrust of the proposed approa…
The Link Prediction Problem in Bipartite Networks
Jérôme Kunegis, Ernesto W. De Luca, Sahin Albayrak
We define and study the link prediction problem in bipartite networks, specializing general link prediction algorithms to the bipartite case. In a graph, a link prediction function…