4 Search Results for "Agarwal, Udit"

Document
Research
DOI: 10.4230/TGDK.4.1.1
On the Computational Cost of Knowledge Graph Embeddings

Authors: Victor Charpenay, Mansour Zoubeirou A Mayaki, and Antoine Zimmermann

Published in: TGDK, Volume 4, Issue 1 (2026). Transactions on Graph Data and Knowledge, Volume 4, Issue 1

Abstract
Over a decade, numerous Knowledge Graph Embedding (KGE) models have been designed and evaluated on reference datasets, always with increasing performance. In this paper, we re-evaluate these models with respect to their computational efficiency during training, by estimating the computational cost of the procedure expressed in floating-point operations. We design a cost model based on analytical expressions and apply it on a collection of 20 KGE models, representative of the state-of-the-art. We show that dimensionality or parameter efficiency, used in the literature to compare models with each other, are not suitable to evaluate the true cost of models. Through fixed-budget experiments, a novel approach to evaluate KGE models based on cost estimates, we re-assess the relative performance of model families compared to the state-of-the-art. Bilinear models such as ComplEx underperform with a low computational budget while hyperbolic linear models appear to offer no particular benefit compared to simpler Euclidian models, especially the MuRE model. Neural models, such as ConvE or CompGCN, achieve reasonable performance in the literature but their high computational cost appears unnecessary when compared with other models. The trade-off between efficiency and expressivity of both linear and neural models is to be further explored.
Cite as

Victor Charpenay, Mansour Zoubeirou A Mayaki, and Antoine Zimmermann. On the Computational Cost of Knowledge Graph Embeddings. In Transactions on Graph Data and Knowledge (TGDK), Volume 4, Issue 1, pp. 1:1-1:30, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@Article{charpenay_et_al:TGDK.4.1.1,
  author =	{Charpenay, Victor and Zoubeirou A Mayaki, Mansour and Zimmermann, Antoine},
  title =	{{On the Computational Cost of Knowledge Graph Embeddings}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{1:1--1:30},
  ISSN =	{2942-7517},
  year =	{2026},
  volume =	{4},
  number =	{1},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.4.1.1},
  URN =		{urn:nbn:de:0030-drops-256863},
  doi =		{10.4230/TGDK.4.1.1},
  annote =	{Keywords: Knowledge Graph Embedding, Parameter Efficiency, Computational Budget, Green AI}
}
Document
DOI: 10.4230/LIPIcs.SEA.2025.17
Computing the Exact Radius of Large Graphs

Authors: Stefan Funke, Claudius Proissl, and Sabine Storandt

Published in: LIPIcs, Volume 338, 23rd International Symposium on Experimental Algorithms (SEA 2025)

Abstract
The radius of a graph is an important structural parameter which plays a key role in social network analysis and related applications. It measures the minimum shortest path distance that is required to reach all nodes in the graph from a single node. A node from which all other nodes are within a distance equal to the radius is called a center of the graph. In a graph with n nodes and m edges, the center and the radius can be determined in Õ(nm) by computing shortest path distances between all pairs of nodes. Fine-grained complexity results suggest that asymptotically faster algorithms are unlikely to exist. In this paper, we describe a novel randomized algorithm for exact radius computation in weighted digraphs with an expected running time in Õ(d³m) where d is the so-called combinatorial dimension. Our methodology is inspired by Clarkson’s algorithm for LP-type problems. The value of d denotes the size of a basis, which is a smallest subset of nodes which enforce the same radius as the whole node set. While we show that there exist graphs with d ∈ Θ(n), our empirical analysis reveals that even large real-world graphs have small combinatorial dimension. This allows us to compute the radius in near-linear time on such instances. The significantly improved scalability can be clearly observed in our experimental evaluation on a diverse set of benchmark graphs.
Cite as

Stefan Funke, Claudius Proissl, and Sabine Storandt. Computing the Exact Radius of Large Graphs. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 17:1-17:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{funke_et_al:LIPIcs.SEA.2025.17,
  author =	{Funke, Stefan and Proissl, Claudius and Storandt, Sabine},
  title =	{{Computing the Exact Radius of Large Graphs}},
  booktitle =	{23rd International Symposium on Experimental Algorithms (SEA 2025)},
  pages =	{17:1--17:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-375-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{338},
  editor =	{Mutzel, Petra and Prezza, Nicola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.17},
  URN =		{urn:nbn:de:0030-drops-232555},
  doi =		{10.4230/LIPIcs.SEA.2025.17},
  annote =	{Keywords: Radius, Graph Center, LP-type, Combinatorial Dimension}
}
Document
DOI: 10.4230/LIPIcs.ECRTS.2025.3
Enabling Containerisation of Distributed Applications with Real-Time Constraints

Authors: Nasim Samimi, Luca Abeni, Daniel Casini, Mauro Marinoni, Twan Basten, Mitra Nasri, Marc Geilen, and Alessandro Biondi

Published in: LIPIcs, Volume 335, 37th Euromicro Conference on Real-Time Systems (ECRTS 2025)

Abstract
Containerisation is becoming a cornerstone of modern distributed systems, thanks to their lightweight virtualisation, high portability, and seamless integration with orchestration tools such as Kubernetes. The usage of containers has also gained traction in real-time cyber-physical systems, such as software-defined vehicles, which are characterised by strict timing requirements to ensure safety and performance. Nevertheless, ensuring real-time execution of co-located containers is challenging because of mutual interference due to the sharing of the same processing hardware. Existing parallel computing frameworks such as Ray and its Kubernetes-enabled variant, KubeRay, excel in distributed computation but lack support for scheduling policies that allow guaranteeing real-time timing constraints and CPU resource isolation between containers, such as the SCHED_DEADLINE policy of Linux. To fill this gap, this paper extends Ray to support real-time containers that leverage SCHED_DEADLINE. To this end, we propose KubeDeadline, a novel, modular Kubernetes extension to support SCHED_DEADLINE. We evaluate our approach through extensive experiments, using synthetic workloads and a case study based on the MobileNet and EfficientNet deep neural networks. Our evaluation shows that KubeDeadline ensures deadline compliance in all synthetic workloads, adds minimal deployment overhead (in the order of milliseconds), and achieves lower worst-case response times, up to 4 times lower, than vanilla Kubernetes under background interference.
Cite as

Nasim Samimi, Luca Abeni, Daniel Casini, Mauro Marinoni, Twan Basten, Mitra Nasri, Marc Geilen, and Alessandro Biondi. Enabling Containerisation of Distributed Applications with Real-Time Constraints. In 37th Euromicro Conference on Real-Time Systems (ECRTS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 335, pp. 3:1-3:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{samimi_et_al:LIPIcs.ECRTS.2025.3,
  author =	{Samimi, Nasim and Abeni, Luca and Casini, Daniel and Marinoni, Mauro and Basten, Twan and Nasri, Mitra and Geilen, Marc and Biondi, Alessandro},
  title =	{{Enabling Containerisation of Distributed Applications with Real-Time Constraints}},
  booktitle =	{37th Euromicro Conference on Real-Time Systems (ECRTS 2025)},
  pages =	{3:1--3:29},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-377-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{335},
  editor =	{Mancuso, Renato},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2025.3},
  URN =		{urn:nbn:de:0030-drops-235816},
  doi =		{10.4230/LIPIcs.ECRTS.2025.3},
  annote =	{Keywords: Kubernetes, real-time containers, SCHED\underlineDEADLINE, KubeRay}
}
Document
DOI: 10.4230/LIPIcs.ISAAC.2016.8
Finding k Simple Shortest Paths and Cycles

Authors: Udit Agarwal and Vijaya Ramachandran

Published in: LIPIcs, Volume 64, 27th International Symposium on Algorithms and Computation (ISAAC 2016)

Abstract
We present algorithms and techniques for several problems related to finding multiple simple shortest paths and cycles in a graph. Our main result is a new algorithm for finding k simple shortest paths for all pairs of vertices in a weighted directed graph G = (V, E). For k = 2 our algorithm runs in O(mn + n^2 log n) time where m and n are the number of edges and vertices in G. For k = 3 our algorithm runs in O(mn^2 + n^3 log n) time, which is almost a factor of n faster than the best previous algorithm. Our approach is based on forming suitable path extensions to find simple shortest paths; this method is different from the 'detour finding' technique used in most of the prior work on simple shortest paths, replacement paths, and distance sensitivity oracles. We present new algorithms for generating simple cycles and simple paths in G in non-decreasing order of their weight. The algorithm for generating simple paths is much faster,and uses another variant of path extensions.
Cite as

Udit Agarwal and Vijaya Ramachandran. Finding k Simple Shortest Paths and Cycles. In 27th International Symposium on Algorithms and Computation (ISAAC 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 64, pp. 8:1-8:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@InProceedings{agarwal_et_al:LIPIcs.ISAAC.2016.8,
  author =	{Agarwal, Udit and Ramachandran, Vijaya},
  title =	{{Finding k Simple Shortest Paths and Cycles}},
  booktitle =	{27th International Symposium on Algorithms and Computation (ISAAC 2016)},
  pages =	{8:1--8:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-026-2},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{64},
  editor =	{Hong, Seok-Hee},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ISAAC.2016.8},
  URN =		{urn:nbn:de:0030-drops-67830},
  doi =		{10.4230/LIPIcs.ISAAC.2016.8},
  annote =	{Keywords: Graph Algorithms, Shortest Paths, k Simple Shortest Paths, Enumerat- ing Simple Cycles, Enumerating Simple Paths}
}
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