6 Search Results for "Wang, Weihang"

Document
Survey
DOI: 10.4230/TGDK.3.2.1
Resilience in Knowledge Graph Embeddings

Authors: Arnab Sharma, N'Dah Jean Kouagou, and Axel-Cyrille Ngonga Ngomo

Published in: TGDK, Volume 3, Issue 2 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 2

Abstract
In recent years, knowledge graphs have gained interest and witnessed widespread applications in various domains, such as information retrieval, question-answering, recommendation systems, amongst others. Large-scale knowledge graphs to this end have demonstrated their utility in effectively representing structured knowledge. To further facilitate the application of machine learning techniques, knowledge graph embedding models have been developed. Such models can transform entities and relationships within knowledge graphs into vectors. However, these embedding models often face challenges related to noise, missing information, distribution shift, adversarial attacks, etc. This can lead to sub-optimal embeddings and incorrect inferences, thereby negatively impacting downstream applications. While the existing literature has focused so far on adversarial attacks on KGE models, the challenges related to the other critical aspects remain unexplored. In this paper, we, first of all, give a unified definition of resilience, encompassing several factors such as generalisation, in-distribution generalization, distribution adaption, and robustness. After formalizing these concepts for machine learning in general, we define them in the context of knowledge graphs. To find the gap in the existing works on resilience in the context of knowledge graphs, we perform a systematic survey, taking into account all these aspects mentioned previously. Our survey results show that most of the existing works focus on a specific aspect of resilience, namely robustness. After categorizing such works based on their respective aspects of resilience, we discuss the challenges and future research directions.
Cite as

Arnab Sharma, N'Dah Jean Kouagou, and Axel-Cyrille Ngonga Ngomo. Resilience in Knowledge Graph Embeddings. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 2, pp. 1:1-1:38, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@Article{sharma_et_al:TGDK.3.2.1,
  author =	{Sharma, Arnab and Kouagou, N'Dah Jean and Ngomo, Axel-Cyrille Ngonga},
  title =	{{Resilience in Knowledge Graph Embeddings}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{1:1--1:38},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.2.1},
  URN =		{urn:nbn:de:0030-drops-248117},
  doi =		{10.4230/TGDK.3.2.1},
  annote =	{Keywords: Knowledge graphs, Resilience, Robustness}
}
Document
DOI: 10.4230/OASIcs.ICPEC.2025.14
In-Browser C++ Interpreter for Lightweight Intelligent Programming Learning Environments

Authors: Tomas Blažauskas, Arnoldas Rauba, Jakub Swacha, Raffaele Montella, and Rytis Maskeliunas

Published in: OASIcs, Volume 133, 6th International Computer Programming Education Conference (ICPEC 2025)

Abstract
The paper presents a browser native C++ interpreter integrated into an AI-assisted educational platform designed to enhance programming learning in formal education. The interpreter leverages Parsing Expression Grammars (PEG) to generate Abstract Syntax Trees (AST) and executes C++ code using a TypeScript-based runtime. The system supports key C++ features, including pointer arithmetic, function overloading, and namespace resolution, and emulates memory management via reference-counted JavaScript objects. Integrated within a web-based learning environment, it provides automated feedback, error explanations, and code quality evaluations. The evaluation involved 4582 students in three difficulty levels and feedback from 14 teachers. The results include high system usability scale (SUS) scores (avg. 83.5) and WBLT learning effectiveness scores (avg. 4.58/5). Interpreter performance testing in 65 cases averaged under 10 ms per task, confirming its practical applicability to school curricula. The system supports SCORM and PWA deployment, enabling LMS-independent usage. The work introduces a technical innovation in browser-based C++ execution and a scalable framework for LLM-enhanced programming pedagogy.
Cite as

Tomas Blažauskas, Arnoldas Rauba, Jakub Swacha, Raffaele Montella, and Rytis Maskeliunas. In-Browser C++ Interpreter for Lightweight Intelligent Programming Learning Environments. In 6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 14:1-14:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{blazauskas_et_al:OASIcs.ICPEC.2025.14,
  author =	{Bla\v{z}auskas, Tomas and Rauba, Arnoldas and Swacha, Jakub and Montella, Raffaele and Maskeliunas, Rytis},
  title =	{{In-Browser C++ Interpreter for Lightweight Intelligent Programming Learning Environments}},
  booktitle =	{6th International Computer Programming Education Conference (ICPEC 2025)},
  pages =	{14:1--14:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-393-5},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{133},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Portela, Filipe and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2025.14},
  URN =		{urn:nbn:de:0030-drops-240449},
  doi =		{10.4230/OASIcs.ICPEC.2025.14},
  annote =	{Keywords: C++ interpreter, browser-based execution, programming education, LLM-assisted learning, PEG, AST, TypeScript runtime}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2025.23
Wastrumentation: Portable WebAssembly Dynamic Analysis with Support for Intercession

Authors: Aäron Munsters, Angel Luis Scull Pupo, and Elisa Gonzalez Boix

Published in: LIPIcs, Volume 333, 39th European Conference on Object-Oriented Programming (ECOOP 2025)

Abstract
Dynamic program analyses help in understanding a program’s runtime behavior and detect issues related to security, program comprehension, or profiling. Instrumentation platforms aid analysis developers by offering a high-level API to write the analysis, and inserting the analysis into the target program. However, current instrumentation platforms for WebAssembly (Wasm) restrict analysis portability because they require concrete runtime environments. Moreover, their analysis API only allows the development of analyses that observe the target program but cannot modify it. As a result, many popular dynamic analyses present for other languages, such as runtime hardening, virtual patching or runtime optimization, cannot currently be implemented for Wasm atop a dynamic analysis platform. Instead, they need to be built manually, which requires knowledge of low-level details of the Wasm’s semantics and instruction set, and how to safely manipulate it. This paper introduces Wastrumentation, the first dynamic analysis platform for WebAssembly that supports intercession. Our solution, based on source code instrumentation, weaves the analysis code directly into the target program code. Inlining the analysis into the target’s source code avoids dependencies on the runtime environment, making analyses portable across Wasm VMs. Moreover, it enables the implementation of analyses in any Wasm-compatible language. We evaluate our solution in two ways. First, we compare it against a state-of-the-art source code instrumentation platform using the WasmR3 benchmarks. The results show improved memory consumption and competitive performance overhead. Second, we develop an extensive portfolio of dynamic analyses, including novel analyses previously unattainable with source code instrumentation platforms, such as memoization, safe heap access, and the removal of NaN non-determinism.
Cite as

Aäron Munsters, Angel Luis Scull Pupo, and Elisa Gonzalez Boix. Wastrumentation: Portable WebAssembly Dynamic Analysis with Support for Intercession. In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 23:1-23:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{munsters_et_al:LIPIcs.ECOOP.2025.23,
  author =	{Munsters, A\"{a}ron and Scull Pupo, Angel Luis and Gonzalez Boix, Elisa},
  title =	{{Wastrumentation: Portable WebAssembly Dynamic Analysis with Support for Intercession}},
  booktitle =	{39th European Conference on Object-Oriented Programming (ECOOP 2025)},
  pages =	{23:1--23:29},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-373-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{333},
  editor =	{Aldrich, Jonathan and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2025.23},
  URN =		{urn:nbn:de:0030-drops-233153},
  doi =		{10.4230/LIPIcs.ECOOP.2025.23},
  annote =	{Keywords: WebAssembly, dynamic analysis, instrumentation platform, intercession}
}
Document
APPROX
DOI: 10.4230/LIPIcs.APPROX/RANDOM.2023.3
Approximating Submodular k-Partition via Principal Partition Sequence

Authors: Karthekeyan Chandrasekaran and Weihang Wang

Published in: LIPIcs, Volume 275, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2023)

Abstract
In submodular k-partition, the input is a submodular function f:2^V → ℝ_{≥ 0} (given by an evaluation oracle) along with a positive integer k and the goal is to find a partition of the ground set V into k non-empty parts V_1, V_2, …, V_k in order to minimize ∑_{i=1}^k f(V_i). Narayanan, Roy, and Patkar [Narayanan et al., 1996] designed an algorithm for submodular k-partition based on the principal partition sequence and showed that the approximation factor of their algorithm is 2 for the special case of graph cut functions (which was subsequently rediscovered by Ravi and Sinha [R. Ravi and A. Sinha, 2008]). In this work, we study the approximation factor of their algorithm for three subfamilies of submodular functions - namely monotone, symmetric, and posimodular and show the following results: 1) The approximation factor of their algorithm for monotone submodular k-partition is 4/3. This result improves on the 2-factor that was known to be achievable for monotone submodular k-partition via other algorithms. Moreover, our upper bound of 4/3 matches the recently shown lower bound under polynomial number of function evaluation queries [Santiago, 2021]. Our upper bound of 4/3 is also the first improvement beyond 2 for a certain graph partitioning problem that is a special case of monotone submodular k-partition. 2) The approximation factor of their algorithm for symmetric submodular k-partition is 2. This result generalizes their approximation factor analysis beyond graph cut functions. 3) The approximation factor of their algorithm for posimodular submodular k-partition is 2. We also construct an example to show that the approximation factor of their algorithm for arbitrary submodular functions is Ω(n/k).
Cite as

Karthekeyan Chandrasekaran and Weihang Wang. Approximating Submodular k-Partition via Principal Partition Sequence. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 275, pp. 3:1-3:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

Copy BibTex To Clipboard

@InProceedings{chandrasekaran_et_al:LIPIcs.APPROX/RANDOM.2023.3,
  author =	{Chandrasekaran, Karthekeyan and Wang, Weihang},
  title =	{{Approximating Submodular k-Partition via Principal Partition Sequence}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2023)},
  pages =	{3:1--3:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-296-9},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{275},
  editor =	{Megow, Nicole and Smith, Adam},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2023.3},
  URN =		{urn:nbn:de:0030-drops-188284},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2023.3},
  annote =	{Keywords: Approximation algorithms}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2022.16
Counting and Enumerating Optimum Cut Sets for Hypergraph k-Partitioning Problems for Fixed k

Authors: Calvin Beideman, Karthekeyan Chandrasekaran, and Weihang Wang

Published in: LIPIcs, Volume 229, 49th International Colloquium on Automata, Languages, and Programming (ICALP 2022)

Abstract
We consider the problem of enumerating optimal solutions for two hypergraph k-partitioning problems - namely, Hypergraph-k-Cut and Minmax-Hypergraph-k-Partition. The input in hypergraph k-partitioning problems is a hypergraph G = (V, E) with positive hyperedge costs along with a fixed positive integer k. The goal is to find a partition of V into k non-empty parts (V₁, V₂, …, V_k) - known as a k-partition - so as to minimize an objective of interest. 1) If the objective of interest is the maximum cut value of the parts, then the problem is known as Minmax-Hypergraph-k-Partition. A subset of hyperedges is a minmax-k-cut-set if it is the subset of hyperedges crossing an optimum k-partition for Minmax-Hypergraph-k-Partition. 2) If the objective of interest is the total cost of hyperedges crossing the k-partition, then the problem is known as Hypergraph-k-Cut. A subset of hyperedges is a min-k-cut-set if it is the subset of hyperedges crossing an optimum k-partition for Hypergraph-k-Cut. We give the first polynomial bound on the number of minmax-k-cut-sets and a polynomial-time algorithm to enumerate all of them in hypergraphs for every fixed k. Our technique is strong enough to also enable an n^{O(k)}p-time deterministic algorithm to enumerate all min-k-cut-sets in hypergraphs, thus improving on the previously known n^{O(k²)}p-time deterministic algorithm, where n is the number of vertices and p is the size of the hypergraph. The correctness analysis of our enumeration approach relies on a structural result that is a strong and unifying generalization of known structural results for Hypergraph-k-Cut and Minmax-Hypergraph-k-Partition. We believe that our structural result is likely to be of independent interest in the theory of hypergraphs (and graphs).
Cite as

Calvin Beideman, Karthekeyan Chandrasekaran, and Weihang Wang. Counting and Enumerating Optimum Cut Sets for Hypergraph k-Partitioning Problems for Fixed k. In 49th International Colloquium on Automata, Languages, and Programming (ICALP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 229, pp. 16:1-16:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

Copy BibTex To Clipboard

@InProceedings{beideman_et_al:LIPIcs.ICALP.2022.16,
  author =	{Beideman, Calvin and Chandrasekaran, Karthekeyan and Wang, Weihang},
  title =	{{Counting and Enumerating Optimum Cut Sets for Hypergraph k-Partitioning Problems for Fixed k}},
  booktitle =	{49th International Colloquium on Automata, Languages, and Programming (ICALP 2022)},
  pages =	{16:1--16:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-235-8},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{229},
  editor =	{Boja\'{n}czyk, Miko{\l}aj and Merelli, Emanuela and Woodruff, David P.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2022.16},
  URN =		{urn:nbn:de:0030-drops-163578},
  doi =		{10.4230/LIPIcs.ICALP.2022.16},
  annote =	{Keywords: hypergraphs, k-partitioning, counting, enumeration}
}
Document
DOI: 10.4230/LIPIcs.ESA.2021.29
𝓁_p-Norm Multiway Cut

Authors: Karthekeyan Chandrasekaran and Weihang Wang

Published in: LIPIcs, Volume 204, 29th Annual European Symposium on Algorithms (ESA 2021)

Abstract
We introduce and study 𝓁_p-norm-multiway-cut: the input here is an undirected graph with non-negative edge weights along with k terminals and the goal is to find a partition of the vertex set into k parts each containing exactly one terminal so as to minimize the 𝓁_p-norm of the cut values of the parts. This is a unified generalization of min-sum multiway cut (when p = 1) and min-max multiway cut (when p = ∞), both of which are well-studied classic problems in the graph partitioning literature. We show that 𝓁_p-norm-multiway-cut is NP-hard for constant number of terminals and is NP-hard in planar graphs. On the algorithmic side, we design an O(log² n)-approximation for all p ≥ 1. We also show an integrality gap of Ω(k^{1-1/p}) for a natural convex program and an O(k^{1-1/p-ε})-inapproximability for any constant ε > 0 assuming the small set expansion hypothesis.
Cite as

Karthekeyan Chandrasekaran and Weihang Wang. 𝓁_p-Norm Multiway Cut. In 29th Annual European Symposium on Algorithms (ESA 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 204, pp. 29:1-29:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

Copy BibTex To Clipboard

@InProceedings{chandrasekaran_et_al:LIPIcs.ESA.2021.29,
  author =	{Chandrasekaran, Karthekeyan and Wang, Weihang},
  title =	{{𝓁\underlinep-Norm Multiway Cut}},
  booktitle =	{29th Annual European Symposium on Algorithms (ESA 2021)},
  pages =	{29:1--29:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-204-4},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{204},
  editor =	{Mutzel, Petra and Pagh, Rasmus and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2021.29},
  URN =		{urn:nbn:de:0030-drops-146103},
  doi =		{10.4230/LIPIcs.ESA.2021.29},
  annote =	{Keywords: multiway cut, approximation algorithms}
}
  • Refine by Type
  • 6 Document/PDF
  • 3 Document/HTML

  • Refine by Publication Year
  • 3 2025
  • 1 2023
  • 1 2022
  • 1 2021

  • Refine by Author
  • 3 Chandrasekaran, Karthekeyan
  • 3 Wang, Weihang
  • 1 Beideman, Calvin
  • 1 Blažauskas, Tomas
  • 1 Gonzalez Boix, Elisa
  • Show More...

  • Refine by Series/Journal
  • 4 LIPIcs
  • 1 OASIcs
  • 1 TGDK

  • Refine by Classification
  • 2 Theory of computation → Approximation algorithms analysis
  • 1 Computing methodologies → Reasoning about belief and knowledge
  • 1 Information systems → Web applications
  • 1 Security and privacy → Information flow control
  • 1 Software and its engineering → Dynamic analysis
  • Show More...

  • Refine by Keyword
  • 1 AST
  • 1 Approximation algorithms
  • 1 C++ interpreter
  • 1 Knowledge graphs
  • 1 LLM-assisted learning
  • Show More...

Any Issues?
X

Feedback on the Current Page

CAPTCHA

Thanks for your feedback!

Feedback submitted to Dagstuhl Publishing

Could not send message

Please try again later or send an E-mail
© 2023-2026 Schloss Dagstuhl – LZI GmbH Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact