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Publikationer

De 50 senaste publikationerna från avdelningen för programvaruteknik och datorsystem:

[1]
H. Boström, "Testing Exchangeability for Multiple Sequences of P-values," i Proceedings of the 14th Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2025, 2025, s. 615-632.
[2]
Z. Li och H. Boström, "FlowGuard: Guarding Flow Matching via Conformal Sampling," i Proceedings of the 14th Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2025, 2025, s. 775-777.
[3]
G. Dong, R. Bresson och H. Boström, "Detecting Attacks with Conformal Test Martingales," i Proceedings of the 14th Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2025, 2025, s. 758-761.
[4]
K. Hammerfald et al., "Leveraging large language models to identify microcounseling skills in psychotherapy transcripts," Psychotherapy Research, s. 1-19, 2025.
[5]
W. Liu och P. Papadimitratos, "Guardian Positioning System (GPS) for Location Based Services," i WiSec 2025 - Proceedings of the 18th ACM Conference on Security and Privacy in Wireless and Mobile Networks, 2025, s. 88-99.
[6]
E. Ståhl et al., "On the Benefits of Predictable Traffic in Virtual Switches: A Case Study," i ANRW 2025 - Proceedings of the 2025 Applied Networking Research Workshop, 2025, s. 113-119.
[7]
V. Gulisano et al., "Foreword," i Debs 2025 Proceedings of the 19th ACM International Conference on Distributed and Event Based Systems, 2025, s. vi-vii.
[8]
W. Liu och P. Papadimitratos, "Self-supervised federated GNSS spoofing detection with opportunistic data," i 2025 IEEE/ION Position, Location and Navigation Symposium, PLANS 2025, 2025, s. 381-390.
[9]
W. Liu och P. Papadimitratos, "GNSS Spoofing Detection Based on Opportunistic Position Information," IEEE Internet of Things Journal, 2025.
[10]
Z. Zhou, H. Jin och P. Papadimitratos, "Clogging DoS Resilient Bootstrapping of Efficient V2V Validation," i 40th Annual ACM Symposium On Applied Computing, 2025, s. 1857-1866.
[11]
Y. Liu et al., "Detecting and removing bloated dependencies in CommonJS packages," Journal of Systems and Software, vol. 230, 2025.
[12]
M. Siavashi et al., "Priority-Aware Preemptive Scheduling for Mixed-Priority Workloads in MoE Inference," i Proceedings of the 2025 The 5th Workshop On Machine Learning And Systems, EUROMLSYS 2025, 2025, s. 132-138.
[13]
H. Jin och P. Papadimitratos, "Accountable, Scalable and DoS-resilient Secure Vehicular Communication," Computers & Security, vol. 156, 2025.
[14]
G. Dong et al., "Obtaining Example-Based Explanations from Deep Neural Networks," i Advances in Intelligent Data Analysis XXIII - 23rd International Symposium on Intelligent Data Analysis, IDA 2025, Proceedings, 2025, s. 432-443.
[15]
A. Rao, "Practical Machine Learning for Predictions in Mobile Networks," Doktorsavhandling Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2025:64, 2025.
[16]
G. Verardo et al., "Reducing the Number of Leads for ECG Imaging with Graph Neural Networks and Meaningful Latent Space," i Statistical Atlases and Computational Models of the Heart. Workshop, CMRxRecon and MBAS Challenge Papers. - 15th International Workshop, STACOM 2024, Held in Conjunction with MICCAI 2024, Revised Selected Papers, 2025, s. 301-312.
[17]
S. Ennadir et al., "Expressivity of Representation Learning on Continuous-Time Dynamic Graphs: An Information-Flow Centric Review," Transactions on Machine Learning Research, vol. 2025-April, 2025.
[18]
C. Ottaviani et al., "Advanced Routing Strategies for LEO and VLEO Constellations : Ensuring Polar Coverage," i 2025 12th Advanced Satellite Multimedia Systems Conference and the 18th Signal Processing for Space Communications Workshop, ASMS/SPSC 2025, 2025.
[19]
M. I. Al Hafiz et al., "A Reconfigurable Stream-Based FPGA Accelerator for Bayesian Confidence Propagation Neural Networks," i Applied Reconfigurable Computing. Architectures, Tools, and Applications - 21st International Symposium, ARC 2025, Proceedings, 2025, s. 196-213.
[20]
L. Bahri, B. Carminati och E. Ferrari, "Privacy-Aware Access Control in Decentralized Online Social Networks," i Encyclopedia of Cryptography, Security and Privacy, Third Edition, : Springer Nature, 2025, s. 1924-1927.
[21]
P. Papadimitratos, "Mix-Zones in Wireless Mobile Networks," i Encyclopedia of Cryptography, Security and Privacy, Sushil Jajodia, Pierangela Samarati, Moti Yung red., 3. uppl. : Springer Nature, 2025, s. 1555-1559.
[22]
R. Yadav et al., "Automatic Tracing in Task-Based Runtime Systems," i ASPLOS 2025 - Proceedings of the 30th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2025, s. 84-99.
[23]
V. Andersson et al., "UPPERCASE IS ALL YOU NEED," i SIGBOVIK : A Record of the Proceedings of SIGBOVIK 2025, 2025, s. 24-35.
[24]
G. Shang et al., "Atlas-Chat : Adapting Large Language Models for Low-Resource Moroccan Arabic Dialect," i LoResLM 2025 - 1st Workshop on Language Models for Low-Resource Languages, Proceedings of the Workshop, 2025, s. 9-30.
[25]
A. E. Samy, Z. T. Kefato och Š. Girdzijauskas, "Leap : Inductive Link Prediction via Learnable Topology Augmentation," i Machine Learning, Optimization, and Data Science - 10th International Conference, LOD 2024, Revised Selected Papers, 2025, s. 448-463.
[26]
V. Komini och S. Girdzijauskas, "Integrating Logit Space Embeddings for Reliable Out-of-Distribution Detection," i Machine Learning, Optimization, and Data Science - 10th International Conference, LOD 2024, Revised Selected Papers, 2025, s. 255-269.
[27]
R. Bresson et al., "KAGNNs : Kolmogorov-Arnold Networks meet Graph Learning," Transactions on Machine Learning Research, vol. 2025-March, s. 1-29, 2025.
[28]
M. Spanghero, "Data verification for GNSS systems and protection of GNSS services," Doktorsavhandling Stockholm, Sweden : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2025:36, 2025.
[29]
M. Spanghero et al., "GNSS jammer localization and identification with airborne commercial GNSS receivers," IEEE Transactions on Information Forensics and Security, vol. 20, s. 3550-3565, 2025.
[30]
M. Spanghero och P. Papadimitratos, "UnReference: analysis of the effect of spoofing on RTK reference stations for connected rovers," i Proceedings of the 2025 IEEE/ION Position, Localization and Navigation Symposium (PLANS), Salt Lake City, UT, USA, 2025, s. 1-12.
[31]
E. Listo Zec et al., "On the effects of similarity metrics in decentralized deep learning under distributional shift," Transactions on Machine Learning Research, vol. 2025-January, s. 1-23, 2025.
[32]
G. Verardo et al., "FMM-Head: Enhancing Autoencoder-Based ECG Anomaly Detection with Prior Knowledge," i Pattern Recognition and Artificial Intelligence - 4th International Conference, ICPRAI 2024, Proceedings, 2025, s. 18-32.
[33]
S. Sheikholeslami, "Tools and Methods for Distributed and Large-Scale Training of Deep Neural Networks," Doktorsavhandling Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2025:28, 2025.
[34]
S. Sheikholeslami et al., "Utilizing Large Language Models for Ablation Studies in Machine Learning and Deep Learning," i The 5th Workshop on Machine Learning and Systems (EuroMLSys), co-located with the 20th European Conference on Computer Systems (EuroSys), 2025.
[35]
A. H. Akhavan Rahnama, "Evaluating the Faithfulness of Local Feature Attribution Explanations : Can We Trust Explainable AI?," Doktorsavhandling Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2025:23, 2025.
[36]
M. Spanghero och P. Papadimitratos, "Consumer INS coupled with carrier phase measurements for GNSS spoofing detection," i ION ITM/PTTI, International Technical Meeting January 27 - 30, 2025 Long Beach, CA, 2025.
[37]
F. Cornell et al., "Unsupervised Ontology- and Taxonomy Construction Through Hyperbolic Relational Domains and Ranges," i Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2023, Revised Selected Papers, 2025, s. 339-348.
[38]
A. Alkhatib, "Addressing Shortcomings of Explainable Machine Learning Methods," Doktorsavhandling Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2025:11, 2025.
[39]
E. Listo Zec, "Decentralized deep learning in statistically heterogeneous environments," Doktorsavhandling Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2025:4, 2025.
[40]
M. Fragkoulis et al., "A survey on the evolution of stream processing systems," The VLDB journal, vol. 33, no. 2, s. 507-541, 2024.
[41]
J. Spenger, P. Carbone och P. Haller, "A Survey of Actor-Like Programming Models for Serverless Computing," i Active Object Languages : Current Research Trends, Frank de Boer, Ferruccio Damiani, Reiner Hähnle, Einar Broch Johnsen, Eduard Kamburjan red., : Springer Nature, 2024, s. 123-146.
[42]
Z. Xu et al., "A Semi-Supervised Model for Non-Cellular Elements Segmentation in Microscopy Images of Wood," i 2024 IEEE International Conference on Big Data (BigData), 2024, s. 2049-2056.
[43]
D. Tiwari, "Augmenting Test Oracles with Production Observations," Doktorsavhandling Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2024:87, 2024.
[44]
B. Lindqvist och A. Podobas, "Algorithms for Fast Spiking Neural Network Simulation on FPGAs," IEEE Access, vol. 12, s. 150334-150353, 2024.
[45]
V. Palmkvist, "Abstraction, Composition, and Resolvable Ambiguity in Programming Language Implementation," Doktorsavhandling Stockholm : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2024:69, 2024.
[46]
F. Schmidt et al., "A Scalable System Architecture for Composition and Deployment of Machine Learning Models in Cognitive Behavioral Therapy," i 2024 IEEE International Conference on Digital Health (ICDH), 2024, s. 79-86.
[47]
K. Segeljakt, S. Haridi och P. Carbone, "AquaLang : A Dataflow Programming Language," i DEBS 2024 - Proceedings of the 18th ACM International Conference on Distributed and Event-Based Systems, 2024, s. 42-53.
[48]
M. Polverini et al., "Achieving Best-path Selection at Line Rate through the SRv6 Live-Live Behavior," i Proceedings of IEEE/IFIP Network Operations and Management Symposium 2024, NOMS 2024, 2024.
[49]
A. Q. Khan et al., "A Taxonomy for Cloud Storage Cost," i Management of Digital EcoSystems - 15th International Conference, MEDES 2023, Revised Selected Papers, 2024, s. 317-330.
[50]
S. Ennadir et al., "A Simple and Yet Fairly Effective Defense for Graph Neural Networks," i AAAI Technical Track on Safe, Robust and Responsible AI Track, 2024, s. 21063-21071.
Fullständig lista i KTH:s publikationsportal