Bojchevski, Aleksandar

34 publications

ICLRW 2025 Kurtail : Kurtosis-Based LLM Quantization Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski, Evangelos Eleftheriou, Martino Dazzi

TMLR 2025 Node-Level Data Valuation on Graphs Simone Antonelli, Aleksandar Bojchevski

NeurIPS 2025 One Sample Is Enough to Make Conformal Prediction Robust Soroush H. Zargarbashi, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski

ICLR 2025 Robust Conformal Prediction with a Single Binary Certificate Soroush H. Zargarbashi, Aleksandar Bojchevski

ICLR 2024 Conformal Inductive Graph Neural Networks Soroush H. Zargarbashi, Aleksandar Bojchevski

ICLR 2024 Rethinking Label Poisoning for GNNs: Pitfalls and Attacks Vijay Lingam, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski

ICML 2024 Robust yet Efficient Conformal Prediction Sets Soroush H. Zargarbashi, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski

NeurIPS 2024 SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors Vijay Lingam, Atula Tejaswi, Aditya Vavre, Aneesh Shetty, Gautham Krishna Gudur, Joydeep Ghosh, Alex Dimakis, Eunsol Choi, Aleksandar Bojchevski, Sujay Sanghavi

ICMLW 2024 SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors Vijay Lingam, Atula Tejaswi Neerkaje, Aditya Vavre, Aneesh Shetty, Gautham Krishna Gudur, Joydeep Ghosh, Alex Dimakis, Eunsol Choi, Aleksandar Bojchevski, Sujay Sanghavi

ICMLW 2024 SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors Vijay Lingam, Atula Tejaswi Neerkaje, Aditya Vavre, Aneesh Shetty, Gautham Krishna Gudur, Joydeep Ghosh, Eunsol Choi, Alex Dimakis, Aleksandar Bojchevski, Sujay Sanghavi

NeurIPSW 2024 SVFT: Parameter-Efficient Fine-Tuning with Singular Vectors Vijay Lingam, Atula Tejaswi, Aditya Vavre, Aneesh Shetty, Gautham Krishna Gudur, Joydeep Ghosh, Alex Dimakis, Eunsol Choi, Aleksandar Bojchevski, Sujay Sanghavi

AAAI 2023 Adversarial Weight Perturbation Improves Generalization in Graph Neural Networks Yihan Wu, Aleksandar Bojchevski, Heng Huang

NeurIPS 2023 Are GATs Out of Balance? Nimrah Mustafa, Aleksandar Bojchevski, Rebekka Burkholz

ICML 2023 Conformal Prediction Sets for Graph Neural Networks Soroush H. Zargarbashi, Simone Antonelli, Aleksandar Bojchevski

NeurIPS 2023 Hierarchical Randomized Smoothing Yan Scholten, Jan Schuchardt, Aleksandar Bojchevski, Stephan Günnemann

ICLR 2023 Localized Randomized Smoothing for Collective Robustness Certification Jan Schuchardt, Tom Wollschläger, Aleksandar Bojchevski, Stephan Günnemann

ICLRW 2023 Pitfalls in Evaluating GNNs Under Label Poisoning Attacks Vijay Lingam, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski

AISTATS 2023 Probing Graph Representations Mohammad Sadegh Akhondzadeh, Vijay Lingam, Aleksandar Bojchevski

ICLRW 2023 Probing Graph Representations Mohammad Sadegh Akhondzadeh, Vijay Lingam, Aleksandar Bojchevski

ICMLW 2023 Rethinking Label Poisoning for GNNs: Pitfalls and Attacks Vijay Lingam, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski

ICLR 2023 Unveiling the Sampling Density in Non-Uniform Geometric Graphs Raffaele Paolino, Aleksandar Bojchevski, Stephan Günnemann, Gitta Kutyniok, Ron Levie

NeurIPS 2022 Are Defenses for Graph Neural Networks Robust? Felix Mujkanovic, Simon Geisler, Stephan Günnemann, Aleksandar Bojchevski

ICLR 2022 Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness Simon Geisler, Johanna Sommer, Jan Schuchardt, Aleksandar Bojchevski, Stephan Günnemann

NeurIPS 2022 Randomized Message-Interception Smoothing: Gray-Box Certificates for Graph Neural Networks Yan Scholten, Jan Schuchardt, Simon Geisler, Aleksandar Bojchevski, Stephan Günnemann

AISTATS 2021 Completing the Picture: Randomized Smoothing Suffers from the Curse of Dimensionality for a Large Family of Distributions Yihan Wu, Aleksandar Bojchevski, Aleksei Kuvshinov, Stephan Günnemann

ICLR 2021 Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks Jan Schuchardt, Aleksandar Bojchevski, Johannes Gasteiger, Stephan Günnemann

NeurIPS 2021 Robustness of Graph Neural Networks at Scale Simon Geisler, Tobias Schmidt, Hakan Şirin, Daniel Zügner, Aleksandar Bojchevski, Stephan Günnemann

ICML 2020 Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More Aleksandar Bojchevski, Johannes Gasteiger, Stephan Günnemann

ICML 2019 Adversarial Attacks on Node Embeddings via Graph Poisoning Aleksandar Bojchevski, Stephan Günnemann

NeurIPS 2019 Certifiable Robustness to Graph Perturbations Aleksandar Bojchevski, Stephan Günnemann

ICLR 2019 Predict Then Propagate: Graph Neural Networks Meet Personalized PageRank Johannes Gasteiger, Aleksandar Bojchevski, Stephan Günnemann

AAAI 2018 Bayesian Robust Attributed Graph Clustering: Joint Learning of Partial Anomalies and Group Structure Aleksandar Bojchevski, Stephan Günnemann

ICLR 2018 Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking Aleksandar Bojchevski, Stephan Günnemann

ICML 2018 NetGAN: Generating Graphs via Random Walks Aleksandar Bojchevski, Oleksandr Shchur, Daniel Zügner, Stephan Günnemann